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Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
DOI 10.1186/s40810-016-0021-4
MEETING ABSTRACTS
Open Access
19th biennial IPEG Meeting
Nijmegen, The Netherlands. 26-30 October 2016
Published: 29 November 2016
Training course
A1
Thalamocortical sleep oscillations
Igor Timofeev1,2
1
Department of Psychiatry and Neuroscience, Université Laval, Québec,
Canada; 2Centre de recherche de l’Institut universitaire en santé mentale
de Québec (CRIUSMQ), Université Laval, Québec, Canada
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A1
In waking and sleeping states, thalamocortical system generates a
variety of oscillations ranging from 0.1 Hz to hundreds of Hz. Most of
them are present during NREM sleep, but slower activities prevail in
this state of vigilance. Thalamocortical network is organized in a loop
in which thalamocortical cells excite reticular thalamic and neocortical cells, reticular thalamic cells inhibit thalamocortical cells and
corticothalamic cells excite thalamocortical and reticular thalamic
cells. Despite stable anatomical connectivity, different types of oscillations preferentially originate either in neocortex or in thalamus.
During sleep stage 2, spindle oscillation (9–15 Hz) is a dominant type
of activity. It is well accepted that spindles originate in the thalamus
via interplay of firing of reticular thalamic and thalamocortical
neurons, but neocortex controls spindle generation. Spindles can be
divided on fast and slow. Several properties of slow spindles do not
match known mechanisms of their thalamic origin.
Slow oscillation (about 1 Hz) dominates slow-wave sleep stage. Each
slow wave is composed of hyperpolarized or silent and depolarized
and active state. Active states may be accompanied by spindles and
higher frequency activities. Slow waves originate mainly in deep
cortical layers from which they propagate to more superficial layers
and they also propagate horizontally. Full expression of slow wave
activities requires the presence of thalamus, although slow oscillation
can be recorded in athalamic preparations.
Therefore, despite the fact of preferential origin of different sleep
oscillations in either neocortex or in thalamus, only the full thalamocortical network can generate sleep activities with known properties.
Support: CIHR and NSERC.
measures. This will be illustrated by means of pertinent examples.
These include elucidating the mechanisms of stimulant action remediating deficient impulse control and the role of the cannabinoid
system in human working memory, as well as drug effects on
sensory gating and specific aspects of visual-spatial attention. Other
examples concern the added sensitivity of EEG and ERP measures,
relative to that of performance measures, in detecting effects of alcohol, and more generally in monitoring and predicting vigilance and
the ability to detect external signals in the immediate future. Relations between brain signals and cognitive competences are revealed
by either comparing different individuals, or moment-to-moment
fluctuations within individuals, or differences in state (e.g., druginduced) within individuals.
A3
EEG and ERP as key techniques for functional brain alterations
studies
P. F. Fabene
Department Neuroscience, Biomedicine and Movement, School of
Medicine, University of Verona, Verona, Italy
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A3
Behavioral studies in rodents are basically based on inferring cognitive
processes out of locomotor activity. In other words, we evaluate memory processes during Morris water maze, or Novel object recognition
based on the time spent of the given subject in close proximity of an
item, platform, or the time required to reach or leave an area of the
cage/maze. By the mean of automatic scoring systems (e.g.: Ethovision,
AniMaze, etc.) we are provided by objective measurements, which
should be in any case interpreted by the researcher. There is always a
lack of direct measurement of the cognitive processes. Integration of
behavioural scoring with electrical activity evaluation of different areas
involved in cognitive processing can be a useful tool, to provide
scientists further parameter helpful in data interpretation. We will thus
discuss the integration of EEG analysis in Alzheimer’s mild cognitive
impairment and acoustic ERPs in AD and epilepsy.
A2
Electropsychopharmacology: applying EEG and ERP to
psychopharmacology
Leon Kenemans
Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht,
Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A2
A4
Targeting EEG network oscillations: translational opportunities for
drug discovery science in psychiatric and neurodegenerative
disorders
A. Ahnaou (
[email protected])
Department of Neuroscience Discovery, Janssen Research &
Development, a Division of Janssen Pharmaceutica NV. Turnhoutseweg
30, B-2340 Beerse, Belgium
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A4
Electroencephalography (EEG), in particular event-related or evoked
potentials (ERPs), as well as their magnetic counterparts, can yield
useful supplementary information when interpreting effects of psychoactive substances on behavior. They can be used to elucidate the
neurocognitive mechanisms that underlie pharmacological modulation of behavior, or they may provide additional sensitivity to detect
neurocognitive effects that are not readily observable in behavioral
Despite decades of research in psychiatric and neurodegenerative
disorders, the attrition rate in clinical trials and late-stage drug discovery programs for the development of novel agents for disease
interception has been unacceptably high. The major issue facing
neuroscience drug discovery is that drugs that show good effectivity
in preclinical models often fail to meet clinical trials endpoints. The
© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
limitations of the traditional animal-based assays prompted a resurgence of interest in rethinking animal models and their predictability
and translational validity in translational neuroscience. Better translation of a biomarker and endophenotype of the disease might rapidly
provide information regarding the effects of drugs on the underlying
disease biology, bridge the translational gap and potentially lower the
rate of clinical trial attrition. An increasing number of experimental and
clinical observations suggest that those chronic brain disorders arise
from structural alterations in neuronal circuits, and therefore focus has
been shifted towards investigation of electrophysiological correlates of
the molecular pathology, with emphasis on neural oscillations and connectivity as promising candidate biomarkers of neuronal disorders.
State-of-the-art examples of pharmacological studies modeling
abnormal network oscillations and disturbed connectivity of several
CNS disorders will be discussed.
A5
Source localization using LORETA software
Sebastian Olbrich (
[email protected])
Department for Psychiatry, Psychotherapy and Psychosomatic, University
of Zurich, Zurich, Switzerland
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A5
The training course will be dedicated to the usage of LORETA software for localization of neuronal sources of EEG activity. After a brief
introduction into the underlying physiology and theoretical assumptions of source localization techniques, an example of how to apply
the software to EEG recordings will be shown, including limitations
and caveats. Further focus will be on connectivity measures between
intracortical areas as well as a short overview on statistical analysis
implemented in the LORETA software.
A6
EEG Analysis methods beyond standard assessments
Robert Oostenveld1,2 (
[email protected])
1
Donders Institute for Brain, Cognition and Behaviour, Radboud
University, Nijmegen, The Netherlands; 2NatMEG, Karolinska Institute,
Stockholm, Sweden
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A6
Data analysis methods for EEG have shown great progress over the
last two decades, partially inspired or driven by methodological advancements in adjacent research methods such as MEG, intracranial
recordings and functional MRI.
In this educational session I will go over the analysis methods that
can be considered part of the traditional repertoire for EEG assessments and will extend that by highlighting some recent methodological advancements for data processing.
Among others, power spectral analysis techniques using multitapers,
statistical approaches based on non-parametric hypothesis, cluster
based inference, robust statistics and source reconstruction techniques based on spatial filtering will be explained. The focus will be
on introducing these techniques in an intuitive manner and providing pointers to data analysis tools that implement them.
A7
Personalized medicine in Depression and ADHD: Introduction and
EEG biomarkers for predicting treatment outcome
Martijn Arns1,2,3
1
neuroCare group, Munich, Germany; 2Research Institute Brainclinics,
Nijmegen, The Netherlands; 3Department of Experimental Psychology,
Utrecht University, Utrecht, The Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A7
At present stimulant medication, antidepressants and behavior therapy
are the most often applied and accepted treatments for ADHD and Depression. However, recent large-scale studies and meta-analyses have
demonstrated limitations of these treatments including reduced long-term
Page 2 of 34
efficacy of stimulant medication, limited efficacy of antidepressant medications and overall limited efficacy of behavioral interventions on the group
level. It hence becomes obvious there is a need for a re-conceptualization
of psychiatric disorders along the lines of NIMH proposed Research Domain Criteria (RDoC) or referred to as biomarkers or personalized medicine.
Personalized Medicine aims to prescribe the right treatment, for the right
person at the right time as opposed to the currently employed ‘one-sizefits-all’ approach. This development relies on identification of subgroups
using biomarkers.
This presentation will summarize the current status of EEG based
personalized medicine and present new results from large biomarker studies in depression and ADHD focused on resting-state
EEG. Several results from the iSPOT study (international Study to
Predict Optimized Treatment) in Depression and ADHD will be
presented [1,2,3,4,5]. In iSPOT-D, 1008 depressed patients are randomized to Escitalopram, Sertraline or Venlafaxine and in iSPOT-A
336 ADHD patients are prescribed with methylphenidate and
patients were assessed at baseline on resting-state EEG and other
measures. Several promising biomarkers that can predict treatment response and remission using baseline biomarkers will be
presented and the importance of gender differences will be
discussed in more detail.
References
1. Arns, M., Bruder, G., Hegerl, U., Spooner, C., Palmer, D. M., Etkin, A., . . .
Gordon, E. (2015a). EEG alpha asymmetry as a gender-specific predictor
of outcome to acute treatment with different antidepressant medications
in the randomized iSPOT-D study. Clinical Neurophysiology. doi: http://
dx.doi.org/10.1016/j.clinph.2015.05.032
2. Arns, M., Etkin, A., Hegerl, U., Williams, L. M., DeBattista, C., Palmer, D. M.,
.Gordon, E. (2015b). Frontal and rostral anterior cingulate (rACC) theta
EEG in depression: Implications for treatment outcome? European
Neuropsychopharmacology,. doi: 10.1016/j.euroneuro.2015.03.007
3. Arns, M., Gordon, E., & Boutros, N. N. (2015). EEG abnormalities are associated
with poorer depressive symptom outcomes with escitalopram and venlafaxineXR, but not sertraline: Results from the multicenter randomized iSPOT-D study.
Clinical EEG and Neuroscience. doi: 10.1177/1550059415621435
4. Olbrich, S., Tränkner, A., Surova, G., Gevirtz, R., Gordon, E., Hegerl, U., &
Arns, M. (2016). CNS- and ANS-arousal predict response to antidepressant
medication: Findings from the randomized iSPOT-D study. Journal of Psychiatric Research, 73, 108–115. doi: 10.1016/j.jpsychires.2015.12.001
5. Olbrich, S., van Dinteren, R., & Arns, M. (2016). Personalized medicine:
Review and perspectives of promising baseline EEG biomarkers in major
depressive disorder and attention deficit hyperactivity disorder.
Neuropsychobiology. doi: 10.1159/000437435
A8
Clinical applications of EEG in psychiatry
Nash Boutros
University of Missouri-Kansas City, Kansas City, MO, USA
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A8
Starting with an outline of the evolving discipline of Clinical
Psychiatric Electrophysiology a discussion of the value of diagnostic tests in general is given. The presentation then focuses on
the well-established clinical indications of the standard EEG in
the day to day practice of clinical psychiatry. Discussion will
cover panic disorder, autistic spectrum disorders, and repeated
aggression in some detail. Case vignettes are included to generate interactive discussion.
Keynotes
A9
The genesis of EEG phenomena: hot topics of the last decade
Fernando Lopes da Silva (
[email protected])
Centre of Neuroscience, Swammerdam Institute for Life Sciences,
University of Amsterdam, Science Park 904, Amsterdam 1098 XH, The
Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A9
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Since the turn of the century, the scope of EEG investigations became much broader, in particular due to the possibility of recording
the full, physiologically relevant range of brain activities from the
infra-slow to the high frequency spectral range, making use of wide
dynamic direct-current (DC) coupled amplifiers, and of accurate recordings of high frequency oscillations up to hundreds of Hz. This
has been denominated full-band or wide-band EEG. In this lecture,
however, I focus on the high frequency EEG/MEG phenomena or
High Frequency Oscillations (HFOs). These phenomena cover a
number of activities that range from 60 – 80 Hz to approximately
500 Hz. Interest for these phenomena has gained momentum in the
last decade. They appear in the healthy brain associated with
sensory, motor and cognitive events, and also in pathological cases,
particularly in epilepsy. Under the concept HFO, activities in the
gamma band (30 – 70 Hz) occupy a prominent place. A variety of
names are used to describe physiological EEG/MEG activity above
70 Hz such as high-gamma and the chi-band; in the context of
epilepsy specific types of oscillations have been described, namely
ripples (≈90 – 200 Hz) and fast ripples (≈ > 200Hz), but the corresponding frequency boundaries are rather fuzzy [1]. Here I will discuss
neuronal processes generating HFOs [1,2], a few relevant applications
in cognitive neuroscience and in epilepsy [3], and practical questions
regarding the possibilities and difficulties of reliably recording HFOs in
human, and distinguishing the latter from artifacts [4].
References
1. Buzsáki, G. and Lopes da Silva, F.H., High frequency oscillations in the
intact brain. Progr. Neurobiol. 2012; 98: 241–249.
2. Jefferys, JG, Menendez de la Prida, L, Wendling, F, Bragin, A, Avoli, M,
Timofeev, I, Lopes da Silva, FH. Mechanisms of physiological and
epileptic HFO generation. Progr Neurobiol. 2012; 98: 250–264.
3. Lopes da Silva, F.H., EEG and MEG: relevance to Neuroscience. Neuron,
2013; 80: 1112 – 1128.
4. Amiri, M, Lina, J-M, Pizzo, F, Gotman, J. High frequency oscillations and
spikes: separating real HFOs from false oscillations. Clin. Neurophysiol.
2016; 127: 187–196.
A10
Cellular basis of sleep slow oscillation: What is clear, what is not
Igor Timofeev1,2
1
Department of Psychiatry and Neuroscience, Université Laval, Québec,
Canada; 2Centre de recherche de l’Institut universitaire en santé mentale
de Québec (CRIUSMQ), Université Laval, Québec, Canada
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A10
The major type of activity generated by the thalamocortical system
during slow-wave sleep is the slow oscillation, composed of slow
waves repeated with a frequency of about 1 Hz. Each slow wave is
comprised of hyperpolarized silent state, often called down state,
and depolarized active state, often called up state. During wake and
REM sleep cortical neurons remain in active state.
What is likely known on slow wave generation: (a) Slow oscillation is
essentially cortical in origin, but it is modulated by thalamic activities.
(b) Cortical slow waves in adults start more in frontal areas and
propagate to other cortical areas, but multiple slow waves recorded
throughout cortical mantle remain local. (c) In ferrets, mice and cats
slow waves start mainly in layer 5, but in epileptic patients they originate around layer 3. (d) Silent states of slow oscillation are essentially periods of disfacilitation, but GABAergic activities can be
detected in a subset of neurons prior to the onset of silent states. (e)
Active states are dominated by excitatory and inhibitory synaptic activities; in anesthetized animals, these activities are balanced, in
sleeping animals inhibition largely dominates active states.
What we don’t know: (a) What triggers the onset of active state?
Three hypotheses are present: (1) Stochastic summation of spikeindependent minis occasionally leading to the first spike that engages the whole network. (2) Intrinsic activity of layer 5 pyramidal
cells (h-like current). (3) Self-organized onset of activity in groups of
neurons. (b) What terminates active states? Following hypotheses are
proposed: (1) Intrinsic neuronal firing frequency accommodation that
Page 3 of 34
decreases the overall excitatory drive. (2) Use-dependent synaptic depression. (3) Activity of Na+- and Ca2+-dependent K+ current. (4)
Extracortical signaling. All these mechanisms are present during wake
and REM sleep, but why active states are not terminated in these
states of vigilance remains unclear.
Support: CIHR and NSERC.
A11
GABAergic modulation of neuronal oscillations in animals and
humans and its consequences for working memory
Ole Jensen (
[email protected])
School of Psychology, University of Birmingham, Birmingham, B15 2TT,
UK
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A11
Background
Networks in the brain must rely on powerful mechanism for routing
and prioritizing information processing. In a larger set of attention and
memory studies we have investigated the notion that alpha oscillations
(9 – 12 Hz) are inhibitory and serve to route the information flow: ‘gating by inhibition’ [1]. The alpha band activity is under top-down control
by areas in the dorsal attention network. As such the alpha band
activity – previously believed to reflect a state of rest - serves an important role for shaping the functional architecture of the working
brain. Gamma band activity (50 – 100 Hz) reflects feed-forward processing and is modulated by the alpha oscillations. In animals is has been
demonstrated that GABAergic interneurons play an important role for
synchronizing neural populations [2]; however, it remains unknown if
these mechanistic principles generalize to human oscillations.
Methods
To investigate how GABAergic modulated affects gamma oscillations, we
recorded ongoing brain activity using magnetoencephalography (MEG) in
human subjects participating in a double-blind pharmacological study receiving placebo and lorazepam. Lorazepam is a benzodiazepine upregulating GABAergic conductance. This was done in participants while they
performed a visuospatial working memory (WM) task.
Results
The key finding was that occipital gamma power associated with WM
recognition increased with lorazepam dosage [3]. In addition, the frequency of the gamma activity decreased with dosage. This is consistent
with models derived from the rat hippocampus. With respect to oscillations in the alpha band, we observed a parametrical decrease with
drug dosage that also predicted a performance decrease. This is consistent with alpha oscillations reflecting functional inhibition.
Conclusion
We conclude that GABAergic interneurons are implicated in the generation of gamma and alpha oscillations in humans. As we will discuss these findings allow us to link neuronal dynamics to behavior in
humans by embracing established animal models.
References
1. Jensen O and Mazaheri A. Shaping functional architecture by oscillatory
alpha activity: gating by inhibition. Front Hum Neurosci 2010; 4:186.
2. Traub RD, Jefferts JGR, Whittington MA. Fast Oscillations in Cortical
Circuits. Boston: MIT Press, 1999
3. Lozano-Soldevilla D, ter Huurne N, Cools R, Jensen O. GABAergic modulation of visual gamma and alpha oscillations and its consequences for
working memory performance. Curr Biol 2014; 24:2878–2887.
A12
Refining brain oscillatory targets for intervention in ADHD
Sandra K Loo
Department of Psychiatry and Biobehavioral Sciences, UCLA, Los
Angeles, CA, USA
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A12
Background
Brain oscillatory patterns are increasingly used as biological markers of
psychiatric disease, developmental course, and treatment response. In
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
order to maximize effectiveness, advanced approaches should enable a
mechanistic understanding of how brain rhythms carry out the
cognitive and emotional processes that, when disordered, may lead to
mental disorders. This will aide in the identification of interventions that
show evidence of mechanism and target engagement and will increase
our understanding of how efficacious interventions achieve their effect
within clinical populations
In this presentation, important considerations in the process of
identifying and refining potential brain oscillatory targets that may
be useful for treatment monitoring and response will be presented.
For example, approaches to characterizing the significant variability
and heterogeneity that exists within ADHD and typically developing
populations are discussed. In addition, the need for refined measurements and signal processing techniques that increase the signal to noise ratio are described. Finally, issues such as targeting
cognitive dysfunction and/or modeling developmental changes
are considered.
We then describe how this approach has been implemented to identify and validate brain targets (biomarkers) in clinical trials for
children with attention-deficit/hyperactivity disorder (ADHD). In
addition, these data will be used to illustrate potential applications
for neuromodulation approaches in ADHD as well as other neurodevelopmental disorders such as autism spectrum disorder (ASD) and
Tourette’s Syndrome.
Relevance and Implications for future research
The data presented suggest that EEG-based biomarkers may be
useful indices of developmental course of disorder, behavioral and
cognitive functioning, and prediction of treatment response.
Although the clinical utility of EEG measures is promising, more
research is needed before these findings can be implemented in
clinical practice.
A13
Elucidating mechanisms of sleep-wake regulation in humans with
pharmaco-genetic tools
Hans-Peter Landolt1,2
1
Institute of Pharmacology and Toxicology, University of Zürich, Zürich,
Switzerland; 2Zürich Center for interdisciplinary Sleep Research,
University of Zürich, Zürich, Switzerland
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A13
Epidemiological studies demonstrate that sleep-wake disorders are
highly prevalent in society and rank third in the prevalence of all
brain diseases. The normal alternation between sleep and wakefulness is tightly regulated, and prolonged EEG recordings show that
distinct sleep and wake states reflect highly complex behaviors. Little
is currently known about the molecular underpinnings of physiological sleep-wake regulation and functions. To foster our knowledge
of the pathophysiology of sleep-wake disorders and their possible rational treatment, a molecular understanding of sleep-wake regulatory
processes is indispensable. Accumulating evidence suggests that
important aspects of sleep-wake regulation in animals and humans
are genetically controlled and, thus, have a molecular basis. Consistent with this view, the combination of neurophysiologic, genetic and
pharmacologic tools revealed specific roles for adenosine, dopamine
and glutamate receptors and metabolic pathways in sleep-wake
regulation. These studies also showed that functional allelic variation
in candidate genes can profoundly affect functional aspects of sleep
and wakefulness, even in healthy humans and under physiological
conditions, as well as modulate individual responses to hypnotic and
wake-promoting agents. These insights may provide a rationale for
personalized sleep-wake pharmacotherapy (Holst et al., Annu Rev
Phamacol Toxicol, 2016). In the future, together with novel ‘omics’-studies of sleep in health and disease, they may pave the way for the discovery of new evidence-based treatments of sleep-wake pathologies
such as insomnia and the pharmacological enhancement of sleepassociated brain functions such as neuronal plasticity.
Research supported by the Swiss National Science Foundation (grant #
320030_135414 & 320030_163439) and the Clinical Research Priority
Program “Sleep and Health” of the University of Zürich.
Page 4 of 34
Symposia
A14
The dos and don’ts for electrophysiological connectivity analysis
Jan Mathijs Schoffelen (
[email protected])
Donders Institute, Radboud University, Nijmegen, The Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A14
In recent years it has been increasingly recognized that insight
into the dynamics of interareal interactions is crucial for our understanding of normal and pathological brain function. Methodological developments and open source availability of advanced
analysis tools have enabled the wider neuroscientific community
to estimate a wide range of connectivity metrics from noninvasively obtained electrophysiological signals. Next to deciding
on an appropriate analysis strategy, researchers are faced with
the challenge to correctly interpret their findings. Volume conduction and electromagnetic field spread cause neuronal signals
to be picked up by multiple channels at once, causing spurious
estimates of connectivity. Comparison across experimental groups
and conditions may be confounded by differences in univariate
signal properties such as signal-to-noise ratio. I will illustrate
some of these interpretational pitfalls and provide some recommendations that may need to be taken into account to improve
the validity of the interpretation of EEG/MEG connectivity
studies.
A15
MEG as a routine diagnostic tool in memory clinic patients
Alida A. Gouw1,2, Arjan Hillebrand2, Matteo Demuru1,2, Peterjan Ris2,
Philip Scheltens1, Cornelis J Stam2
1
Alzheimer Center and Department of Neurology, Neuroscience Campus
Amsterdam, VU University Medical Center, Amsterdam, The Netherlands;
2
Department of Clinical Neurophysiology and MEG 4Center,
Neuroscience Campus Amsterdam, VU University Medical Center,
Amsterdam, The Netherlands
Correspondence: Alida A Gouw (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A15
Background
Electro-encephalography (EEG) has been used as a routine diagnostic
tool for patients of the Alzheimer Center Amsterdam since 2001 [1]. Recently, EEG has partly been replaced by magneto-encephalography
(MEG), because it may be more sensitive for pathology in disease
specific regions. We investigated its discriminative value between
Alzheimer’s disease (AD) and subjective cognitive decline (SCD) using a
machine learning approach.
Methods
MEG was recorded in an unselected proportion of memory clinic
patients as part of a routine workup. MEG data were co-registered
with a head-size matched template-MRI and source-reconstructed
by projection onto 90 AAL-regions using beamforming [2, 3]. Clinical reports were made using visual and spectral analyses, blinded
for clinical information. Diagnoses were made in a weekly multidisciplinary meeting using full clinical information and additional
investigations, such as MRI and neuropsychological examination.
The first 20 AD and 20 SCD patients were further analysed. Directed connectivity (directed phase transfer entropy [dPTE]) and
minimum spanning tree (MST) based network measures (8–13 Hz
band) were calculated per region [3–5], where the imbalance in information flow between regions was used to construct the MST.
Combinations of MEG measures at eight AD-specific regions (left
and right hippocampus, parahippocampal gyrus, precuneus,
cuneus) were entered into random forest models to classify
between patient groups.
Results
From April 2015 to July 2016, 101 patients received an MEG. Diagnoses were AD (n = 26); SCD (n = 24); psychiatric disorder (n = 18); mild
cognitive impairment (n = 10); fronto-temporal dementia (n = 7);
Lewy body dementia (n = 5); vascular dementia (n = 1); and other/
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
postponed diagnosis (n = 10). One patient’s MEG diagnostic report
could not be made because of movement artefacts. Her MRI and
neuropsychological examination could also not be completed and
she was diagnosed with severe AD based on clinical information and
cerebrospinal fluid biomarkers. In the distinction between AD (age
64.8 ± 7.9, 50 % female) and SCD (age 61.4 ± 21.8, 55 % female), a
random forest model with relative theta power of the eight AD
regions yielded an accuracy of 0.810. Addition of dPTE for these regions increased the accuracy to 0.843. When network measures (leaf
fraction, diameter, tree hierarchy) were added to the model with
theta power and dPTE an accuracy of 0.812 was found.
Conclusion
Routine diagnostic MEG is feasible in a memory clinic screening and
has a high accuracy in the discrimination between AD and SCD using
theta power in AD-specific regions. Directed connectivity has modest
additional diagnostic value whereas network measures did not add
to the diagnostic accuracy.
References
1. Liedorp M, van der Flier WM, Hoogervorst ELJ, Scheltens P, Stam CJ.
Associations between patterns of EEG abnormalities and diagnosis in a
large memory clinic cohort. Dement Geriatr Cogn Disord 2009; 27(1):18–23.
2. Hillebrand A, Barnes GR, Bosboom JL, Berendse HW, Stam CJ. Frequencydependent functional connectivity within resting-state networks: an
atlas-based MEG beamformer solution. Neuroimage 2012; 59(4):3909–21.
3. Hillebrand A, Tewarie P, van Dellen E, Yu M, Carbo EWS, Douw L, et al.
Direction of information flow in large-scale resting-state networks is
frequency-dependent. PNAS 2016; 113(14):3867–72.
4. Stam CJ, Tewarie P, Van Dellen E, van Straaten ECW, Hillebrand A, Van
Mieghem P. The trees and the forest: Characterization of complex brain
networks with minimum spanning trees. Int J Psychophysiol 2014;
92(3):129–38.
5. Lobier M, Siebenhühner F, Palva S, Palva JM. Phase transfer entropy: a
novel phase-based measure for directed connectivity in networks
coupled by oscillatory interactions. Neuroimage 2014; 85:853–72.
A16
Identification of the epileptogenic zone using MEG network
analysis
Ida A. Nissen1, Cornelis J. Stam1, Ilse E. C. W. van Straaten1, Jaap C.
Reijneveld2, Arjan Hillebrand1
1
Department of Clinical Neurophysiology and MEG Center, VU University
Medical Center, Amsterdam, the Netherlands; 2Brain Tumor Center
Amsterdam & Department of Neurology, VU University Medical Center,
Amsterdam, the Netherlands
Correspondence: Ida A. Nissen (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A16
Introduction
Epilepsy is increasingly seen as a brain network disorder [1–3]. Patients
with epilepsy have been shown to have different networks compared to
healthy controls, deviating from the optimal configuration and with abnormal network hubs [4–8]. A potent treatment for pharmacoresistant
epilepsy is epilepsy surgery. The goal of epilepsy surgery is to remove or
disconnect the epileptogenic zone, which renders the patient seizurefree [9]. A hypothesis about the location of the epileptogenic zone can
be based on techniques such as electroencephalography (EEG) and magnetoencephalography (MEG). However, establishing a hypothesis is
challenging and not always successful as currently one third of the patients continue to experience seizures after surgery [10]. New methods
are therefore needed to generate more accurate hypotheses about the
location of the epileptogenic zone such that more patients become
seizure-free. Our aim was to develop such a new method based on network theory. We hypothesized that the epileptogenic zone coincides or
connects with hubs and information senders in the network.
Methods
We analyzed eyes-closed resting-state MEG recordings of 22 patients
with pharmacoresistant epilepsy. The time series in source space
(virtual electrodes) were reconstructed using beamforming for 90 regions of the AAL atlas [11]. We estimated functional connectivity
Page 5 of 34
between those regions using phase lag index (PLI) [12] in the broadband (0.5-48Hz). We used 20 epochs of 3.28 s each without artefacts
or epileptiform activity. We generated the minimum spanning tree
based on the PLI and calculated the betweenness centrality (an indicator of hubs) for each region. Furthermore, we assessed effective
connectivity (an indicator of information senders) using the directed
phase transfer entropy (dPTE) [11] for different frequency bands.
Results
ROIs with high broadband betweenness centrality (hubs) coincided
with the resection cavity (or resection lobe) in 8/14 (9/14) seizurefree patients and in 0/8 (0/8) patients with remaining seizures (73 %
(77 %) accuracy). For the effective connectivity, high dPTE values coincided with the resection cavity (or resection lobe) in 8/14 (10/14)
seizure-free patients and only in 2/8 (2/8) patients with remaining
seizures (64 % (73 %) accuracy) in the delta band (0.5-4Hz).
Implications
Hub regions and strong senders are markers of the epileptogenic zone.
These results are a first step towards a localization method that can be
applied to MEG recordings even in the absence of epileptiform activity,
yielding an improvement in localization and finally surgery outcome.
References
1. Kramer MA, Cash SS: Epilepsy as a disorder of cortical network
organization. The neuroscientist 2012, 18: 360–372.
2. Stam CJ: Modern network science of neurological disorders. Nature
Reviews Neuroscience 2014, 15: 683–695.
3. van Diessen E, Diederen SJ, Braun KP, Jansen FE, Stam CJ: Functional and
structural brain networks in epilepsy: what have we learned? Epilepsia
2013, 54: 1855–1865.
4. Bernhardt BC, Chen Z, He Y, Evans AC, Bernasconi N: Graph-theoretical analysis
reveals disrupted small-world organization of cortical thickness correlation networks in temporal lobe epilepsy. Cerebral cortex 2011, 21: 2147–2157.
5. Jin S-H, Jeong W, Chung CK: Mesial temporal lobe epilepsy with hippocampal sclerosis is a network disorder with altered cortical hubs. Epilepsia
2015, 56: 772–779.
6. Liao W, Zhang Z, Pan Z, Mantini D, Ding J, Duan X et al.: Altered
functional connectivity and small-world in mesial temporal lobe epilepsy.
PloS one 2010, 5: e8525.
7. van Diessen E, Hanemaaijer JI, Otte WM, Zelmann R, Jacobs J, Jansen FE
et al.: Are high frequency oscillations associated with altered network
topology in partial epilepsy? Neuroimage 2013, 82: 564–573.
8. Zhang Z, Liao W, Chen H, Mantini D, Ding JR, Xu Q et al.: Altered
functional-structural coupling of large-scale brain networks in idiopathic
generalized epilepsy. Brain 2011, 134: 2912–2928.
9. Luders HO, Najm I, Nair D, Widdess-Walsh P, Bingman W: The epileptogenic zone: general principles. Epileptic disorders 2006, 8: S1.
10. Jobst BC, Cascino GD: Resective Epilepsy Surgery for Drug-Resistant Focal
Epilepsy: A Review. JAMA 2015, 313: 285–293.
11. Hillebrand A, Tewarie P, van Dellen E, Yu M, Carbo EW, Douw L et al.:
Direction of information flow in large-scale resting-state networks is
frequency-dependent. Proceedings of the National Academy of Sciences
2016, 113: 3867–3872.
12. Stam CJ, Nolte G, Daffertshofer A: Phase lag index: assessment of functional
connectivity from multi-channel EEG and MEG with diminished bias from
common sources. Human brain mapping 2007, 28: 1178–1193.
A17
EEG biomarker integration for better decision making in clinical
trials
Sonja Simpraga1, Ricardo Alvarez-Jimenez2, Huibert D Mansvelder1, Joop
MA van Gerven2, Geert Jan Groeneveld2,3, Simon-Shlomo Poil1,4*, Klaus
Linkenkaer-Hansen1*
1
Dept. Integrative Neurophysiology, CNCR, Neuroscience Campus
Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;
2
Dept. Clinical Pharmacology, Centre for Human Drug Research, Leiden,
Netherlands; 3Dept. Neurology, VU University Medical Center,
Amsterdam, Netherlands; 4NBT Analytics BV, Amsterdam, Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A17
*
These authors contributed equally
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Brain disorders are a huge burden on the health care system, key issues being inaccurate diagnosis and insufficient treatment options.
Hence, there is an urgent need for biomarkers that monitor disease
status or therapeutic response. Current biomarkers lack the desired
accuracy, because of the large variability in healthy subjects and the
often subtle disease-related changes. In EEG, however, pathophysiology is often expressed in multiple ways. Here we show that an
integrative approach in which any biomarker that carries complementary information about a disease or therapeutic intervention
can result in an accurate diagnostic index for better decision making
in clinical trials.
Recently, we showed that EEG biomarker integration improves the prediction of conversion from mild cognitive impairment to Alzheimer’s
disease (AD) compared with a single-biomarker based prediction [1].
The integrative biomarker index can be used for stratification of
patients at recruitment in clinical studies and for documenting and
quantifying effects of intervention.
Here, we provide additional proof-of-concept that EEG-based
prediction can be improved with the integrative biomarker approach in clinical trials where a drug is tested in a scopolamine
challenge model in healthy subjects. Scopolamine is the most
extensively studied and used model for cognitive impairment
and resembles the changes seen in AD patients [2]. It is used
in drug development to demonstrate the reversal of the temporary scopolamine-induced cognitive deficits by a cognition
enhancing compound. For this purpose, we have developed an
integrative EEG-biomarker index (mAChR index) that is optimally sensitive to the CNS effects of scopolamine, to objectively determine whether reversal of scopolamine effects by a
cholinergic compound is successful. The mAChR index yielded
higher classification performance than any individual EEG biomarker with accuracy, sensitivity, specificity and precision of
90 %. This significantly outperforms the single-best EEG biomarker (relative delta power). Validation on an independent dataset indicated the robustness of the index. To examine the validity
of scopolamine as a cognitive impairment model, we applied this
integrative index on healthy elderly controls and Alzheimer’s patients and observed that this index indeed differentiates patients
from controls.
We address this by using novel features of the Neurophysiological
Biomarker Toolbox (http://www.nbtwiki.net/), which employ datamining algorithms to combine the information from multiple biomarkers. Our results demonstrate that integrating information from
multiple EEG biomarkers better captures the unique phenotype of an
individual patient and is a promising approach to enhance accuracy
and reduce the multiple-comparisons problem when using EEG in
clinical trials.
References
1. Poil SS, de Haan W, van der Flier WM, Mansvelder HD, Scheltens P,
Linkenkaer-Hansen K. Integrative EEG biomarkers predict progression
to Alzheimer’s disease at the MCI stage. Front Aging Neurosci.
2013; 5:58.
2. Klinkenberg I, Blokland A. The validity of scopolamine as a
pharmacological model for cognitive impairment: A review of animal
behavioral studies. Neurosci Biobehav Rev. 2010; 34:1307–50.
A18
Continuous EEG and deep learning for outcome prediction in
postanoxic coma
Michel JAM van Putten1,2, Marleen C Tjepkema-Cloostermans1, Jeannette
Hofmeijer2,3
1
Department of neurology and clinical neurophysiology, Medisch
Spectrum Twente, Enschede, Netherlands; 2Clinical Neurophysiology,
University of Twente, Enschede, the Netherlands; 3Department of
neurology, Rijnstate Ziekenhuis, Arnhem, Netherlands
Correspondence: Michel JAM van Putten
(
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A18
Page 6 of 34
Introduction
Reliable outcome prediction in approximately 50 % of patients with a
postanoxic encephalopathy is possible with visual interpretation of continuous EEG recorded within 24 h after cardiac arrest [1–6]. To assist in
the visual assessment, we developed the Cerebral Recovery Index [7]
and, more recently, a random forest classifier, showing similar performance for outcome prediction as visual assessment of the EEG [8]. Deep
Learning may advance the prognostic value of EEG significantly, in part
as it does not depend on ‘hand-made’ features [3, 9].
Methods
We used data from the EEG database of the Medisch Spectrum
Twente and Rijnstate hospitals with recordings from patients treated
in the Intensive Care Unit with a postanoxic encephalopathy after a
cardiac arrest. EEGs were recorded with twenty-one silver/silver chloride cup electrodes placed on the scalp according to the international
10–20 system using a Neurocenter EEG recording system (Clinical
Science Systems, Voorschoten, The Netherlands) or a Nihon Kohden
system (VCM Medical, the Netherlands). Neurological outcome
(Cerebral performance category scores) was dichotomized as good (no
or mild neurological impairment) or poor (severe neurological impairment, vegetative state or death) at 6 months after cardiac arrest.
We implemented a convolutional neural network (CNN) in python
with TensorFlow on a CentOS system with the NVIDIA GTX-1080 as
GPU. The input layer had dimensions 128x19 to process the raw 19channel EEG. EEGs were analyzed using non-overlapping 2 s epochs
using 5 min segments at each hour after cardiac arrest. For each
patient in the validation set, we calculated the percentage of 2 s
epochs within the 5 min segment that is predicted as poor neurological outcome. Using ROC curves the threshold at which poor outcome could be predicted with 100 % specificity was determined.
Results
After training with 131 EEGs, evaluation in an independent set with
33 patients showed that poor outcome could reliably be predicted in
67 % of the patients, without false positives (specificity 100 %) at =
12 h after cardiac arrest; poor outcome prediction at a later instance
(t = 24) was not possible with a specificity of 100 %.
Discussion and Conclusion
We show feasibility of CNN to process EEG in patients with a postanoxic
coma for prognostication. Pilot results show high predictive value for poor
neurological outcome. As temporal evolution of EEG patterns in these patients is significant [2], recurrent neural nets may outperform convolutional
networks. To understand the discriminating features, we currently explore
methods for interpretation and visualization of networks.
References
1. Hofmeijer, J., T. M. J. Beernink, F. H. Bosch, A. Beishuizen, M. C. TjepkemaCloostermans and M.J.A.M. van Putten. “Early EEG contributes to multimodal
outcome prediction of postanoxic coma.” Neurology 2015; (85): 1–7.
2. Hofmeijer, J. and M.J.A.M. Van Putten (2016). “EEG in postanoxic coma:
prognostic and diagnostic value.” Clinical Neurophysiology 127(4): 2047–2055.
3. LeCun, Y., Y. Bengio and G. Hinton. “Deep learning.” Nature 2015; 13(1): 35–35.
4. Rossetti, A. O., A. A. Rabinstein and M. Oddo. “Neurological prognostication
of outcome in patients in coma after cardiac arrest.” The Lancet Neurology
2016; 15(6): 597–609.
5. Sivaraju, A., E. J. Gilmore, C. R. Wira, A. Stevens, N. Rampal, J. J. Moeller, D.
M. Greer, L. J. Hirsch and N. Gaspard. “Prognostication of post-cardiac arrest coma: early clinical and electroencephalographic predictors of outcome.” Intensive Care Medicine 2015; 41(7): 1264–1272.
6. Tjepkema-Cloostermans, M. C., J. Hofmeijer, R. J. Trof, M. J. Blans, A.
Beishuizen and M.JA.M. van Putten. “Electroencephalogram predicts outcome in patients with postanoxic coma during mild therapeutic
hypothermia.” Critical care medicine 2015; 43(1).
7. Tjepkema-Cloostermans, M. C., F. B. van Meulen, G. Meinsma and M.J.A.M.
van Putten. “A Cerebral Recovery Index (CRI) for early prognosis in patients after cardiac arrest.” Critical Care 2013; 17(5): R252-R252.
8. Tjepkema-Cloostermans, M. C., J. Hofmeijer, A. Beishuizen, H. Hom, M. J.
Blans, F.H. Bosch and M.J.A.M. van Putten. “Cerebral Recovery Index: reliable help for prediction of neurological outcome after cardiac arrest”.
Submitted 2016
9. Angermueller, C., T. Pärnamaa, L. Parts and S. Oliver. “Deep Learning for
Computational Biology.” Molecular Systems Biology, 2016; (12): 878–878.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
A19
Prospects and challenges of Alzheimer’s classification using
resting-state EEG rhythms
Claudio Babiloni1,2, Antonio Ivano Triggiani3, Roberta Lizio1,2, Susanna
Cordone1, Antonio Brunetti4, Giacomo Tattoli4, Vitoantonio Bevilacqua4,
Andrea Soricelli5,6, Raffaele Ferri7, Flavio Nobili8, Loreto Gesualdo9, José
Carlos Millán-Calenti10, Ana Buján10, Rosanna Tortelli11, Valentina
Cardinali12,16, Orietta Barulli11, Antonio Giannini13, Pantaleo Spagnolo14,
Silvia Armenise15, Grazia Buenza12, Gaetano Scianatico11, Giancarlo
Logroscino11,15, Giovanni B. Frisoni16,17,18, and Claudio Del Percio5
1
Department of Physiology and Pharmacology “Vittorio Erspamer”,
University of Rome “La Sapienza”, Rome, Italy; 2Department of
Neuroscience, IRCCS San Raffaele Pisana, Rome, Italy; 3Department of
Clinical and Experimental Medicine, University of Foggia, Foggia, Italy;
4
Department of Electrical and Information Engineering, Polytechnic of
Bari, Bari, Italy; 5Department of Integrated Imaging, IRCCS SDN, Napoli,
Italy; 6Department of Motor Sciences and Healthiness, University of
Naples Parthenope, Naples, Italy; 7Department of Neurology, IRCCS Oasi
Institute for Research on Mental Retardation and Brain Aging, Troina,
Enna, Italy; 8Service of Clinical Neurophysiology (DiNOGMI; DipTeC),
IRCCS AOU S Martino-IST, Genoa, Italy; 9Dipartimento Emergenza e
Trapianti d’Organi (D.E.T.O), University of Bari, Bari, Italy; 10Gerontology
Research Group, Department of Medicine, Faculty of Health Sciences,
University of A Coruña, A Coruña, Spain; 11Unit of Neurodegenerative
Diseases, Department of Clinical Research in Neurology, University of
Bari “Aldo Moro”, Pia Fondazione Cardinale G. Panico, Tricase, Lecce,
Italy; 12Department of Neurology and Neurophysiopathology, Hospital
“Di Venere”, Bari, Italy; 13Department of Imaging - Division of Radiology,
Hospital “Di Venere”, Bari, Italy; 14Division of Neuroradiology, “F. Ferrari”
Hospital, Casarano, Lecce, Italy; 15Department of Radiology, Card. G.
Panico Hospital, Tricase, Lecce, Italy; 16Department of Basic Medical
Sciences, Neurosciences and Sense Organs, University of Bari “Aldo
Moro”, Bari, Italy; 17LENITEM (Laboratory of Epidemiology, Neuroimaging
and Telemedicine), IRCCS Centro “S. Giovanni di Dio-F.B.F.”, Brescia, Italy;
18
Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging,
University Hospitals and University of Geneva, Geneva, Switzerland
Correspondence: Claudio Babiloni (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A19
Background and aim
In the European FP7 “DECIDE” project (www.eu-decide.eu), a computinggrid infrastructure was developed to compute electroencephalographic
(EEG) and other biomarkers for diagnosis and instrumental assessment of
patients with Alzheimer’s disease (AD). In the framework of that project,
previous evidence showed a 75.5 % best accuracy in the classification of
120 Alzheimer’s disease (AD) patients with dementia and 100 matched
normal elderly (Nold) subjects based on cortical source current density
and linear lagged connectivity estimated by eLORETA freeware from resting state eyes-closed electroencephalographic (rsEEG) rhythms (Babiloni
et al., 2016). Specifically, that accuracy was reached using the ratio
between occipital delta and alpha1 current density for a linear univariate
classifier (receiver operating characteristic curves). Here we tested a nonlinear multivariate classification (artificial neural networks, ANNs) from the
same database of rsEEG markers.
Methods
Frequency bands of interest of the mentioned EEG database were delta
(2–4 Hz), theta (4–8 Hz), alpha1 (8–10.5 Hz), and alpha2 (10.5-13 Hz) as
an input to ANNs.
Results
ANN classification showed an accuracy of 77 % using the most 4 discriminative rsEEG markers of source current density (delta/alpha1 and
theta/alpha1 ratios in posterior cortical lobes). It also showed an accuracy of 72 % using the most 4 discriminative rsEEG markers of source
lagged linear connectivity (alphas between posterior cortical lobes).
With these 8 markers combined, an accuracy of 76 % was reached.
Overall, the present nonlinear (ANN) multivariate classification rate
cross-validated that obtained using a linear univariate classifier.
Conclusions
Although these linear rsEEG markers of cortical activity and connectivity unveil different relevant neurophysiological mechanisms underpinning cortical arousal and vigilance in AD patients, they provide
Page 7 of 34
quite redundant information for classification purposes. Future AD
studies should use ANNs combining the present markers with other
linear (i.e. directed transfer function) and nonlinear rsEEG markers to
improve the classification accuracy.
A20
Basmisanil, a negative allosteric modulator of GABA-A alpha5
subunit-containing receptors shows target and neuronal circuit
engagement in man
Joerg F Hipp1, Robert Comley1, Darren Bentley4, Michael Derks4, Pilar
Garces1, Frederic Knoflach2, Sian Lennon-Chrimes4, Stephane Nave1, Jana
Noldeke1, Nick Seneca1, Gerhard Trube2, Christoph Wandel3, Andrew
WThomas5, and Maria-Clemancia Hernandez2
1
Roche Pharma Research and Early Development, Translational Medicine
Neuroscience and Biomarkers, F. Hoffmann-La Roche Ltd., CH-4070 Basel,
Switzerland; 2Roche Pharma Research and Early Development, Discovery
Neuroscience, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland.
3
Roche Pharma Research and Early Development, Clinical Safety, F.
Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland; 4Roche Pharma
Research and Early Development, Clinical Pharmacology, F. Hoffmann-La
Roche Ltd., CH-4070 Basel, Switzerland; 5Roche Pharma Research and
Early Development, Medicinal Chemistry, F. Hoffmann-La Roche Ltd., CH4070 Basel, Switzerland
Correspondence: Joerg F Hipp (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A20
Background
Inhibitory GABAergic signaling plays a key role in brain function.
Drugs that enhance GABA-A receptor function (e.g. Benzodiazepines)
are widely used to treat conditions such as anxiety, insomnia, and
epilepsy. In contrast, no inhibitors of GABA-A receptors exist for clinical use. Preclinical animal studies suggest that releasing inhibition
by selectively inhibiting GABA-A alpha5 subunit-containing receptors
may be beneficial in conditions of impaired cognition such Down
syndrome, Schizophrenia, and Alzheimer’s disease, and may also
promote functional recovery after ischemic stroke, importantly
without the side effects associated to non-selective inhibitors. Here we
characterize basmisanil, a novel selective negative allosteric modulator
of GABA-A alpha5 receptors, in terms of in vitro pharmacology as well
as receptor occupancy and EEG signature in healthy volunteers.
Methods
Radioligand binding (3H-flumazenil) and voltage-clamp electrophysiology experiments were conducted in vitro on GABA-A receptors
expressed in HEK293 cells and Xenopus oocytes to demonstrate
binding and functional selectivity for the GABA-A alpha5 vs. alpha1/
2/3 subunit-containing receptors. A receptor occupancy study with
the GABAA a5 PET tracer [11C]Ro15-4513 was conducted in 10
healthy volunteers at 3 timepoints: baseline, 3, and 9 h following 1 of
4 doses of basmisanil (2x15, 2x60, 3x130, 3x1250 mg). A separate
EEG study in 12 volunteers measured at baseline, midazolam (5 mg),
and 14 days of basmisanil treatment (240 mg, bid).
Results
Basmisanil (RO5186582, RG1662) bound to cloned human GABA-A
alpha5 with 5-nM affinity and more than 90-fold selectivity versus
alpha1/2/3 subunit-containing receptors, and concentration-dependently
and reversibly inhibited the GABA-induced current of alpha5 expressing
cells, yet had weak or no activity on GABA-A receptors containing other
alpha subunits. Using PET, receptor occupancy was confirmed in vivo in
key regions of GABA-A alpha5 subunit containing receptors including
hippocampus, insula, prefrontal cortex, and ventral striatum. Spectral analysis of the resting EEG revealed power increase in theta to alpha-, and
decrease in the beta frequency range. This EEG signature was qualitatively opposite to that of Midazolam, a non-selective positive allosteric
modulator of GABA-A receptors. Basmisanil was safe and well tolerated,
and no treatment-emergent epileptiform abnormalities were observed.
Discussion
Basmisanil is a highly selective GABA-A alpha5 negative allosteric
modulator that reaches the desired target with good safety and
tolerability, and modulates neuronal activity in humans. These data
suggest basmisanil as a promising candidate drug for further clinical
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
testing in conditions which may benefit from a reduction in excessive GABA-mediated tonic inhibition, such as cognitive impairment
and stroke recovery.
Competing interests
All authors are or were employers of F. Hoffmann-La Roche Ltd.
A21
EEG cross-frequency coupling associated with attentional
performance: an RDoC approach to attention
Berrie Gerrits1,2, Madelon A Vollebregt1,2, Sebastian Olbrich4, Roy PC
Kessels2, Donna Palmer5, Evian Gordon5, Martijn Arns1,3
1
Research Institute Brainclinics, Nijmegen, The Netherlands; 2Radboud
University Medical Centre, Donders Institute for Brain, Cognition and
Behaviour, Department of Cognitive Neuroscience, Nijmegen, The
Netherlands; 3Dept. of Experimental Psychology, Utrecht University,
Utrecht, The Netherlands; 4Dept. of Psychiatry, Psychotherapy and
Psychosomatic, University Zürich, Zürich, Switzerland; 5Brain Resource
Ltd., Sydney, NSW, Australia
Correspondence: Berrie Gerrits (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A21
The quality of attentional performance plays a crucial role in goaldirected behavior in daily life activities, cognitive task performance,
and in multiple psychiatric illnesses. The Research Domain Criteria
(RDoC) approach put forward by the National Institute of Mental
Health aims to investigate cognitive constructs while abandoning the
conventional diagnostic system of psychiatric illnesses. The current
study used an RDoC approach to investigate functions underlying attentional performance.
One of the previously postulated physiologic mechanisms that could
explain variance in attentional performance is the quality of interplay
between neuronal networks1,2. Various attempts to visualize this
interplay have been made using different approaches. In our current
study, we aimed to validate the approach of functional Independent
Component Analysis (fICA) based on electroencephalograms (EEG’s)
for this purpose. This method yields components that reflect EEG
cross-frequency coupling patterns between networks (details about
the method can be found elsewhere3).
We first applied fICA to combined Eyes Open resting state EEG and EEG
during an n-back task data in a large sample of healthy adults (n = 1397),
yielding 32 components. Secondly, we obtained individual component
loadings for every subject for the two conditions as well as a difference
loading score (Loadingtask-LoadingEO) per network. Thirdly, we operationalized attentional performance by differentiating between attenders (n =
704) versus non-attenders, (n = 320) on the n-back task and found a
significant difference between groups for the difference loading score for
component 10. We proposed that component 10 reflects the anticorrelated interaction of an attention network and a resting state network.
This finding was cross-validated in an adolescent Attention-Deficit/Hyperactivity Disorder (ADHD) population (n = 80), clinically suffering from attentional problems. As expected, the difference loading scores in this group
was similar to the pattern observed in non-attenders. Furthermore, it was
accompanied by a lower overall loading on component 10 in both
conditions.
The current findings seem to validate fICA as a method to visualize
neuronal networks and their interactions. Combining this method
with objective behavioral measures may contribute to the understanding of brain mechanisms involved in attention and attentional
problems such as observed in multiple psychiatric illnesses.
References
1. Leech, R., Kamourieh, S., Beckmann, C. F., & Sharp, D. J. (2011). Fractionating
the default mode network: Distinct contributions of the ventral and dorsal
posterior cingulate cortex to cognitive control. The Journal of Neuroscience:
The Official Journal of the Society for Neuroscience, 31(9), 3217–24. doi:
10.1523/JNEUROSCI.5626-10.2011
2. Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The
neural bases of momentary lapses in attention. Nature Neuroscience, 9(7),
971–8. doi: 10.1038/nn1727
Page 8 of 34
3. Aoki, Y., Ishii, R., Pascual-Marqui, R. D., Canuet, L., Ikeda, S., Hata, M., Takeda, M.
(2015). Detection of eeg-resting state independent networks by eloreta-ica
method. Frontiers in Human Neuroscience, 9. doi: 10.3389/fnhum.2015.00031
A22
Attention for inhibition in ADHD: new insights with ERP source
imaging
Tieme WP Janssen1, Dirk J Heslenfeld1, Rosa van Mourik1, Katleen
Geladé2, Athanasios Maras2, Jaap Oosterlaan1
1
Clinical Neuropsychology, VU University, Amsterdam, Noord-Holland,
1081 BT, Netherlands; 2Yulius Academy, Barendrecht, Zuid-Holland, 2994
GC, Netherlands
Correspondence: Tieme WP Janssen (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A22
Background
Deficits in response inhibition figure prominently in models of ADHD
and have been documented in cognitive [1], ERP [2] and fMRI studies
[3]. Parallel to these developments, some authors have criticized the inhibition model of ADHD and associated methodology, suggesting that
attentional factors confound former results [4]. In a previous fMRI study
[5] we aimed to control for attentional confounds during a stop-signal
task (SST). Despite this modified SST, we found evidence for reduced
activation in key-areas of the inhibition network, such as the right inferior frontal gyrus (rIFG), supplementary motor area (SMA) and anterior
cingulate cortex (ACC). However, according to Barkley [6], inhibition
problems precede other cognitive dysfunctions, such as attentional deficits. In order to investigate this hypothesis at the brain level, both high
spatial and temporal resolution are needed, which have not yet been
fully integrated in one imaging technique. In the current study [7], we
addressed this issue by localizing ERP components associated with
response inhibition in children with ADHD.
Methods
Dense array ERPs (128 electrodes) were obtained for 46 children with
ADHD and 51 controls during the SST. Early and late components were
compared between groups. N2 and P3 components were localized with
LAURA distributed linear inverse solution for each participant, and
statistically compared between groups (Bonferroni-corrected based on
the number of electrodes, with p = .05/128 = .0004).
Results
A success-related N1 modulation was only apparent in the ADHD
group. N2 and P3 amplitudes were reduced in ADHD. During the successful inhibition N2, the ADHD group showed reduced activation in
rIFG, SMA, and right temporoparietal junction (rTPJ), and during
failed inhibition in the rIFG. During the successful inhibition P3, reduced activation was found in ACC and SMA.
Conclusions
Source localization of N2 revealed not only a typical inhibition network (rIFG and SMA) that was affected, but also a major hub of the
ventral attention system, the rTPJ. The ventral attention system supports attentional reorienting to salient and behaviourally relevant external stimuli. The fact that this ventral attention network is
implicated in the same 50 ms time window (240-290 ms after stop
stimulus) as the inhibition network creates a challenge to Barkley’s
theory of ADHD.
Competing interests
The author(s) declare no potential conflicts of interest
References
1. Oosterlaan, J., Logan, G. D. & Sergeant, J. A. Response inhibition in AD/
HD, CD, comorbid AD/HD + CD, anxious, and control children: a metaanalysis of studies with the stop task. J. Child Psychol. Psychiatry. 1998;
39: 411–425.
2. Johnstone, S., Barry, R. & Clarke, A. R. Behavioural and ERP indices
of response inhibition during a Stop-signal task in children with two
subtypes of Attention-Deficit Hyperactivity Disorder. Int. J. Psychophysiol.
2007; 66: 37–47.
3. Hart, H., Radua, J., Nakao, T., Mataix-Cols, D. & Rubia, K. Meta-analysis of
Functional Magnetic Resonance Imaging Studies of Inhibition and
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
4.
5.
6.
7.
Attention in Attention-deficit/Hyperactivity Disorder. JAMA Psychiatry.
2013; 70: 185–198
Alderson, R., Rapport, M. D. & Kofler, M. J. Attention-deficit/hyperactivity
disorder and behavioral inhibition: a meta-analytic review of the stopsignal paradigm. J. Abnorm. Child Psychol. 2007; 35: 745–58.
Janssen, T. W. P., Heslenfeld, D. J., Mourik, R. van, Logan, G. D. &
Oosterlaan, J. Neural correlates of response inhibition in children with
attention-deficit/hyperactivity disorder: A controlled version of the stopsignal task. Psychiatry Res. Neuroimaging. 2015; 233: 278–284.
Barkley, R. A. Behavioral inhibition, sustained attention, and executive functions:
Constructing a unifying theory of ADHD. Psychol. Bull. 1997; 121: 65–94.
Janssen, T. W. P. et al. Alterations in the Ventral Attention Network During
the Stop-Signal Task in Children With ADHD: An Event-Related Potential
Source Imaging Study. J. Atten. Disord. 2015; Epub ahead of print
A23
Neurofeedback and pharmacological treatments in ADHD - evidence
and EEG-markers
Daniel Brandeis1,2
1
Department of Child and Adolescent Psychiatry and Psychotherapy,
Central Institute of Mental Health, Medical Faculty Mannheim/
Heidelberg University, J5, 68159 Mannheim, Germany; 2Department of
Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital,
University of Zürich, Neumünsterallee 9, 8032 Zürich, Switzerland
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A23
Scientific background/Introduction
Neurofeedback is a promising treatment for ADHD despite recent
evidence cautioning that probably blinded ratings draw a less positive picture.
Theoretical framework/Hypothesis/Purpose of the work
The current presentation will focus on how recent metaanalytic evidence for neurofeedback in ADHD, address specifically studies on
the add-on use and interactions with pharmacological treatment,
and on the predictive EEG-based markers for neurofeedback.
Used Methods and Materials
Review of evidence from recent metaanalysis during the last 8 years [1–3]
and selected individual papers on the relation to pharmacological treatment, EEG markers [4, 5] and mechanism of learning self-regulation.
Findings
The clinically relevant efficacy of neurofeedback is reduced in probably blinded ratings and compared to active or sham control conditions. This may reflect considerable unspecific effects, compromised
neurofeedback quality, or lack of learning self-regulation. How neurofeedback depends on previous or concurrent pharmacological treatment is unclear. Some head to head studies report comparable or
additive effects of neurofeedback and medication, but not that neurofeedback works best as an add-on or second stage treatment (beyond practical considerations). Several predictive EEG markers have
been proposed but await replication.
Discussion of Relevance and Implications for future Research
The findings do not yet allow for clear recommendations as to which patients profit most from neurofeedback alone or in combination pharmacological intervention. Studies on stepped care approaches and personalized
approaches – what works for whom – are urgently needed.
References
1. Arns, M., et al., Efficacy of neurofeedback treatment in ADHD: the effects
on inattention, impulsivity and hyperactivity: a meta-analysis. Clinical EEG
and Neuroscience, 2009. 40(3): p. 180–189.
2. Cortese, S., et al., Neurofeedback for attention-deficit/hyperactivity disorder: meta-analysis of clinical and neuropsychological outcomes from
randomized controlled trials. Journal of the American Academy of Child
& Adolescent Psychiatry, 2016. 55(6): p. 444–55.
3. Sonuga-Barke, E.J.S., et al., Nonpharmacological interventions for ADHD: Systematic review and meta-analyses of randomized controlled trials of dietary and psychological treatments. American Journal of Psychiatry, 2013. 170(3): p. 275–89.
4. Wangler, S., et al., Neurofeedback in children with ADHD: Specific eventrelated potential findings of a randomized controlled trial. Clinical Neurophysiology, 2011. 122(5): p. 942–50.
Page 9 of 34
5. Arns, M., W. Drinkenburg, and J. Leon Kenemans, The Effects of QEEGInformed Neurofeedback in ADHD: An Open-Label Pilot Study. Applied
Psychophysiology and Biofeedback, 2012. 7(3): p. 171–80.
A24
Deviant alpha oscillations as measure to help understanding the
underlying mechanism of ADHD and predict treatment outcome
Madelon A Vollebregt1,2, Martijn Arns1,3
1
Research Institute Brainclinics, Nijmegen, The Netherlands; 2Department
of Cognitive Neuroscience, Donders Institute for Brain, Cognition and
Behaviour, Radboud University Medical Centre, Nijmegen, The
Netherlands; 4Dept. of Experimental Psychology, Utrecht University,
Utrecht, The Netherlands
Correspondence: Madelon A Vollebregt (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A24
Background
Attention-deficit hyperactivity disorder (ADHD) is characterized by an
inappropriate pattern of inattentiveness. Increasing evidence demonstrates that the modulation of alpha oscillations plays an important
role in the allocation of attention. A failure to modulate alpha activity
might therefore reflect ADHD. The first study presented here aimed
to investigate alpha modulation in children with ADHD during attentional performance. The second study aimed to replicate and extend
previous findings with respect to electroencephalographic (EEG) biomarkers that have shown promise in predicting treatment outcome
to stimulant medication in ADHD.
Methods
For the first study [1], posterior alpha activity (8–12 Hz) was measured
in 30 healthy children and 30 children with ADHD aged 7–10 years,
using EEG while they performed a visuospatial covert attention task.
We focused the analyses on healthy boys (N = 9) and boys with ADHD
(N = 17). For the second study [2], data from the international Study to
Predict Optimized Treatment Response in ADHD (iSPOT-A), 336 children
and adolescents with ADHD were included and prescribed methylphenidate, and 158 healthy children were included. Treatment response was established after six weeks using the clinician rated ADHDRating Scale-IV (ADHD-RS-IV). Responders to treatment were defined as
>25 % improvement. The EEG Theta/Beta ratio (TBR) and alpha peak
frequency (APF) were investigated as predictors for treatment outcome.
Results
In the first study, alpha activity in typically developing boys was similar to
previous results of healthy adults: it decreased in the hemisphere contralateral to the attended hemifield, whereas it relatively increased in the
other hemisphere. However, in boys with ADHD this hemispheric
lateralization in the alpha band was not obvious (group contrast, p = .018).
In the second study, male-adolescent non-responders exhibited a low
frontal APF (ES = 0.83), whereas no differences in TBR were found between
responders and non-responders. 62 % of the ADHD group was classified
as a responder. Responders were more often males (63 % versus
51 %, p = .031), but did not differ from non-responders in age,
medication dosage, and baseline severity of ADHD.
Conclusions
The first study demonstrated that the ability to modulate alpha oscillations
in visual regions with the allocation of spatial attention was clearly present
in healthy boys, but not in boys with ADHD. The second study demonstrated that male adolescent non-responders to methylphenidate display
a lower frequency at which frontal alpha oscillations is peaking. The typical
maturational changes in EEG emerging in adolescents observed in ADHD
responders and controls, are absent in non-responders.
Trial registration
Clinical trial registration information; www.clinicaltrials.gov; NCT01932398
& NCT00863499
Competing interests
MA reports research grants, options/shares from Brain Resource Ltd. (Sydney,
Australia) and neuroCare group and he is also a co-inventor on 4 patent
applications (A61B5/0402; US2007/0299323, A1; WO2010/139361 A1) related to EEG,
neuromodulation and psychophysiology, but does not own these nor receives any
proceeds related to these patents.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
References
1. Vollebregt, M.A., Zumer, J.M., ter Huurne, N., Buitelaar, J.K., Jensen, O.
(2016). Posterior alpha oscillations reflect attentional problems in boys
with Attention Deficit Hyperactivity Disorder. Clinical Neurophysiology,
127(5), 2182–2191.
2. Arns, M., Vollebregt, M.A., Palmer, D., Spooner, C., Gordon, E., Kohn, M.,
Clarke, S., Elliot, G., Buitelaar, J.K. (in prep). ADHD non-response to methylphenidate associated with slow alpha peak-frequency in male adolescents: Results from the iSPOT-A study.
A25
Brain arousal regulation: a predictive biomarker in psychiatry
Christian Sander, Ulrich Hegerl
Department of Psychiatrie, University Hospital Leipzig, Leipzig, Saxonia, 04103,
Germany
Correspondence: Christian Sander (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A25
Arousal fundamentally impacts normal and abnormal behavior,
and recently research on disturbed arousal regulation in mental
disorders has attracted increasing interest. Accordingly, arousal
has been implemented as a basic dimension of mental disorders
in the Research Domain Criteria (RDoC) project of the National Institute of Mental Health (NIMH). The talk introduces the arousal
regulation model of affective disorders and ADHD, which suggests hyper-arousal as a core pathogenetic factor in uni- and bipolar depression, and, in contrast, hypo-arousal in mania and
ADHD. The model explains different clinical phenomena, as manic
behavior is in parts interpreted as an autoregulatory attempt to
stabilize brain arousal by creating a stimulating environment,
whereas the withdrawal and sensation avoidance as well as insomnia symptoms in depression is seen as reflecting the underlying chronic hyperarousal. Many depressed patients experience
themselves as subjectively fatigued and in need of rest, extended
bed-times and inactivity in most cases do not result in the desired recovery but in the contrary depressive symptoms and
sleep problems tend to increase. As inferable from the model, interventions that decrease arousal (e.g. antidepressants) or increase sleep need (e.g. sleep deprivation, sleep restriction) are
efficient, whereas the inefficacy of stimulants has often been
shown in depression. The arousal model contributes to delineating more homogenous subgroups within affective disorders and
predicts response to treatment based on the respective brain
arousal disturbance. Electroencephalography under resting conditions is most suitable for the assessment of brain arousal regulation, as different arousal states (also called EEG-vigilance stages)
can be differentiated during the transition from high alertness to
drowsiness until sleep onset according to specific EEG characteristics. The second part of the talk will introduce a computeralgorithm (Vigilance Algorithm Leipzig, VIGALL2.1), allowing semiautomatic classification of EEG-vigilance stages during restingEEG recordings. The time sequence of these EEG-vigilance stages
indicates the individual arousal regulation of the recorded subject. The final part of the talk will outline results from current
studies applying VIGALL 2.1 and investigating hypotheses derived
from the arousal regulation model with regards to the usage of
brain arousal regulation as a diagnostic and/or predictive biomarker in psychiatric research.
Competing interests
The author(s) declare(s) that they have no competing interests.
A26
Panic attacks on the epilepsy spectrum
Nash N Boutros (
[email protected])
University of Missouri-Kansas City, Kansas City, Missouri, USA 64108
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A26
Page 10 of 34
Background
A rather highly unexamined dimension of psychiatric symptomatology
is duration particularly when ultra brief and episodic. Brief and episodic
symptoms are frequently seen in individuals committing seemly unmotivated repeated violent acts, dissociative episodes or panic attacks.
Growing evidence suggest that at least in a subset of patients exhibiting these symptoms focal fronto-limbic hyper-excitability may be contributing to the clinical picture. Such conditions can be conceptualized
to fall on the epilepsy spectrum. We now present preliminary data from
panic patients examining their focal coherence.
Methods
11 panic patients and 10 healthy control subjects were included. All
had at least two unprovoked panic attacks. All subjects underwent
10 min of eye open and 10 min of eyes closed magnetoencephalography recording (CTF, Canada). The data were analyzed based on 27
regions of interests in each hemisphere. Areas were divided to
fronto-limbic (FL) or extra fronto-limbic (EFL).
Findings
In the eyes-closed condition one pair had higher coherence in the control group (Occipital-Parietal). 31 pairs had higher coherence in PD (20
FL-FL, 11 FL-EFL, NONE EFL-EFL). In the eye open condition NO area
showed more coherence in controls while 59 did for panic. Of the 59
pairs 46 were FL-FL, 15 were FL-EFL and NONE were EFL-EFL.
Relevance and Implications for Future Research
If the above data are confirmed in future studies with larger sample
sizes, the implications would be that it may be possible to predict response to various types of medications (e.g., selective serotonin reuptake inhibitors (SSRIs) vs. anticonvulsants). These findings would
lead to more personalized treatment planning.
A27
Electrophysiological markers in the prediction of various treatment
approaches in major depression and obsessive compulsive
disorder
Sebastian Olbrich1, Alexandra Kirsten1, Anna-Lena Dohrmann2, Galina Surova2
1
Department for Psychiatry, Psychotherapy and Psychosomatic,
University of Zurich, Zurich, Switzerland; 2Department for Mental Health,
University Leipzig, Leipzig, Germany
Correspondence: Sebastian Olbrich (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A27
Despite large research efforts - also in electrophysiology - within the
last decades, up to now there are no clinically accepted or used biomarkers that help to diagnose affective or anxiety disorders: It seems
that the discriminative abilities of clinicians concerning diagnostic
decisions are fair enough. However, what is even more important
than a correct diagnosis is choosing the best treatment. Here, the decisions of the clinicians are not supported by any evidence. Especially
in disorders where with various treatment approaches - such as
major depressive disorder (MDD) and obsessive compulsive disorder
(OCD) – but a still very high percentage of non-responders to first
line therapies, biomarkers could contribute to an individualized
medicine with faster responses and less trial and error approaches.
Electrophysiological biomarkers provide a direct window to brain
function combined with cost-effective settings and broad availability.
Therefore, data on electroencephalogram (EEG) based algorithms derived from different studies will be presented that help to discriminate patients with better response to different types of treatment.
Within the first part, the focus will be on predictors for treatment
outcome following therapy with different types of antidepressants.
Further, EEG-based biomarkers with discriminative power concerning
outcome of electro-convulsive therapy (ECT) and will be shown. The
second part is dedicated to treatment of OCD with cognitivebehavioral therapy, selective-serotonin inhibitors (SSRIs) or a combination of both. EEG-based biomarkers will be presented that might
support the right choice of treatment.
The presentation of data will be followed by a brief outlook to what will
has to come to transfer research knowledge into every day routine.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Besides the need for large, prospective multicenter studies, new analytical approaches will be presented that could help to establish an individualized medicine in neuropsychiatric disorders one day.
Competing interests
Authors report no competing interests.
A28
The sgACC in depression: getting at the heart of it
TA Iseger1,2, JL Kenemans1, M Arns1,2,3
1
Dept. of Experimental Psychology, Utrecht University, Utrecht, The
Netherlands; 2Research Institute Brainclinics, Nijmegen, The Netherlands;
3
neuroCare Group, Munich, Germany
Correspondence: TA Iseger (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A28
Major depressive disorder (MDD) is a chronic, mental disease with a
remitting and relapsing course. Antidepressant medication is the
most common treatment for MDD, however, the precise working
mechanism underlying these treatments remains unclear. Recent
neuromodulation treatments demonstrate that direct stimulation of
the dorsolateral prefrontal cortex (DLPFC) and subgenual anterior
cingulate (sgACC) relate to clinical improvement, suggesting connectivity alterations in this network to mediate antidepressant response,
which might be similar for pharmacological treatments as well. This will
be the focus of part 1. The international Study to Predict Optimized
Treatment in Depression (iSPOT-D) is an international multicenter study
that collected EEG data for 1008 MDD patients. We investigated
whether connectivity in alpha and theta frequencies within this network changed during antidepressant treatment between: patients and
controls, and responders and non-responders. Women exhibited higher
alpha and theta connectivity compared to males, both pre- and posttreatment. Decreased alpha connectivity after treatment was found
only for male responders, while non-responders and females exhibited
no changes in alpha connectivity. Furthermore, it could be useful to a
priori stratify by gender for future MDD studies [1].
Part two focusses on functional connectivity assumptions between
the DLPFC, sgACC and the vagal nerve. Preliminary results will be
presented regarding a method to localize the DLPFC: neuro-cardiacguided rTMS (NCG-rTMS). The efficacy of rTMS in the treatment of
MDD has been well established in recent years, however with various
methods of locating the DLPFC. It has been proposed that the efficacy
of rTMS in MDD is more related to stimulating the area that is functionally connected to the sgACC rather then to specific cortical areas.
Therefore, we set-out to develop and test a new method that employs
the functional role of the sgACC to establish in real time if the correct
cortical area is targeted. Several studies have shown that the sgACC is
involved in parasympathetic regulation such as heart rate (HR) and respiration, and that neurostimulation of these areas led to HR decreases,
most likely through connectivity with the nervus vagus. Based on the
notion that rTMS aims to transsynaptically stimulate the sgACC, we
used electrocardiogram (ECG) R-peak triggered single pulse TMS to
various frontal locations to establish the correct DLPFC location.
References
[1] T.A. Iseger, M.S. Korgaonkar, J.L. Kenemans, S.M. Grieve, C. Baeken, P. Fitzgerald
& M. Arns. Alpha connectivity change between the Subgenual Anterior
Cingulate and Prefrontal Cortices related to antidepressant medication
response in males. Submitted, Aug 2016
A29
Heart rate variability and sleep EEG derived markers as correlates
of depression and treatment response
Marcel A Pawlowski1, Marek Adamczyk2, Thorsten Mikoteit2, Axel Steiger1
1
Max Planck Institute of Psychiatry, Munich, Germany; 2Psychiatric Clinics
of the University of Basel, Center for Affective, Stress and Sleep
Disorders, Basel, Switzerland
Correspondence: Marcel A Pawlowski (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A29
Page 11 of 34
Study objectives
The relevance of rapid eye movement (REM) sleep for affective disorders
derives from its well-established abnormalities in depressed patients, that
is increased REM sleep pressure with increased frequency of rapid eye
movements (REM density) as a trait marker of major depression. In this
study we examined whether prefrontal theta cordance and heart rate variability (HRV) during REM sleep could represent biomarkers of antidepressant treatment response to optimize treatment outcome.
Methods
In an open-label, case–control design, thirty-three in-patients (21 females) with a depressive episode were treated with various antidepressants for four weeks. Response to treatment was defined as a ≥
50 % reduction of HAM-D score at the end of the fourth week. SleepEEG was recorded after the first and the fourth week of medication.
Cordance was computed for prefrontal EEG channels in the theta frequency band during tonic REM sleep. HRV was derived from 3-min
artefact-free electrocardiogram segments during REM sleep.
Results
First, fourteen responders had significantly higher prefrontal theta cordance as compared to nineteen non-responders after the first week of
antidepressant medication. Second, HRV in REM sleep was decreased in
depressive patients at week four as compared to controls (high effect
size; Cohen´s d > 1). Third, HRV showed negative correlation with REM
density in healthy subjects and patients at week four.
Conclusions
Our data suggest that prefrontal REM sleep-deprived cordance may
predict response to antidepressant treatment in depressed patients,
whereas HRV distinguishes healthy subjects from depressed patients.
A30
Applying integrated EEG-behavioural analyses in genetic mouse
models for Autism Spectrum Disorder; the identification of
translational neuronal biomarkers
Martien J Kas1,2, Karlijn I van Aerde2
1
Groningen Institute for Evolutionary Life Sciences, University of
Groningen, Groningen, the Netherlands; 2Department of Translational
Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands
Correspondence: Martien J Kas (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A30
Autism Spectrum Disorder (ASD) is a highly heterogeneous neurodevelopment disorder that is clinically defined by impaired social interaction, as well as repetitive and restricted behaviours. More than 200
ASD risk genes have been identified. Understanding the functional
impact of these genetic variants will contribute to unravel clinical
heterogeneity and to improve treatment efficacy. To provide clinically relevant neuronal biomarkers for specific biological subgroups,
we initiated integrated EEG-behavioural analyses in selected genetic
mouse models for ASD. So far, EEG data from ASD patients have
shown changes in the power of brain oscillations in several frequency bands as well as in response to sensory stimuli. Although
these results tell us that ASD patients have alterations at the level of
brain circuits, and/or during processing of specific tasks, these biomarkers are currently not used for diagnosis of the disease.
To increase the selectively and sensitivity of neurophysiological biomarkers we analyzed the EEG of genetically modified mice during
specific aspects of a behavioral task. To this end we coupled the systems used for EEG recordings and the software that tracks the location of the animal, allowing us to select parts of EEG measurements
based on animal behaviour. We used Protocadherin 9 (Pcdh9) mutant
mice as a model for the social interaction deficits seen in ASD
patients (Bruining et al., 2015). These mice show deficits in sensorimotor development and long-term social discrimination capacity,
while long-term fear conditioning is normal. Preliminary EEG results
showed a decrease in gamma band oscillations in mutant mice during social interaction with both familiar and novel intruder mice. Furthermore, mutant mice showed impaired sensory information
processing during an auditory mismatch negativity task. Currently,
we are expanding these findings and investigate both EEG
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
measurements and behavioral outcomes in experimental paradigms
with varying degrees of difficulty for social discrimination. This way, we
hope to identify translational EEG biomarkers to guide ASD patient classification and to contribute to the development of novel treatment
strategies for this heterogeneous neurodevelopmental disorder.
A31
Anesthesia, an opportunity to measure a pharmaco-EEG par
excellence
Clementina M van Rijn1, Marijtje LA Jongsma2, Philip LC van den Broek1,
Jan van Egmond3
1
Donders Institute for Brain, Cognition and Behaviour, Radboud
University, Nijmegen, the Netherlands; 2Behavioural Science Institute,
Radboud University, Nijmegen, the Netherlands; 3Department of
Anesthesiology, Radboud University Hospital, Nijmegen, the Netherlands
Correspondence: Clementina M van Rijn (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A31
The IPEG is an association for researchers involved in electrophysiological brain research and pharmacology, and the contribution of
pharmaco-EEG research to the field of neuroscience is gaining in importance. In the past few years the functions of brain circuits, i.e.
functional neuroanatomical resting-state networks, have come to be
on the verge of being understood. This progress is the result of close
collaboration between many disciplines: neuroanatomy, psychology,
physics and pharmacology, to name just a few, which are making a
joint effort to understand the functioning of the brain.
In view of these developments, the EEG measured during anesthesia
might hold keys to disentangle (or to the contrary perhaps to unify),
behavioral, pharmacological and neurophysiological signatures of various states of behavior, especially of the difficult to quantify states of
consciousness. This is because anesthesia is a drug-induced state in
which patients do not have any sensation, they are unconscious.
Moreover, during the whole period of anesthesia, the anesthesiologist
meticulously monitors the state of wakefulness, so this procedure
complies perfectly with the IPEG recommendation, which advices to
measure EEG activity under vigilance-controlled conditions [4].
To induce a state of anesthesia, a variety of drugs can be used, all with
quite different molecular targets. One of the still unanswered questions
is: are different drugs inducing different states of anesthesia, or is
anesthesia a well-described state that might be induced by modifying
different stations in a hypothesized “esthesia circuit”? The contribution
of mathematicians to the field of time series analysis is yielding
advanced analysis algorithms with a huge potential to answer this
question, since it touches on brain circuits and connectivity.
In this oral I will mini-review the literature to point out characteristic
EEG and connectivity changes induced by various types of anesthetics, propofol, isoflurane and ketamine included [e.g.1,5]. I will illustrate the findings in the literature with our own data of both rats
and humans [2, 3]. Further research questions will be proposed and
discussed with the audience, in the hope to boost interest and research in our IPEG society in the EEG under anesthesia, the
pharmaco-EEG par excellence.
Competing interests
None.
References
1. Akeju O, Song AH, Hamilos AE, Pavone KJ, Flores FJ, Brown EN, Purdon
PL. Electroencephalogram signatures of ketamine anesthesia-induced unconsciousness. Clin Neurophysiol, 2016, 127, 2414–2422.
2. Broek PLC van den, van Rijn CM, Egmond J van, Coenen AML, Booij
LHDJ. An Effective Correlation Dimension and Burst Suppression Ratio of
the EEG in rat. Correlation with Sevoflurane Induced Anaesthetic Depth.
Eur J Anaesthesiology, 2006, 23, 391–402.
3. Broek, PLC van den, Monitoring Anesthetic Depth: Modification,
Evaluation and Application of the Correlation Dimension. Nijmegen 2003
(thesis : http://repository.ubn.ru.nl/handle/2066/19249).
Page 12 of 34
4. Drinkenburg WHIM, · Ruigt GSF,· Ahnaou A. Pharmaco-EEG Studies in Animals: An Overview of Contemporary Translational Applications. Neuropsychobiology, 2015, 72, 151–164.
5. Purdon PL, Sampson A, Pavone KJ, Brown EN. Clinical Electroencephalography
for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology,
2015, 123(4):937–960.
A32
Proof of early disintegration of functional network connectivity in
the K18 seeding transgenic mouse model of tauopathy spreading
from the locus coeruleus: novel opportunities for assessing
pharmacological intervention therapies for Alzheimer’s disease
A Ahnaou, C Walsh, L Raeymaekers, R Biermans, NV Manyakov, C
Wintmolders, A Bottelbergs, K Van Kolen, D Moechars, JA Kemp and WH
Drinkenburg
Department of Neuroscience Discovery, Janssen Research &
Development, a Division of Janssen Pharmaceutica NV. Turnhoutseweg
30, B-2340 Beerse, Belgium
Correspondence: A Ahnaou (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A32
Alzheimer’s disease (AD) is a disconnection syndrome manifested
by the disruption of white matter integrity, loss of synapses and
functional connectivity (FC) across different cortical and subcortical regions. Early in AD progression, tau pathology can be found
in the brainstem locus coeruleus (LC) prior to its amyloid-induced
exacerbation and clinical symptoms. Accordingly, the pathological
process of AD is characterized by the cell-cell spread of tau pathology from the LC into the medial temporal lobe, which triggers
pathological changes causing functional disconnectivity. Network
dynamics have become a leading model to assess both the anatomical relationships (structural networks) and the coupling of dynamic neurophysiology (functional networks) linking separate
brain regions.
The present study used a tau seeding model in which preformed
synthetic tau fibrils (K18) were unilaterally injected into the LC of
transgenic mice expressing mutant human P301L tau, equipped with
multichannel electrodes in frontal cortical and CA1-CA3 hippocampal
areas. This approach allows us to 1/quantify longitudinal coherence
and FC using phase-amplitude theta-gamma coupling (PAC); 2/identify the directionality of connectivity, using lagged and extended
partial direct coherence (PDC); 3/measure pre-attentive auditory P50
potentials; 4/investigate sleep-wake organization; and 5/quantify
phospho(p)-tau pathology in regions of interest using immunohistochemistry (AT100 antibody).
At the functional level, a decrease in spectral power at a range of
frequencies in the hippocampal regions ipsilateral to the injection
site is found at 2 weeks post-K18 injection, while an increase in
power in contralateral hippocampal regions is hypothesized to be
indicative of early compensatory mechanisms. Inter-hippocampal
coherence is reduced in slow frequency oscillations and FC is significantly impaired as evidenced by: decreased intra- and interhemispheric hippocampal directionality of theta frequency oscillations; and reduced intra- and inter-hemispheric functional PAC
strength. At the structural level, abnormal pTau aggregation is
regionally specific, with AT100-positive tau detected in the pons,
medulla, thalamus and cerebellum.
Ongoing assessment of pre-attentive auditory information processing, sleep-wake alterations and changes in the activity of GABAergic
interneurons, which play a critical role in theta-gamma interactions,
will allow further investigation into this aforementioned network dysfunction. Electrophysiological abnormalities in the hippocampus and
cortex following injection of K18 into the LC convincingly support
the relevance of tau pathology early in the LC. These functional alterations offer a reliable in vivo assay to test AD therapeutic agents for
early intervention of tau pathology and possible prevention of the
impairments in synaptic plasticity and neuronal network connectivity
as seen in AD.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
A33
Public-private initiative to align EEG biomarkers of Alzheimer’s
disease in human and mouse models for early stages of drug
discovery: the achievements of IMI PharmaCog project
Claudio Babiloni1,2, Claudio Del Percio2,3, Nicola Marzano2, Susanna Cordone2,
Susanna Lopez2, Giuseppe Noce6, Cristina Bagnoli4, Paolo Maria Rossini5,
Andrea Soricelli6, Flavio Mariano Nobili7, David Bartres Faz8, Olivier Blin9, Pierre
Payoux10, Regis Bordet 11, Bernhard Mueller 12, Magda Tsolaki 13, Lucilla
Parnetti 14, Ulrich Hegerl15, Tilman Hensch15, Juergen Dukart16 Alessandro
Bertolino16, Gianluigi Forloni17, Angelisa Frasca17, Jill Richardson18, Jesper Frank
Bastlund19, Bettina Clausen19, Marina Bentivoglio20, Paolo Francesco Fabene20,
Giuseppe Bertini20, Jonathan Kelley21, Wilhelmus Drinkenburg21, Giovanni
Frisoni4; on behalf of PharmaCog Consortium
1
Sapienza University of Rome, Rome, Italy; 2University of Foggia, Foggia, Italy;
3
IRCSS San Raffaele Pisana, Rome, Italy; 4IRCCS Istituto Centro San Giovanni di
Dio-Fatebenefratelli, Brescia, Italy; 5Catholic University, Rome, Italy; 6IRCCS SDN,
Naples, Italy; 7University of Genoa, Genoa, Italy; 8University of Barcelona,
Barcelona, Spain; 9Mediterranean Institute of Cognitive Neurosciences,
Marseille, France; 10University of Toulouse, Toulouse, France; 11Lille 2 University,
Lille, France; 12University of Duisburg-Essen, Essen, Germany; 13University of
Thessaloniki, Thessaloniki, Greece; 14University of Perugia, Perugia, Italy;
15
University of Leipzig, Leipzig, Germany; 16Roche, Basel, Switzerland; 17Mario
Negri Institute, Milan, Italy; 18GSK R&D, London, UK; 19Lundbeck, Valby,
Denmark; 20University of Verona, Verona, Italy; 21Janssen Pharmaceutica,
Beerse, Belgium
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A33
Background and aim
In the European FP7 IMI “PharmaCog” project (Grant Agreement n°
115009, www.pharmacog.org), we evaluated whether cortical electroencephalographic (EEG) rhythms in quiet wakefulness reflected prodromal
Alzheimer’s disease (AD) in amnesic mild cognitive impairment (aMCI) and
had a back-translational value in transgenic mouse models of Alzheimer’s
disease (AD).
Methods
The research data (including human biological samples) were
sourced ethically and used in line with international ethical
standards. EEG rhythms were recorded in 127 aMCI subjects. Cortical
sources of EEG rhythms were estimated by eLORETA package (http://
www.uzh.ch/keyinst/loreta.htm). Back translation of the EEG markers
was tested on on- going EEG rhythms in wild type and transgenic
mouse models of AD developing an accumulation of Aβ1-42 in the
brain (i.e. one mutation in PDAPP and two mutations in TASTPM).
Results
(1) Compared with the aMCI sub-group showing “negativity” to Aβ142/phospho tau in the cerebrospinal fluid, the aMCI sub-group
showing “positivity” (prodromal AD) exhibited an abnormal delta
(<4Hz) source activity in widespread cortical regions while a posterior
source activity in low-frequency alpha rhythms (8–10.5 Hz) pointed
to a progressive abnormality across disease progression in 2 years; (2) Ongoing EEG rhythms in the same frequency range were abnormal in the
transgenic PDAPP and TASTPM mice when compared to the control wildtype animals. Furthermore, these EEG rhythms were modulated by an
Aβ1 − 42 lowering agent (monoclonal antibody 3D6) administered for
4 weeks in TASTPM mice. No effect was observed in wild-type mice.
Conclusions
The results of the PharmaCog project suggest that markers of on-going
cortical EEG rhythms < 12 Hz may reflect prodromal AD processes in aMCI
subjects and can be back-translated to transgenic mouse models of AD.
These results encouraged the use of EEG biomarkers for an early
evaluation of new AD modifying drugs in transgenic mouse models of AD.
A34
Neurophysiological biomarkers in first episode psychosis
Dean F Salisbury, Brian A Coffman, Timothy Murphy, Sarah M Haigh
Department of Psychiatry,Dean F Salisbury University of Pittsburgh
School of Medicine, Pittsburgh, PA, 15213, USA
Correspondence: Dean F Salisbury (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A34
Page 13 of 34
A biomarker is an objective biological measure that can be used
for health risk prediction, or for screening, diagnosis, or tracking
disease progression. In psychosis research, a key recent development has been the application of a staging framework. The understanding that there is a progressive course to psychosis,
including a potential prodromal phase of increasing disability before the emergence of frank psychosis, has spurred the search
for screening biomarkers to indicate those truly prodromal clinical
high risk for psychosis individuals that will convert to psychosis
(approximately 30 % in 3 years), crucial for early prophylactic
treatment. Practically, true prodromal cases are rare and studies
tracking conversion long and costly. To be useful for screening
any disease presence biomarker must obligatorily be reduced at
first psychosis. Our group has been testing various auditory-based
neurophysiological tasks in first episode psychosis individuals to
develop screening biomarkers for an incipient psychotic break.
Here we describe several candidate biomarkers. Passive listening,
simple mismatch negativity (MMN) to a rare deviant tone is not
abnormal in first episode psychosis (Study 1: 29 first episode
schizophrenia and 40 controls; Study 2: 35 first episode schizophrenia and 35 controls). Complex MMN tasks that depend on
extraction of patterns in auditory sequences show more promise.
In a series of passive tasks where the number of tones in groups
were occasionally changed, we saw significant reductions of complex MMN to a rare extra tone (19 first episode schizophrenia
and 19 controls). We also observed abnormalities of a slow potential that appeared to indicate the formation of each group as
an acoustic object. Having participants actively count stimuli in
each group revealed that a missing tone (e.g. a group of 3 instead of a group of 4) elicited an emitted P300, and that the
posterior P300b component was abnormal in first episode schizophrenia (20 first episode schizophrenia and 32 controls). Using a
single tone auditory evoked potential task, attention to stimuli
was manipulated by having participants either press a button to
every 7 tones or watch a silent video (10 first episode schizophrenia and 10 matched controls). Healthy participants modulated their N100 with attention, but first episode psychosis
individuals did not. These data suggest that several neurophysiological measures may be suitable as biomarkers for the presence
of psychosis. Future work will deploy these tasks in clinical high
risk individuals to track whether they show promise as screening
biomarkers for an incipient psychotic break.
A35
Perception of sleep in patients with insomnia related to
generalized anxiety disorder, patients with apnea and in healthy
controls
Peter Anderer1,2, Georg Gruber1, Silvia Parapatics1, Gerda M Saletu-Zyhlarz2,
Bernd Saletu2, Georg Dorffner1,3
1
The Siesta Group Schlafanalyse GmbH, Vienna, Austria; 2Department of
Psychiatry and Psychotherapy, Medical University of Vienna, Vienna,
Austria; 3Center for Medical Statistics, Informatics and Intelligent Systems,
Medical University of Vienna, Vienna, Austria
Correspondence: Peter Anderer (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A35
Background
Although sleep research has been trying to elucidate the relations
between objective and subjective sleep and awakening quality for
five decades, findings have often been controversial. This might be
due to the lack of large data sets, to the differences between different sleep disorders and to the inter-individual differences in sleep
perception per se.
Objectives
The aim of the present study was to investigate relations between
objective and subjective sleep variables in a large number of healthy
subjects as well as in 2 clinically relevant patient groups, i.e. nonorganic insomnia in generalized anxiety disorder (insomnia/GAD) and
sleep apnea.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Material and methods
One hundred and seventy-seven healthy subjects (94 females, 83
males, aged 20 – 95 years), 61 insomniac GAD patients (32 females,
29 males, aged 21 – 66 years) and 51 apnea patients (7 females, 44
males, aged 29 – 73 years) underwent two polysomnographic nights
analyzed by the Somnolyzer [1] and completed the self-rating scale
for sleep and awakening quality [2].
Results
Patients with insomnia/GAD underestimated their sleep efficiency in
both nights (objective sleep efficiency index (SEI) 77 % and 84 % versus subjective SEI 57 % and 64 % for adaptation and baseline night,
respectively, p < 0.001 Wilcoxon test). Apnea patients showed no differences between subjective and objective SEI (objective 80 % and
87 % versus subjective 79 % and 86 %). Healthy controls – specifically males and subjects older than 60 years – overestimated their
sleep efficiency in the adaptation night (objective 80 % and 86 %
versus subjective 84 % and 87 %, p < 0.001 for night 1). Correlation
analysis between objective and subjective SEI on change values from
adaptation to baseline night revealed highly significant correlations
for all three groups (r = .77 for GAD, r = .57 for apnea and r = 51 in
healthy controls). Interestingly, the regression lines go through the
origin in all three groups, i.e. no change in objective SEI is perceived
as no change in subjective SEI.
Conclusions
Relations between subjective and objective sleep efficiency are influenced by age, gender and the type of sleep disorder. In correlation
analyses, the problem of inter-individual judgements of sleep perception can be reduced by using change values between adaptation
and baseline nights rather than raw values. The variety of correlations requires a parallel evaluation of subjective and objective variables as they are not interchangeable.
Competing interests
Peter Anderer, Georg Gruber, Silvia Parapatics and Georg Dorffner are
employees of The Siesta Group Schlafanalyse GmbH. Gerda M Saletu-Zyhlarz
and Bernd Saletu have no competing interests.
References
1. Anderer P, et al. An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x
7 utilizing the Siesta database. Neuropsychobiology. 2005; 51:115–133.
2. Saletu B, et al. (1997): Nonorganic insomnia in generalized anxiety
disorder. 2. Comparative studies on sleep, awakening, daytime vigilance
and anxiety under lorazepam plus diphenhydramine (SomniumR) versus
lorazepam alone, utilizing clinical, polysomnographic and EEG mapping
methods. Neuropsychobiology, 1997; 36:130–152.
A36
Catecholaminergic regulation of learning rate in a dynamic
environment
Marieke Jepma, Sander Nieuwenhuis
Cognitive Psychology Unit, Leiden University, Leiden, the Netherlands
Correspondence: Marieke Jepma (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A36
Adaptive behavior in a changing world requires flexibly adapting
one’s rate of learning to the rate of environmental change. Recent
studies have examined the computational mechanisms by which
various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the ‘learning rate’). However, the brain
mechanisms, and in particular the neuromodulators, involved in this
process are still largely unknown. The brain-wide neurophysiological
effects of the catecholamines norepinephrine and dopamine on
stimulus-evoked cortical responses suggest that the catecholamine
systems are well positioned to regulate learning about environmental
change, but more direct evidence for a role of this system is scant.
Here, we report evidence from a study employing pharmacology,
scalp electrophysiology and computational modeling (N = 32) that
suggests an important role for catecholamines in learning-rate regulation. We found that the P3 component of the EEG-an
Page 14 of 34
electrophysiological index of outcome-evoked phasic catecholamine
release in the cortex-predicted learning rate, and formally mediated
the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variablescapturing the unexpectedness of an outcome and the uncertainty of
a preexisting belief-on learning rate. Furthermore, a pharmacological
manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants’ baseline learning rate. Our findings provide converging
evidence for a causal role of the human catecholamine systems in
learning-rate regulation as a function of environmental change.
A37
Dopamine and the cortical representation of reward
Iris Schutte, Ivo Heitland, J Leon Kenemans
Department of Experimental Psychology, Helmholtz Institute, Utrecht
University, Utrecht The Netherlands
Correspondence: Iris Schutte (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A37
The way humans behave is greatly affected by the principle expected
utility, the combination of subjective value (SV) of the outcome of an
act (is it rewarding?) and subjective probability (SP) of that outcome.
In an initial study (n = 42) we examined the electro-cortical representations of the anticipation of SV and SP during a cued Go/NoGo experiment. During this task cue letters signaled upcoming target
letters to which participants had to respond. The probability of target letter appearance after the cue letter and the amount of money
that could be won for correct and fast responses were orthogonally
manipulated across four task blocks. Results show that reward availability affected a prefrontal reward P200 and a centro-parietal P300
ERP. Moreover, a fronto-central ERP was affected by both reward
and probability manipulations. These results suggest that reward
and probability are partially separately processed in the cortex. Furthermore, reward and probability information are integrated around
300 ms after presentation of the cue and possibly processed via a
shared underlying cortical mechanism that may act to reduce uncertainty or to prepare for action. In a follow-up study we investigated
the role of dopamine (and noradrenaline) in either of these processes by employing a within-subjects haloperidol/clonidine/
placebo cross-over design (n = 24) with the same cued Go/NoGo
paradigm.
Trial registration
The Netherlands National Trial Register (NTR) (CC = 4493).
A38
Optimizing the earliest memory stages: a role for acetylcholine
and serotonin?
Anke Sambeth (
[email protected])
Neuropsychology and Psychopharmacology, Maastricht University,
Maastricht, the Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A38
Acetylcholine and serotonin both play an important role in encoding
and consolidation of memories. However, it has also been suggested
that these two neuromodulators take part, and might even interact,
in processes initiated before conscious encoding even takes place.
Sensory memory and novelty detection, two processes related to reduction of surprise, are part of those early stages. They can be measured with the mismatch negativity (MMN) and P3a components of
the event-related potential, respectively. In a series of experiments,
we examined whether cholinergic and serotonergic manipulations
affect MMN and P3a components during a novelty oddball task. In
this task, frequent standard stimuli were interspersed with infrequent
deviant and infrequent novel stimuli at a pace of one stimulus presentation per second. Biperiden, a cholinergic agonist, and rivastigmine, a cholinesterase inhibitor, did not affect MMN amplitude.
Acute tryptophan depletion, a method to reduce serotonin in the
brain, and citalopram, a selective serotonin re-uptake inhibitor, were
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
also unable to affect the MMN. No significant interactions between treatments were found related to the MMN. Cholinergic
treatments did, however, affect the P3a amplitude: P3a was decreased after Biperiden intake and increased after Rivastigmine.
The serotonergic manipulations did not affect P3a amplitude, neither were interactions found between treatments. Our results
thus show that, although the cholinergic and serotonergic systems do not seem to play a role in sensory memory, acetylcholine’s role in novelty detection, and thus in handling surprise, is
evident.
A39
Processing of the mismatch negativity under the LSD state
Christopher Timmermann1, 2, Mendel Kaelen1, Eduardo Schenberg1,
Amanda Feilding3, Robert Leech2, David Nutt1, Robin Carhart-Harris1,
Suresh Muthukumaraswamy4
1
Centre for Neuropsychopharmacology, Department of Medicine,
Imperial College London, London, UK; 2Computational, Cognitive and
Clinical Neuroscience Laboratory, Department of Medicine, Imperial
College London, London, UK; 3The Beckley Foundation, Oxford, UK;
4
CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A39
Background
Lysergic acid diethylamide (LSD) is a classic psychedelic drug and
serotonin 2A receptor agonist. A common feature of the LSD state is
its capability to provide an experience of modulating the salience of
external events. The Mismatch Negativity (MMN) is an event-related
potential/field (ERP/ERF), that indexes expectation disruption (or
‘surprise’) mechanisms, which have been shown to be modulated in
patients with disorders of consciousness, as well as in schizophrenia
and following ketamine administration. In this study the MMN paradigm was used to assess expectation and surprise mechanisms under
LSD and placebo conditions in healthy participants.
Methods
A balanced order, within subject design was used for the study. 20
Healthy volunteers underwent MEG recordings following intravenous administration of LSD (75 mcg IV) and placebo at least 2 weeks
apart. Participants were presented with auditory stimuli consisting
of oddball and standard tones while resting inside the MEG scanner. Following preprocessing and averaging, the resulting eventrelated fields (ERF) were converted into scalp-map images and
smoothed for statistical analysis corresponding to four conditions:
auditory stimuli of standard tones under LSD (1) and placebo (2)
and deviant tones under LSD (3) and placebo (4). The ERFs were entered into a within-subject analysis of variance with 2 main factors:
‘drug’ (LSD and placebo) and ‘expectation disruption’ (standard and
deviant).
Results
An interaction effect between ‘expectation disruption’ and ‘drug’ factors was found in a right lateralized cluster in the scalp. Post hoc analyses within this ROI, reveal significant differences in the processing
of standard tones between placebo and LSD conditions as well as
deviant tones. Within the placebo condition the difference between
standards and deviants was significant, while it wasn’t following LSD
administration.
Conclusions
Results indicate a reduction of activity related to the processing of
novel stimuli, while showing that the surprise response was increased under the LSD condition in large areas of the scalp for familiar stimuli. These findings may inform how salience mechanisms may
be disrupted under LSD and is consistent with reports of “increased
novelty” to familiar stimuli in the LSD state. Mechanisms underlying
this modulation may be accounted by modulation of prediction error
in the psychedelic state.
This research received financial and intellectual support from the
Beckley Foundation and was conducted as part of a wider BeckleyImperial research programme.
Page 15 of 34
A40
The effects of psilocybin on human EEG, comparison with animal
models
Tomas Palenicek1,2, Filip Tyls1,2, Michaela Viktorinova1, Anna Bravermanova1,2,
Renata Androvicova1, Vaclava Sedlamyerova1, Vladimir Krajca1, Martin
Brunovsky1
1
National Institute of Mental Health, Klecany, Czech Republic; 2Third
Faculty of Medicine, Charles University, Prague, Czech Republic
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A40
Objectives
Psilocin, the active metabolite of psilocybin, is a classical psychedelic
tryptamine acting as an agonist at serotonin 5-HT2A/C and 5-HT1A
receptors. It has been used extensively to model psychosis in
humans as well as in animals, and during the last decade given more
attention as a potential antidepressant and anxiolytic drug. Recent
studies in healthy volunteers have shown that psilocybin leads to a
global desynchronization of brain activity and disconnection of the
main brain networks. The purpose of the current study is to compare
the translational validity of psilocybin/psilocin effects on EEG activity
and connectivity between healthy volunteers and rats.
Methods
For the human study, a 19 channel EEG of a standard 10/20 system
was recorded with BioSDA09 amplifier (M&I). Subjects (M10/F10) were
administered 0.26 mg/kg of psilocybin or placebo orally in a doubleblinded, crossover manner. EEG was recorded before and at 50, 90, 180
and 240 min after drug administration. In the animal study, psilocin
was administered to male Wistar rats (n = 10) subcutaneously in dose
of 4 mg/kg. Multichannel EEG with 12 cortical (6 homolateral pairs)
electrodes at frontal, parietal and temporal regions were recorded for
10 min before and 90 min after dosing using BrainScope EADS 221
amplifier (M&I). EEG in animals was co-recorded with behavioural activity and epochs of inactivity were then subjected for further processing.
Data was pre-processed using Brainvision and WaveFinder software
followed by further power spectral and coherence analyses using
Neuroguide software. Source localization of EEG activity was analysed
by LORETA, 3D brain mapping in animals was performed using an inhouse developed Matlab tool.
Results
Psilocybin induced an absolute as well as relative alpha power decrease
in occipital regions, while beta and gamma power increases in frontotemporal areas in humans. The effects were most robust 50 min after
drug administration. Source localization by LORETA confirmed the
localization of EEG changes. However, it is of note that the gamma
power cannot be distinguished from artificial motor activations. EEG coherence was mainly decreased in theta, alpha and beta bands, with
some increases observed in beta and gamma bands. In rats there was a
global power decrease in absolute power however relative power
showed partly similar profile to humans with theta power decrease and
beta and gamma power increase. Furthermore, there was a global decrease of coherence in rats following drug administration.
Conclusions
The effects of psilocin/psilocybin resulted in similar direction of EEG
changes in both humans and rats with disconnection (decreased coherence) being the most stable phenomenon observed, indicating
good translational validity.
This study was supported by the projects IGA MHCR NT/13897,
ED2.1.00/03.0078, LO1611/NPU I, MH CZ - DRO (NIMH-CZ, 00023752)
and PRVOUK P34.
A41
Salvinorin-A induces a unique pattern of neurophysiological
effects in humans characterized by alpha suppression and
widespread increases in cortical delta activity
M Valle1, A E Maqueda1, S Romero2, M A Mañanas2, S Barker3, J Riba1
1
Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; 2Universitat
Politècnica de Catalunya (UPC), Barcelona, Spain; 3Louisiana State
University, Baton Rouge, LA, USA.
Correspondence: M Valle
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A41
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Background
Salvinorin-A (SA) is a potent perception-modifying drug found in the
leaves of the plant Salvia divinorum. Unlike 5-HT2A agonists such as
DMT, LSD and psilocybin, SA is a selective kappa-opioid receptor
(KOR) agonist. Its pattern of effects in humans also shows important
differences with that of the classical psychedelics. While subjects also
experience intense visual and auditory phenomena, SA completely
blocks external sensory perception, and leads to a characteristic total
loss of contact with external reality. Here we investigated the neurophysiological correlates of SA effects in humans.
Methods
We measured spontaneous brain oscillations (EEG) in 24 healthy
volunteers, before and after the administration of 1 mg vaporized
SA. We recorded the EEG from 19 scalp leads and we calculated
drug-induced energy changes in ten frequency bands between 1.3
and 40 Hz. Additionally, we computed the changes in the intracerebral current density distribution associated with the voltage values
recorded at the scalp.
Results
SA administration led to rapid and significant changes in brain
oscillations that coincided with maximum drug levels in plasma.
SA suppressed the alpha rhythm (7.5-13 Hz) and markedly
increased slow delta activity (1.3-3.5 Hz). Less prominent effects
included increases in the theta (3.5-7.5 Hz) and low gamma (35–
40 Hz) bands. Alpha decreases were localized over parietooccipital regions, including the posterior cingulate cortex and visual areas. Delta increases were observed over most of the brain,
with the maximum located over auditory and visual cortex in the
left temporal lobe. Theta increases were found over left temporal
and frontal areas. Finally, gamma increases were restricted to visual areas in the occipital cortex.
Conclusion
These results show a unique pattern of neurophysiological effects for
SA in humans. While it shares with serotonergic psychedelics the
alpha-suppressing action, its main neurophysiological signature is an
atypical enhancement of slow delta activity. These differences may
explain the marked differences in subjective effects between SA and
5-HT2A agonists.
This research was supported by Grant PI12/02758 from the Spanish
government
A42
QEEG signatures predicting antidepressant response to ketamine
Martin Brunovsky1,2, Jiri Horacek1,2, Tomas Palenicek1,2, Peter Sos1, Filip
Tyls1,2, Michaela Viktorinova1,2, Cyril Höschl1,2
1
National Institute of Mental Health, Klecany, Czech Republic; 2Third
Faculty of Medicine, Charles University, Prague, Czech Republic
Correspondence: Martin Brunovsky (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A42
Objective
Treatment-resistant depression (TRD) is a disabling disorder that
negatively impact patient`s morbidity and mortality and constitutes a
major challenge for current psychopharmacology. The discovery of
rapid-acting antidepressive action of ketamine has motivated studies
aiming to reveal the molecular mechanism of this effect and to enable the clinical application of similarly rapid-acting antidepressants.
In our two studies, the time-course of effects of ketamine was
assessed in treatment-resistant depressive patients by QEEG to elucidate changes associated with treatment effect and to assess potential predictors of treatment response.
Methods
The pool analysis was completed from data of two double-blind,
cross-over, placebo-controlled studies, assessing the effect of single
infusion of ketamine (0.54 mg/kg within 30 min) in altogether 50 inpatients with major depressive disorder. EEG data were analysed during the infusion (10 min and 30 min) and 24 h after ketamine
administration using exact low-resolution electromagnetic tomography (eLORETA). Response to treatment was defined as a ≥50 % reduction of MADRS score.
Page 16 of 34
Results
Ketamine induced immediate (10 min and 30 min) decrease of parietooccipital sources of alpha-1 and alpha-2 activities and an increase
of gamma-sources in all subjects. Responders to medication were
characterized by excess of mediofrontal delta and theta sources in
comparison to non-responders. Moreover, only the responders
showed significant changes that persisted 24 h after infusion, while
no significant changes were observed in non-responders. Among the
clinical variables we have found a significant correlation between the
BPRS score during ketamine infusion and MADRS score at day 7, and
the intensity of psychotomimetic symptoms during infusion seems
to be the strongest clinical predictor of antidepressive effect of ketamine. Regarding the QEEG parameters, the patients with better responses showed higher pre-treatment theta activity in mediofrontal
areas and in the rostral anterior cingulate. Better response to ketamine was also connected with higher pre-treatment lagged phase
synchronization (i.e. higher connectivity) between anterior cingulate
and mediofrontal cortex at theta and alpha-1 frequency bands.
Conclusion
Our results suggest that an acute increase of mediofrontal cortical
sources of theta and delta activities after ketamine infusion could be
potential biomarkers to differentiate responders and non-responders to
ketamine. Higher pre-treatment theta activity in mediofrontal areas together with higher lagged phase synchronization between anterior cingulate and mediofrontal cortex at theta and alpha-1 frequency bands
could serve as predictors of treatment response to ketamine. Moreover,
the antidepressive effect of ketamine seems to be undoubtedly
connected with patient`s psychotomimetic experience.
Supported by grants AZV MZCR 15-33250A and by the project
PRVOUK P34.
Oral presentations
A43
Nonlinearity of the visual system assessed by cross-frequency
phase coupling
Matthijs JL Perenboom1,Yuan Yang3, Frans CT van der Helm3, Michel D
Ferrari1, Alfred C Schouten3,4, Else A Tolner1,2
1
Department of Neurology, Leiden University Medical Centre, Leiden,
The Netherlands; 2Department of Human Genetics, Leiden University
Medical Centre, Leiden, The Netherlands; 3Department of Biomechanical
Engineering, Delft University of Technology, Delft, The Netherlands;
4
MIRA Institute for Biomedical Technology and Technical Medicine,
University of Twente, Enschede, The Netherlands
Correspondence: Matthijs JL Perenboom (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A43
Background
Processing of visual input by the brain is a highly nonlinear operation, involving complex interactions among neuronal networks.
Nonlinear visual system activity includes harmonic interactions,
thought to reflect resonance of neural processing, whereas intermodulation, being the contribution of multiple input frequencies to one
output frequency, relates to functional integration [1]. Using a sumof-sinusoid signal as visual input [2], it is possible to elicit a richer
class of nonlinear responses than the classic pulse train stimulus,
thereby providing a more complete description of nonlinearity. Here,
we will use nonlinear EEG analyses to quantify higher-order nonlinearities in visual processing.
Methods
Ten healthy participants were subjected to bi-sinusoidal light stimulation of 13 and 23 Hz for 320 1 s-epochs, while scalp EEG (8 electrodes) was recorded at the occipital, parietal and frontal lobes. The
frequencies of light stimulus were chosen to guarantee no overlap of
their harmonic and intermodulation frequencies for different orders
of nonlinearity. Nonlinear interactions and time delay from stimulus
to cortex were analyzed in the frequency domain using novel phase
synchronization measures [3] and amplitude spectrum.
Results
Higher harmonic and intermodulation interactions were detected
between visual input and cortical responses. First to fourth order
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
phase coupling interactions were enhanced in the visual cortex compared to parietal and frontal responses. Spectral amplitude differences were less pronounced between cortical regions. Time delay
estimation showed a delay between light stimulus and visual cortex
of 118 ± 21 ms, significantly higher than the delay between stimulus
and frontal or parietal lobes.
Discussion
This study demonstrates the potential of using sum-of-sinusoid light
stimulation and quantitative nonlinear EEG analysis to identify
higher-order nonlinear dynamics of visual processing. We foresee
that application of the described frequency interaction analyses can
further our insight in the nonlinear dynamics of visual processing not
only in healthy subjects, but also with respect to the pathophysiology of neurological diseases with visual manifestations that relate
to cortical hyperexcitability, like migraine and epilepsy.
References
1. Friston KJ. Book review: Brain function, nonlinear coupling, and neuronal
transients. Neuroscientist. 2001 Oct 1;7(5):406–18.
2. Victor J, Shapley R. A method of nonlinear analysis in the frequency
domain. Biophys J. 1980 Mar;29(3):459.
3. Yang Y, Solis-Escalante T, Yao J, Daffertshofer A, Schouten AC, van der
Helm FC. A General Approach for Quantifying Nonlinear Connectivity in
the Nervous System Based on Phase Coupling. Int J Neural Syst. 2016
Feb;26(01):1550031.
A44
Whole-brain time-frequency analysis of event-related potentials for
the assessment of pharmacodynamic effects in the human brain
Roman Rosipal1,3, Leonardo Jose Trejo1, John Wallerius1, Ross Apparies2,
Barbora Cimrova1,3,4, James Miller2
1
Pacific Development and Technology, LLC, Palo Alto, CA 94303, USA;
2
Neuro Assessment Systems, Inc., Littleton, CO 80123, USA; 3Slovak
Academy of Sciences, Bratislava, Slovakia; 4Comenius University,
Bratislava, Slovakia
Correspondence: Roman Rosipal (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A44
We are developing Whole Brain Time-Frequency (WBTF) analysis as a
new physiological biomarker for clinical trials of pharmacodynamics of
novel drugs. WBTF analysis expands the power of event-related potential (ERP) assessment by using wavelets to measure both evoked
(phase-locked) and induced (non-phase-locked) activity. Unlike traditional ERP measures, which are indexed by specific electrodes and
peak latencies, WBTF analysis measures integrated change in brain responses across time, frequency and space to infer whether a drug has
a significant effect. WBTF analysis also uses permutation tests and multiple comparison corrections to identify important within-subject
changes between conditions and rule out differences arising from
recording noise, artifacts or random variability.
The specific aim of this study was to assess the sensitivity and specificity of WBTF analysis to drug effects that are typically measured with
ERP amplitudes and latencies. We simulated effects of dose-related
changes in N1-P2-P3 ERP components and 40-Hz induced gamma
bursts at 24 electrodes. Simulations included a range of amplitude effects, latency effects and signal-to-noise ratios, serving to define the
sensitivity and specificity of WBTF analysis to ERP differences.
The simulations allowed us to optimize parameters for WBTF analysis,
including choice of analyzing wavelets, energy normalization, baseline
correction, measures of evoked and induced activity, and method of
testing significant differences. We found that WBTF analysis reliably detects small differences in evoked activity (on the order of 10 %) in realistic noise and background EEG conditions. We found similar
detectability of small differences in induced 40-Hz gamma bursts.
It is the goal of the further studies to investigate the clinical relevance of these observed differences using WBTF analysis, and to relate the evoked and induced components ERP differences to
mechanisms of drug action. Currently we are applying WBTF analysis
to data from three Phase 1 clinical trials of novel compounds for
schizophrenia in both healthy controls and schizophrenia patients.
Page 17 of 34
A45
Dysregulation of hyperpolarization-activated inward cation current
(Ih) affects thalamocortical oscillations: the role of the auxiliary
subunit TRIP8b on HCN channel function in thalamic and cortical
neurons
Mehrnoush Zobeiri1, Rahul Chaudhary1, Annika Lütjohann1, Patrick
Meuth1, Hans-Christian Pape1, Dane M Chetkovich2, Gilles van Luijtelaar3,
Thomas Budde1
1
Institute für Physiologie I, Westfälische Wilhelms-Universität, Münster,
Germany; 2Davee Department of Neurology and Clinical Neurosciences
and Department of Physiology, Northwestern University, Chicago, IL,
USA; 3Donders Centre for Cognition, Radboud University Nijmegen,
Nijmegen, The Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A45
Background
The family of hyperpolarization-activated cyclic nucleotide-gated cation
(HCN) channels consisiting four different isoforms (HCN1-4) have a
major role in controlling neuronal excitability and generation of rhythmic oscillatory activity in individual neurons and neuronal networks [1,
2]. These channels activate in response to hyperpolarizing potentials
negative to −50 to −60 mV and depolarize the resting membrane potential. HCN channels are regulated by small molecules like cyclic nucleotides and different accessory proteins. TRIP8b is a brain-specific
accessory subunit of HCN channels which controls the gating, surface
expression and trafficking of different HCN channels subunits in many
regions of brain [3–5]. The role of this protein for Ih characteristics in
thalamic and cortical neurons and the functional consequences of
TRIP8b dysregulation for thalamocortical oscillations however is not yet
fully understood. The present study aimed at providing a better understanding of the functional role of TRIP8b in the thalamocortical system
and shedding some light on possible dysfunctional aspects by combining in vitro and in vivo electrophysiological approaches.
In this study, Ih was measured in whole cell patch clamp recordings
from thalamocortical (TC) neurons of different thalamic nuclei, as well
as pyramidal neurons in layer V and VI of the somatosensory cortex
of TRIP8b-deficient (TRIP8b−/−) and control (C57Bl/6 J) mice (p15 –
p90). Effects of TRIP8b-dependent dysregulation of Ih on thalamocortical oscillations was monitored by local field potential (LFP) recordings from the ventral-posterior medial complex of the thalamus
(VPM) and somatosensory cortex (p 90 – p120), regions which are
known to be involved in generation of normal and also pathological
thalamocortical oscillations.
Results
Characterization of Ih in the thalamocortical system in the absence of
the auxiliary subunit TRIP8b showed a significant decrease in Ih density and changes in intrinsic properties and firing patterns of TC and
cortical pyramidal neurons. These changes were accompanied by an
increase in cAMP sensitivity in TC neurons. Dysregulation of Ih in the
thalamocortical system of TRIP8b−/− mice was associated with altered
thalamocortical oscillations revealing a significant increase in slow oscillations in the delta frequency range (0.5-4 Hz) during episodes of
active-wakefulness.
Conclusion
The results of our study point to the importance of TRIP8b, as a
brain-specific auxiliary subunit of HCN channels, in regulation of cell
and network oscillations. It was demonstrated here that the presence
of TRIP8b is necessary for modulation of thalamocortical delta oscillations due to its direct effect on HCN channels protein expression in
the thalamocortical system.
References
1. Wahl-Schott, C. & Biel, M. HCN channels: Structure, cellular regulation and
physiological function. Cell. Mol. life Sci. 66, 470–494 (2009).
2. Biel, M., Wahl-Schott, C., Michalakis, S. & Zong, X. Hyperpolarizationactivated cation channels: from genes to function. Physiol. Rev. 89,
847–85 (2009).
3. Bina Santoro, Rebecca A. Piskorowski, Phillip Pian, Lei Hu, Haiying Liu,
and S. A. S. TRIP8b splice variants form a family of auxiliary subunits that
regulate gating and trafficking of HCN channels in the brain. Neuron 81,
8715–8723 (2009).
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
4. Lewis, A. S. et al. Alternatively spliced isoforms of TRIP8b differentially
control h channel trafficking and function. J. Neurosci. 29, 6250–6265 (2009).
5. Pan, Y. et al. TRIP8b is required for maximal expression of HCN1 in the
mouse retina. PLoS One 9, e85850 (2014).
6. Piskorowski, R., Santoro, B. & Siegelbaum, S. A. TRIP8b splice forms act in
concert to regulate the localization and expression of HCN1 channels in
CA1 pyramidal neurons. Neuron 70, 495–509 (2011).
7. Santoro, B. et al. Article TRIP8b Splice Variants Form a Family of Auxiliary
Subunits that Regulate Gating and Trafficking of HCN Channels in the
Brain. Neuron 62, 802–813 (2009).
8. Heuermann, R. J. et al. Reduction of thalamic and cortical Ih by deletion
of TRIP8b produces a mouse model of human absence epilepsy.
Neurobiol. Dis. 85, 81–92 (2016).
A46
Advanced EEG imaging of neuronal network interactions during
spatial working memory performance in rats: paving the road for
pharmacological assessments
S Jacob1,2, K Tahon1, D Balschun2, WH Drinkenburg1
1
Department of Neuroscience, Janssen Research & Development, a
Division of Janssen Pharmaceutica NV, 2340, Beerse, Belgium;
2.
Laboratory of Biological Psychology, University of Leuven, 3000,
Leuven,Belgium
Correspondence: S Jacob (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A46
Cognitive processes are based on the coordination of interactions of
populations of neurons that are distributed within and across different specialized brain areas. Accumulating evidence suggests that
neuronal oscillations play a pivotal role in driving brain communication. This communication is affected in many neurodegenerative diseases. Accordingly, understanding network interactions during
cognitive activity is crucial for a better comprehension of neurodegenerative consequences for cognitive functioning as well as for
assessing the efficacy of novel pharmacological treatments. The purpose of the present study was to evaluate putative EEG-based biomarkers during the trial-unique delayed nonmatching-to-location
(TUNL) task in rats. The task assesses memory for location across different delays and spatial separations in a computer-automated
touchscreen set-up. Once EEG-instrumented rats reached performance criteria (80 % accuracy in an 8 s delay for two consecutive
days), brain activity in the CA1 region of the hippocampus, medial
prefrontal cortex, and retrospenial cortex was monitored during two
consecutive TUNL sessions using an 8 s and a 16 s delay. Time
frequency-based analysis of EEG readouts was used to investigate
neuronal connectivity during the different delays comparing correct
vs. incorrect trials. In particular, cross-frequency coupling (CFC, when
the phase of a low frequency oscillation drives the amplitude of the
coupled higher frequency oscillation) was analyzed as this has been
suggested a possible mechanism facilitating working memory. It was
hypothesized that functional connectivity during the delay will be reduced during incorrect trials compared to correct ones for both delays and separations. Behavioral results confirmed that accuracy was
higher in the larger separation for the 8 s delay (M = 84.29 %, 95 %CI [81.03, 87.55]) compared with smaller separation for the same
delay (M = 74.99 %, 95 %-CI [69.89, 80.09]). Furthermore, the 16 s appeared to be more challenging as accuracy was reduced for both
large (M = 63.05 %, 95 %-CI [55.95, 70.15]) and small separation (M =
60.41 %, 95 %-CI [55.57, 65.25]) compared with the 8 s delay. Interestingly, results from the CFC during the delay support our hypothesis as 8 Hz frequency modulation of 90Hz amplitude in the medial
prefrontal cortex showed a more rapid decrease in CFC during the
delay for the incorrect trials in both delays and separations compared to the correct trials. Overall, results identified the critical role
of neuronal oscillations and connectivity for working memory in the
TUNL task. This study reinforces the strength of combining multiple
approaches to further understand cognitive processes and assessment of pharmacological treatments.
Page 18 of 34
A47
EEG functional connectivity of Brodmann area 24 in obsessivecompulsive disorder
J Koprivova1, E Saifutdinova1, T Nekovarova1, M Raszka1, J Prasko2
1
National Institute of Mental Health, Klecany, Czech Republic; 2Faculty of
Medicine and Dentistry,Palacky University Olomouc, University Hospital,
Olomouc, Czech Republic
Correspondence: J Koprivova (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A47
Background
A growing body of evidence have challenged the traditional
orbitofrontostriatal hypothesis and suggested that dysregulation of
widespread brain networks may underlie the OCD disorder. In last
decades, the increasing attention of neuroscience research has been
payed to large-scale network organization of the brain. Three
prominent networks were identified: “Central Executive Network”,
“Default Mode Network” and “Salience Network”, responsible for
synchronization of anticorrelated activity of DMN and CEN. Several
studies have stressed the role of the dorsal anterior cingulate cortex,
a core structure within the salience network, in OCD pathophysiology. Our two previous studies also revealed abnormal EEG activity
in this structure (Brodmann area, BA 24), however little is known
about its EEG functional connectivity in OCD. Based on our previous
findings, we tested functional connectivity between EEG sources in
BA 24 and rest of the brain in the group of OCD patients and in
heathy controls.
Methods
96 in-patients diagnosed with OCD and 95 healthy controls matched
for age and sex were included in the study. All subjects were righthanded. 27 OCD patients were drug-free and 69 were medicated with
SSRIs. All subjects underwent 19-channel resting-state EEG examination.
Functional connectivity was analysed in LORETA-KEY software. We
assessed connectivity between centroid of BA 24 and centroids of all
the other Brodmann areas as defined in the LORETA-KEY software.
Lagged nonlinear connectivity was computed in eight frequency
bands: delta (1.5 - 6 Hz), theta (6.5 - 8 Hz), alpha 1 (8.5 - 10 Hz),
alpha 2 (10.5 - 12 Hz), beta1 (12.5 - 18 Hz), beta 2 (18.5 - 21 Hz), beta 3
(21.5 - 30 Hz) and gamma (30.5 - 44.0 Hz). Groups were compared using tstatistics and permutation testing to correct for multiple comparisons.
Results
Drug-free and SSRIs medicated patients did not differ from each
other in functional connectivity and therefore they were further
tested as a unitary group. Compared with controls, OCD patients had
higher lagged nonlinear functional connectivity between BA 24 and
BA 5 and BA 7 in the beta 3 as well as in the gamma frequency band
(p < 0.05). In the gamma band the results were significant only for
the left BA 5 and 7, however connectivities in the right hemisphere
were close to threshold.
Conclusion
We hypothesize that an aberrant synchronization between default
mode and central executive network related to the aberrant activity
of the salience network may underlie symptoms of OCD.
This work was supported by the projects ED2.1.00/03.0078, LO1611
and MH CZ - DRO 00023752.
A48
Cortical network reorganization in mild and prodromal Alzheimer
disease: graph theory approach on resting state EEG recordings
L Bonanni1, R Franciotti1, NW Falasca2, F Nobili3, D Arnaldi3, M Onofrj1
1
Department of Neuroscience, Imaging and Clinical Science, and Aging
Research Centre, G. d’Annunzio University, Chieti, 66013, Italy; 2BIND –
Behavioral Imaging and Neural Dynamics Center, University of ChietiPescara, Chieti, 66013, Italy; 3Department of Neuroscience (DINOGMI),
Clinical Neurology, University of Genoa and IRCCS AOU San Martino-IST,
Genoa, 16126, Italy
Correspondence: L Bonanni (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A48
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Background
Alzheimer’s disease (AD) has a long preclinical period in the absence
of overt symptoms in which the process progresses until it crosses a
threshold to clinically recognizable dysfunction [1]. Graph theoretical
analysis of cerebral networks has been implemented in AD challenging the classical concept of neurological disorders being either
‘local’ or ‘global’, and have pointed to the overload and failure of
hubs as a possible final common pathway in neurological disorders.
Previous EEG studies on the comparison between AD and control
subjects reported divergent results [2]. An intermediate trend was
found in subjects with mild cognitive impairment (MCI) with respect
to AD and control subjects [3]. The aim of the study was to asses by
means of graph theory analysis if AD patients with mild dementia
could show a different cortical organization from age matched control subjects and if these possible differences could be already
present at the stage of MCI.
Results
The main finding of the present study is that network reorganization
is evident in AD since the prodromal stage (AD-MCI). Specifically, ADMCI and AD showed a lower number of links among nodes than
control group (p = 0.0007). Both inward and outward links among
nodes and brain areas with a high level of functional connectivity
(so-called hubs) were found to be reduced in both AD-MCI and AD
patients. Hubs in the parietal areas (P3, P4, and Pz) showed lower
number of links in AD-MCI and AD than control group. Temporal
nodes showed lower clustering coefficient and local efficiency in patients than control group. Significant differences between AD-MCI
and AD were found in the right occipital node. Indeed, the clustering
coefficient and the local efficiency was reduced in AD compared with
AD-MCI in O2 (p < 0.05).
Conclusions
Our results suggest that brain network functional alterations mainly
involved the temporal nodes in prodromal stage of AD, whereas
brain dynamic changed in the posterior areas with disease progression to overt AD dementia.
The functional disconnection between temporal and parietooccipital areas could be related to medial temporal lobe atrophy
which is a characteristic neuropathological change in the early
stage of AD [4].
References
1. Braak H, Thal DR, Ghebremedhin E, Del Tredici K. Stages of the
pathologic process in Alzheimer disease: age categories from 1 to
100 years. J Neuropathol Exp Neurol. 2011;70:960–9.
2. de Haan W, Pijnenburg YA, Strijers RL, van der Made Y, van der Flier WM,
Scheltens P, Stam CJ. Functional neural network analysis in
frontotemporal dementia and Alzheimer’s disease using EEG and graph
theory. BMC Neurosci. 2009;10:101.
3. Vecchio F, Miraglia F, Quaranta D, Granata G, Romanello R, Marra C,
Bramanti P, Rossini PM. Cortical connectivity and memory performance
in cognitive decline: A study via graph theory from EEG data.
Neuroscience. 2016;316:143–50.
4. Rusinek H, Endo Y, De Santi S, Frid D, Tsui WH, Segal S, Convit A, de
Leon MJ. Atrophy rate in medial temporal lobe during progression of
Alzheimer disease. Neurology 2004;64:2354–9.
A49
Sleep disturbances in obsessive-compulsive disorder: association
with response to repetitive transcranial magnetic stimulation
(rTMS)
Lana Donse1, Alexander T Sack4,5, Paul B Fitzgerald6, Martijn Arns1,2,3
1
Research Institute Brainclinics, Nijmegen, The Netherlands;
2
Department of Experimental Psychology, Utrecht University, Utrecht,
The Netherlands; 3neuroCare Group, Munich, Germany; 4Department
of Cognitive Neuroscience, Maastricht University, Maastricht, The
Netherlands; 5Maastricht Brain Imaging Center, Maastricht, The
Netherlands; 6Monash Alfred Psychiatry Research Centre, the Alfred
and Monash University, Central Clinical School, Victoria, Australia
Correspondence: Lana Donse (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A49
Page 19 of 34
Background
Obsessive-compulsive disorder (OCD) is a debilitating disorder with a
substantial portion of patients not responding to first-line treatment.
Repetitive transcranial magnetic stimulation (rTMS) is an effective
augmentation strategy for treatment-refractory patients, but as the
response rate is approximately 35 % [1], it is important to identify
predictors of rTMS response. Emerging evidence indicates a relatively
high prevalence of sleep disturbances in OCD patients, in particular
circadian rhythm sleep disorder (CRSD) [2]. It is therefore proposed
that sleep disturbances may affect treatment efficacy.
Methods
In this open-label study, 22 OCD patients received at least 10 sessions of
rTMS treatment targeted at the supplementary motor area combined
with psychotherapy. They were compared to a matched control group of
healthy subjects to examine sleep disturbance. Treatment outcome was
measured by monitoring obsessive-compulsive as well as depressive
symptoms each fifth session using the YBOCS and BDI, respectively.
Treatment response was defined as a reduction > 35 % on the YBOCS.
Sleep disturbances were measured by means of self-report (PSQI, HSDQ)
and actigraphy. Treatment response prediction models were based on
subjective and objective measures of CRSD and insomnia.
Results
OCD patients showed a higher rate of sleep disturbances than controls.
The OCD group consisted of 12 responders and 10 non-responders. Responders showed a significantly larger reduction in both obsessivecompulsive and depressive symptoms, while no difference in baseline
severity existed. Sleep disturbances, on the contrary, were more severe
in non-responders than responders. Furthermore, a predictive model
based on CRSD could accurately predict treatment response with 83 %
sensitivity and 63 % specificity, whereas the insomnia model could not.
Conclusions
Sleep disturbances in OCD can significantly predict rTMS treatment
response, in particular CRSD. Therefore, CRSD may serve as a biomarker for different subtypes of OCD that correspond with response
to specific treatment approaches.
Competing interests
PBF is supported by a NHMRC Practitioner Fellowship (1078567).
PBF has received equipment for research from MagVenture A/S, Medtronic Ltd,
Cervel Neurotech and Brainsway Ltd and funding for research from Neuronetics
and Cervel Neurotech. He is on the scientific advisory board for Bionomics Ltd.
MA reports research grants, options/shares from Brain Resource Ltd. (Sydney,
Australia) and neuroCare group and he is also a co-inventor on 4 patent
applications (A61B5/0402; US2007/0299323, A1; WO2010/139361 A1) related to
EEG, neuromodulation and psychophysiology, but does not own these nor
receives any proceeds related to these patents.
References
1. Berlim, M. T., Neufeld, M. H., Van den Eynde, F. Repetitive transcranial
magnetic stimulation (rTMS) for obsessive-compulsive disorder (OCD): An
exploratory meta-analysis of randomized and sham-controlled trials. J Psychiatr Res. 2013; 47:999–1006.
2. Nota, J. A., Sharkey, K. M., Coles, M. E. Sleep, arousal, and circadian rhythms
in adults with obsessive-compulsive disorder: A meta-analysis. Neurosci Biobehav Rev. 2015; 51:100–107.
A50
Glutamatergic deficit and negative symptoms: new evidence from
the ketamine model of schizophrenia
Stephanie Thiebes1, Gregor Leicht1, Stjepan Curic1, Saskia Steinmann1, Nenad
Polomac1, Iris Eichler2, Lars Eichler2, Christian Zöllner2, Jürgen Gallinat3, Ileana
Hanganu-Opatz4, Christoph Mulert1
1
Psychiatry Neuroimaging Branch, Department of Psychiatry and
Psychotherapy, University Medical Center Hamburg-Eppendorf,
20251Hamburg, Germany; 2Department of Anesthesiology, University
Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany;
3
Department of Psychiatry and Psychotherapy, University Medical Center
Hamburg-Eppendorf, 20251 Hamburg, Germany; 4Developmental
Neurophysiology, Institute of Neuroanatomy, University Medical Center
Hamburg- Eppendorf, 20251 Hamburg, Germany
Correspondence: Stephanie Thiebes (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A50
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Targeting the N-methyl-D-aspartate-receptor (NMDAR) is a major
approach for treating negative symptoms of schizophrenia. The ketamine model of schizophrenia has the advantage of comprehensively
producing schizophrenia like symptoms such as positive, cognitive
and negative symptoms in healthy volunteers. The amplitude of the
Mismatch Negativity (MMN), a neurophysiological parameter related
to infrequent stimuli, is known to be significantly reduced in
schizophrenic patients but also in healthy controls receiving ketamine [1,2]. Accordingly, it was the aim of the present study to investigate whether changes of MMN during ketamine administration are
related to the emergence of negative symptoms in healthy subjects.
Therefore, we examined the impact of ketamine on MMN amplitudes
and its sources (sources localization approach: low resolution electromagnetic tomography (LORETA)) by means of 64-channel electroencephalography (EEG) recording during performance of an auditory
MMN paradigm and assessed the psychopathological status using
the Altered State of Consciousness (5D-ASC) Rating Scale and the
Positive and Negative Syndrome Scale (PANSS). Twenty-four male,
healthy volunteers were measured with pharmacological EEG using a
single-blind, randomized, placebo-controlled crossover design.
We identified significant changes of the MMN response, to both duration and frequency deviants, under ketamine condition as well as a
significant increase in all PANSS scores. Reductions of MMN amplitudes were significantly correlated with more pronounced negative
symptoms, assessed by the PANSS.
Accordingly, the MMN might represent a biomarker for negative
symptoms in schizophrenia related to an insufficient NMDAR system
and could be used to identify schizophrenia patients with negative
symptoms due to NMDAR dysfunction and thus to determine a maximal benefit of drugs modulating neurotransmission at the NMDAR.
Competing interests
The authors declare that they have no competing interests.
References
1. Shelley AM, Ward PB, Catts SV, Michie PT, Andrews S, McConaghy N.
Mismatch negativity: an index of a preattentive processing deficit in
schizophrenia. Biol Psychiatry. 1991; 30(10):1059–1062.
2. Umbricht D, Koller R, Vollenweider FX, Schmid L. Mismatch negativity
predicts psychotic experiences induced by NMDA receptor antagonist in
healthy volunteers. Biol Psychiatry. 2002; 51(5):400–406.
A51
Isolated epileptiform discharges in psychiatry: outcomes in an
integrative practice
Ronald J Swatzyna1, Jay D Tarnow1, Robert P Turner2, Alexandra J Roark1,
Erin K MacInerney1, and Gerald P Kozlowski3
1
Tarnow Center for Self-Management, Houston, TX, USA; 2Network
Neurology LLC, Charleston, SC, USA; 3Saybrook University, Oakland, CA,
USA
Correspondence: Ronald J Swatzyna (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A51
Background
The search for biomarkers that can inform medication decisions in
neuropsychiatric disorders is a goal of the Research Domain Criteria
project under the National Institute of Mental Health. Isolated epileptiform discharges (IEDs) may be such a biomarker. IEDs have been
linked to increased psychopathology that traverses many diagnoses
[1]. It has been suggested that IEDs may represent an epiphenomenon with an etiology of unappreciated significance [2]. The literature suggests that anticonvulsants should be considered when IEDs
are identified [3, 4]; however, outcome studies have yet to be
published. This study investigates the predictive value of IEDs as a biomarker for the use of anticonvulsants on a large cohort of patients.
Method
We reviewed refractory cases from a large multidisciplinary practice
whose EEG readings contained IEDs and were subsequently medicated
with anticonvulsants by the clinic’s psychiatrist. The psychiatrist’s follow
up progress notes were assessed to determine the impact of adding
Page 20 of 34
anticonvulsants. Ratings were based on clinical presentation and reported in three categories: Improved, unchanged, and more severe.
There were two exclusion criteria: a prior diagnosis of seizure disorder
and a history of prior treatment with anticonvulsants. Of the 735 patients in our database, 325 (44.22 %) were identified with IEDs. The final
sample was comprised of 76 refractory cases. The study included 61
males (80.26 %) and 15 females (19.74 %) ages 5 to 52.
Results
Of the 76 cases treated with anticonvulsants, the vast majority were
found to be improved in follow-up progress notes: Improved 65
(85.53 %), Unchanged 6 (7.89 %), and More Severe 5 (6.58 %).
Conclusions
IEDs predict positive treatment outcome to anticonvulsant medication and may not only represent a biomarker for medication
selection but also a step towards an evidence-based diagnosis. This
review serves as the first large outcome study in which patients with
IEDs were treated with anticonvulsants. Our findings suggest that
EEG screening should be utilized in all refractory cases regardless of
age, gender, or diagnosis. When IEDs are identified, anticonvulsants
should be considered as a treatment option.
Consent to publish
This study does not contain details relating to individual participants.
Competing interests
The authors declare that they have no competing interests.
References
1. Zimmerman EM, Konopka LM. Preliminary findings of single- and
multifocused epileptiform discharges in nonepileptic psychiatric patients.
Clin EEG Neurosci. 2014;45(4):285–292. doi: 10.1177/1550059413506001.
2. Boutros NN. Standard EEG: A research roadmap for neuropsychiatry. Cham,
Switzerland: Springer; 2013:135–147chap14.
3. Millichap JG, Millichap JJ, Stack CV. Utility of the electroencephalogram in
attention deficit hyperactivity disorder. Clin EEG Neurosci. 2011;42(3):180–184.
doi: 10.1177/155005941104200307.
4. Swatzyna RJ, Tarnow JD, Roark A, Mardick J. The utility of EEG in
attention deficit hyperactivity disorder: a replication study. Clin EEG
Neurosci. 2016. doi: 10.1177/1550059416640441.
A52
Do cannabinoid antagonists affect cognition? SLV326 induces
changes in theta and gamma bands in active rats
Martin F J Perescis1,2, Natasja de Bruin3, Liesbeth Heijink4, Chris Kruse5,
Lyudmila Vinogradova6, Annika Lüttjohann7, Gilles van Luijtelaar1,
Clementina M van Rijn1
1
Radboud University, Nijmegen, The Netherlands; 2HAS University of
Applied Sciences, ‘s Hertogenbosch, The Netherlands; 3Fraunhofer
Institute for Molecular Biology and Applied Ecology IME, Project Group
Translational Medicine & Pharmacology TMP, Frankfurt am Main,
Germany; 4 Astellas Pharma Europe R&D, Leiden, The Netherlands;
5
University of Amsterdam, Amsterdam, The Netherlands; 6 Institute of
Higher Nervous Activity and Neurophysiology, Russian Academy of
Sciences, Moscow, Russia; 7 Westfälische Wilhelms Universität Münster,
Münster, Germany
Correspondence: Martin F J Perescis (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A52
Cannabinoid CB1 antagonists have been investigated for possible
treatment of e.g. obesity-related disorders. However, clinical application was halted due to their symptoms of anxiety and depression. In
addition to these adverse effects, we have shown earlier that chronic
treatment with the CB1 antagonist rimonabant may induce convulsive seizures which were EEG-confirmed. However, due to the wide
distribution of CB1 receptors throughout the CNS, it is highly unlikely
that chronic blocking of the CB1 receptor is only manifested in seizures. CB1 agonists have been described to alter the EEG frequency
spectrum. No such data are available for CB antagonists.
In a regulatory repeat-dose toxicity study “muscle spasms” were observed in Wistar rats, daily dosed with the CB1 receptor antagonist
SLV326 during 5 months. In selected SLV326-treated and control
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
animals, EEG and behavior were monitored for 24 h. Subsequently,
random segments of the interictal EEG were selected, totaling
20 min per animal. These segments were assigned to subsets of ‘active state’ or ‘passive state’, based on Passive Infrared (PIR) motion
detection. Spectral information was calculated using a Fast Fourier
Transformation analysis.
25 % of SLV326 treated animals showed, EEG-confirmed, spontaneously occurring generalized convulsive seizures, whereas all controls
were seizure-free. The behavioral signs of the seizures were typical
for a limbic origin.
The frequency spectrum of the interictal EEG of the treated rats showed
a lower theta peak frequency, as well as lower gamma power compared to the controls. These frequency changes were state-dependent:
they were only found during high locomotor activity. However, the
treatment did not affect the amount of locomotor activity itself.
Apart from confirming our previous finding that long-term blockade
of the endogenous cannabinoid system can provoke limbic seizures
in otherwise healthy rats, this study shows that SLV326 alters the frequency spectrum of the EEG, but only when rats are highly active. It
is therefore likely that the EEG effects caused by SLV326 are linked to
higher order behavior that might be present during locomotion.
Theta rhythm is shown to be a marker of complex behavior, and
gamma rhythm is typically associated with cognitive functions.
Therefore, these observations suggest that CB antagonists might
have effects on complex behavior and cognition.
A53
EEG connectivity on sources in male non-smokers after nicotine
administration during resting-state
Paolo Ranzi1, Jan A Freund2,4, Christiane M Thiel3,4 & Christoph S Herrmann1,4
1
Experimental Psychology Group, Department of Psychology, Cluster of
Excellence “Hearing4all”, European Medical School, Carl von Ossietzky
University, Oldenburg, Germany; 2Institute for Chemistry and Biology of the
Marine Environment, Carl von Ossietzky University, Oldenburg, Germany;
3
Biological Psychology Group, Department of Psychology, Cluster of
Excellence “Hearing4all”, European Medical School, Carl von Ossietzky
University, Oldenburg, Germany; 4Research Center Neurosensory Science,
Carl von Ossietzky University, Oldenburg, Germany
Correspondence: Paolo Ranzi (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A53
Background
New developments in pharmacology are based on non-invasive neuroimaging, particularly by leveraging and optimizing techniques and
methodologies already validated in basic neuroscience. Particularly
interesting is the use of connectivity measures of electromagnetic oscillatory activity regarding the modulation of vigilance. Indeed, several recent anesthesiology papers found a connection between
vigilance and the connectivity measured from electromagnetic oscillatory activity [1]. We present an EEG connectivity study aimed to establish whether nicotine-induced modulations of vigilance impact
connectivity.
Methods
EEG activity was recorded in an eyes-open and eyes-closed condition
before and after drug administration in thirty healthy male nonsmokers. The subjects were randomly allocated either to a nicotine
group (14 subjects, 7 mg transdermal nicotine) or to a placebo
group. A double-blind placebo-controlled design was implemented.
With source reconstruction procedure (eLORETA algorithm), we extracted thirteen time-series representing thirteen regions of interest
(ROIs). Each ROI was anatomically precise and belonged to the
resting-state network which seems to be modulated specifically by
eyes-open and eyes-closed activity. In the literature such restingstate network is labeled as the Default Mode Network. Here we
conducted connectivity analysis (renormalized Partial Directed Coherence, rPDC) on the ROIs’ time-series, focusing on the frequency range
of 8.5 to 18.4 Hz. Such frequency range was further subdivided into
three frequency bands (α1, α2 and β1) in order to comply with
current EEG standards of practice.
Page 21 of 34
Results
Our connectivity analysis found that during eyes-closed, nicotine decreased feed-back connectivity (from precentral gyrus to precuneus, angular gyrus, cuneus and superior occipital gyrus) at 10.5-12.4 Hz (α2). During
eyes-open, no significant results were found at any frequency range.
Conclusions
We interpreted the results by help of previous anesthesiology literature
about an anti-correlated relationship between feed-back and feedforward connectivity. Such relationship emerged by pharmacologicallyinduced sedation during eyes-closed condition. Our results suggest that
nicotine potentially increases the level of vigilance. Such nicotine-effect
is particularly prominent during the eyes-closed condition.
Competing interests
Nothing to declare.
References
1. Maksimow A, Silfverhuth M, Langsjo J, Kaskinoro K, Georgiadis S,
Jaaskelainen S, et al. Directional connectivity between frontal and
posterior brain regions is altered with increasing concentrations of
propofol. PloS one. 2014;9(11):e113616.
A54
Withdrawn
Poster presentations
A55
Modulation of the NMDA receptor function enhances hippocampal
network oscillations, connectivity and synaptic LTP in-vivo: A case
study with a Glycine Transporter-1 Inhibitor
Ahnaou A, Biermans R, Huysmans H, Drinkenburg WH
Department of Neuroscience Discovery, Janssen Research &
Development, a Division of Janssen Pharmaceutica NV. Turnhoutseweg
30, B-2340 Beerse, Belgium
Correspondence: Ahnaou A (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A55
Hypofunction of N-methyl-d-aspartate receptors (NMDARs) has been associated with deficits in synaptic plasticity and cognitive decline as found
in neuropsychiatric and neurodegenerative disorders such as Alzheimer’s
disease. Glycine and D-serine are endogenous ligands of the NMDAR and
therapeutic approaches that enhance NMDAR activity through increases
in glycine and/or D-serine levels are expected to enhance synaptic
strength and to potentially improve have impact on cognition processes.
The present in-vivo study investigated whether positive modulation of
brain glycine levels, through modulation by the glycine transporter 1
(GlyT1) inhibitor SSR504734, affects network connectivity and long-term
potentiation (LTP) at the hippocampus. For in-vivo network oscillations
and connectivity, multichannel EEG recordings were performed in conscious Sprague–Dawley rats from frontal cortical, hippocampal CA1 and
CA3 and dentate gyrus (DG) structures after subcutaneous administration
of vehicle or SSR504734 (2.5, 10 and 40 mg/kg). For hippocampal synaptic plasticity, rats were anesthetized with urethane and recording and
stimulating electrodes were inserted at the DG and at the medial perforant pathway (MPP), respectively. Population spike (PS) amplitudes (PSA)
and excitatory postsynaptic potential (EPSP) slope were measured before
and 2-h after high-frequency stimulation (HFS).
SSR504734 (at 40 mg/kg) elicited robust EEG slow theta oscillations
(4–6.5 Hz) at the DG, CA1 and CA3 and in addition slow gamma oscillations (30-50Hz) in the frontal areas, next to network coherence
changes between frontal and CA1 recording sites, which were dissociated from motor behavior. SSR504734 (at 40 mg/kg) enhanced LTP
of the PS amplitude after HFS of the MPP synapse, whereas the potentiation of EPSP slope was short-lived.
The present data support the hypothesis on a facilitating role of the
NMDARs glycine binding site on network oscillations and synaptic efficacy at the medial perforant path of the DG. Future studies will
evaluate novel approaches targeting D-Serine modulatory sites, for
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
example by inhibition of the enzyme d-amino acid oxidase (DAAO),
which slows the break-down of D-serine, or by its transporter, the
alanine-serine-cysteine-1 (Asc-1), the abnormal glio-transmission of
which has been linked to synaptic failure in Alzheimer’s disease.
A56
Withdrawn
A57
Neurofeedback training as a treatment for dyslexia
Parissa Azadi, Stig Hollup
Department of Psychology, Norwegian University of Science and
Technology, Trondheim, Norway
Correspondence: Stig Hollup (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A57
Dyslexia is amongst the commonest of neurobiological disorders, affecting about 20 % of children in Norway. Its heterogeneity makes it
difficult to establish a single treatment which is suitable for most of
the affected. According to the phonological theory of dyslexia, the
disorder is caused by a deficit in the representation, storage and recall of speech sounds. Different brain areas have been linked to the
phonological deficit by means of different brain imaging techniques,
among other quantitative electroencephalography (qEEG).
The aim of this study was to improve reading ability in children with
dyslexia by means of individualized neurofeedback training. The study
was conducted as a pre-post intervention single-subject design with 5
participants, aged from 13 to 14 years. The intervention consisted of 25
sessions of neurofeedback training, 15 beta/theta frontocentral sessions
and 10 individualized sessions, mostly towards the language areas. The
effect of the intervention was measured by means of qEEG and the
LOGOS (a Norwegian dyslexia assessment battery).
The results showed improvement in reading abilities and phonological
skills amongst all participants. Furthermore, qEEG analysis showed increased alpha activity in several brain areas, and normalization of theta
and beta activity in comparison to a normative database. An increase
of alpha activity may possibly indicate changes in alpha coherence
which can be an indication of improved attentional processes. This
may explain the improvements in reading and phonological skills. The
analysis also confirms the heterogeneity of dyslexia, and the complicity
of several brain areas that are involved in dyslexia.
This study is limited by the small number of participants, and the restriction in time (the number of training sessions offered). However, the
improvement in reading and phonological skills in this study suggests
that neurofeedback training may be an effective and relevant intervention for adolescents with dyslexia. But, further research in this area with
larger samples and a larger number of training sessions is required.
The study was approved by the regional ethics committee.
Competing interests
There are no competing interests.
A58
Mismatch negativity (MMN) in serotonergic model of psychosis
induced by psilocybin
Anna Bravermanova1,2, Michaela Viktorinova1,3, Filip Tyls 1,3, Jakub Korcak1,3,
Vlastimil Koudelka1, Martin Brunovsky1,3, Martin Bares1,3 and Tomas Palenicek1,3
1
National Institute of Mental Health, Klecany, Czech Republic; 21st Faculty
of Medicine, Charles University in Prague, Prague, Czech Republic; 33rd
Faculty of Medicine, Charles University in Prague, Prague, Czech Republic
Correspondence: Anna Bravermanova (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A58
Background
The auditory MMN (mismatch negativity) is considered to be an
index of automatic context-dependent information processing and
Page 22 of 34
auditory sensory memory. MMN deficit is a characteristic endophenotype of schizophrenia. A 5-HT2A agonist psilocybin induces acute
transient psychotic symptoms and is extensively used as a putative
pharmacological model of schizophrenia. Our aim was to investigate
the effect of psilocybin on this pre-attentive cognitive functions.
Methods
A double-blind, placebo controlled study design was used. 20
healthy adult volunteers were administered a dose of psilocybin
(0,26 mg/kg) and placebo per os in 2 separate sessions. Auditory
MMN was recorded in sound and electrically shielded room, 120 min
after ingestion of psilocybin/placebo. Participants were lying down
with their eyes closed in a comfortable setting with two sitters who
were present during whole experiment.
MMN
A single deviant paradigm with 1350 standard (1000Hz, 75 dB SPL,
100 ms duration) and 75 deviant in frequency (1200Hz, 75 dB SPL,
100 ms) tones were presented binaurally in regular order when every 20th
was deviant tone. Data was acquired with a standard 32-channel digital
EEG amplifier BrainScope (unimedis, Prague) with 21 Ag/AgCl scalp electrodes placed according to the 10/20 system and sampled at 1000 Hz.
Results
Mismatch negativity was calculated by subtracting the average of
frequently occurring stimuli from the average of deviants. There were
no significant differences in latency, absolute amplitude and area
under curve of MMN during psilocybin intoxication compared to placebo. Furthermore, there were no correlations between subjective effects induced by psilocybin (HRS and ASCS) and MMN.
Conclusion
Our results correspond with previous findings [1]. Psilocybin does
not affect processing at the level of pre-attentive cognition and the
auditory sensory memory.
This effect is probably due to different underlying receptor mechanism as the generation of MMN is strongly dependent on NMDAR dysfunction. Another reason for negative results could be inappropriate
timing of recording or insufficient single-deviant paradigm.
This work is supported by Ministry of Health of the Czech Republic,
grant nr. 15-29900A. All rights reserved.
References
1. Umbricht D, Vollenweider F X, Schmid L, Grübel C, Skrabo A, Huber R et
Koller R. Effects of 5-HT2A agonist Psilocybin on Mismatch Negativity
generation and AX-Continuous Performance Task: Implications for the
Neuropharmacology of Cognitive Deficits in Schizophrenia. Neuropsychopharmacology 2003;Jan;28(1):170–81
A59
Comparison between SMR and Upper Alpha Neurofeedback
trainings as a non-pharmacological treatment of ADHD and sleep
disorders in children and adolescents
Eléonore Czarik1, Hervé Caci2, Jean-Paul Laurent3
1
Université Paris 8, Ecole doctorale cognition, langage, interaction, Saint-Denis,
France; 2Hopitaux pediatriques de Nice Chulenval, Nice, France; 3Lutin cité des
sciences et de l’industrie, laboratoire, cognitions humaines et artificielles, chart
ea 404, Université Paris 8, Saint-Denis, France
Correspondence: Eléonore Czarik (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A59
Background
About 5 % of school-aged children may have an Attention DeficitHyperactivity Disorder (ADHD), a neurodevelopmental disorder often
associated with other comorbid conditions including sleep disorders.
ADHD became a public health concern. Psychostimulants are the first
line pharmacological treatments for ADHD. However, parents are
often reluctant to medicate their children and, additionally, a proportion of patients stop their treatment because of side effects. Nonpharmacological treatments are also available. Recently, improvements of cognitive functioning and hyperactivity level of patients
with ADHD have been reported after Neurofeedback trainings with a
relative Upper Alpha Power enhancement paradigm. Sensorimotor
rhythm (SMR) Neurofeedback has been also proposed to improve
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
ADHD symptoms. The aim of this study is to compare the benefits of
Upper Alpha and SMR trainings on ADHD symptoms and concomitant improvement of sleep.
Methods
In this controlled and randomized study, 60 French medication-free children and adolescents with ADHD aged from 8 to 15 years old will participate in 30 neurofeedback sessions. They will be assigned to either in
either the SMR or the Upper Alpha training group. EEG, ADHD rating
scales, cognitive assessment, and actigraphic records will be performed at
pre-, mid- and post-training times, and 6 months after the end of protocol.
Results
The main expected outcome is the clinical reduction of at least 30 %
of ADHD symptoms, and we anticipated the superiority of Upper
Alpha training over SMR in reducing hyperactivity levels. Improvement of sleep quality is a secondary outcome.
Conclusion
To date, no comparison between SMR and Upper Alpha Neurofeedback trainings with a significant number of sessions and enough patients in each group has been conducted. We hope to gain valuable
insights into specific effects of both trainings on ADHD symptoms
and sleep without any medication. This study would foster the development of research on Neurofeedback and its clinical applications,
which are under-investigated in France.
Trial Registration
N°ID RCB 2016-A00655-46
Keywords
ADHD, Neurofeedback, SMR-Upper Alpha Training, EEG, non pharmacological treatment, sleep disorders
A60
Effect of Tai-Chi and Cyclic Meditation on hemodynamic responses
of the prefrontal cortex
S Deepeshwar1, NK Manjunath2, M Avinash3
1
Cognitive Neuroscience Laboratory (CNL), Swami Vivekananda Yoga
Anusandhana Samsthana (S-VYASA), 19 Eknath Bhavan, Gavipuram
Circle, K.G. Nagar, Bangalore India – 560019; 2Swami Vivekananda Yoga
Anusandhana Samsthana (S-VYASA), 19 Eknath Bhavan, Gavipuram
Circle, K.G. Nagar, Bangalore India – 560019; 3Shanghai Sports University,
Shanghai, China.
Correspondence: S Deepeshwar (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A60
Background
Mind body based meditation techniques called Tai-Chi Chuan (TCC, a
moving meditation) [1] and Cyclic Meditation (CM, a stimulation and
relaxation meditation) [2] has been proven to reshape the patterns
of brain structures and functional connectivity. TCC practices showed
improvement in the brain functions associated with cognition, behavior and health [3]. Similarly, CM also reported improvement in
midbrain region [4] associated with better information processing
speed or improved motor speed [5].
Method and materials
We evaluated the effect of Tai-Chi Chuan (TCC, a Chines movement
based meditation technique) and Cyclic Meditation (CM, an Indian
traditional based stimulation and relaxation meditation technique)
on the hemodynamic responses of the prefrontal cortex (PFC) activity
and autonomic functions (such as R-R interval (RR-I of heart rate variability and respiration). These two meditation practices were compared with simple walking. Employing 64 channel near infrared
spectroscopy (NIRS), we measured hemoglobin concentration change
(i.e., Oxyhemoglobin [DHbO], Deoxyhemoglobin [DHbR] and Total
hemoglobin change [DTHC]) in the bilateral PFC before and after
TCC, CM and Walking in young college students (n = 25; average
mean age ± SD; 23.4 ± 3.1 years).
Results
We observed the left PFC activity predominantly modulates sympathetic
activity effects during the Tai-Chi whereas CM showed changes on right
PFC with vagal dominance. However, the changes in oxyhemoglobin and
total blood volume change after Tai-Chi was significant higher (p < 0.05,
spm t-maps) on left hemisphere, whereas after CM, there were a
Page 23 of 34
significant increase in oxyhemoglobin (p < 0.01) with a decrease in deoxyhemoglobin (p < 0.05) on right PFC. The normal walking showed decrease in Oxyhemoglobin with increase in deoxyhemoglobin on left PFC.
The autonomic functions result showed a significant increase in RR- interval (p < 0.05) along with significant reduction in HR (p < 0.05) in CM
whereas Tai-chi session showed significant increase in HR (p < 0.05) when
compared to walking session. Within group analysis showed a significant
reduction in RR-I and significant increase in HR both in Tai-chi and walking sessions. The CM showed there were a significant improvement in
RR-interval of HRV (p < 0.01) with reduction of heart rate and breath rate
(p < 0.05).
Conclusions
The result suggested that Tai-Chi and CM both have positive effect
on left and right prefrontal cortex and increase sympathovagal balance (alertful rest) in autonomic nervous system activity.
Keywords
Tai-Chi-Chuan (TCC); Yoga; Cyclic Meditation (CM); Walking; Prefrontal
Cortex (PFC); Heart Rate Variability (HRV)
References
1. J. L. W. Robins, R. K. Elswick, and N. L. McCain, “The story of the evolution
of a unique tai chi form: origins, philosophy, and research.,” J. Holist.
Nurs., vol. 30, no. 3, pp. 134–46, 2012.
2. P. Subramanya and S. Telles, “A review of the scientific studies on cyclic
meditation.,” Int. J. Yoga, vol. 2, no. 2, pp. 46–48, Jul. 2009.
3. G.-X. Wei, H.-M. Dong, Z. Yang, J. Luo, and X.-N. Zuo, “Tai Chi Chuan
optimizes the functional organization of the intrinsic human brain
architecture in older adults.,” Front. Aging Neurosci., vol. 6, p. 74, Jan. 2014.
4. P. Subramanya and S. Telles, “Changes in midlatency auditory evoked
potentials following two yoga-based relaxation techniques.,” Clin. EEG
Neurosci., vol. 40, no. 3, pp. 190–5, Jul. 2009.
5. P. Subramanya and S. Telles, “Performance on psychomotor tasks
following two yoga-based relaxation techniques.,” Percept. Mot. Skills, vol.
109, no. 2, pp. 563–76, Oct. 2009.
A61
Withdrawn
A62
EnkephaloVision: fast dynamic EEG analysis in combination with
eye tracking for efficacy testing of plant-derived and low triturated
homeopathic drugs.
Wilfried Dimpfel (
[email protected])
Justus-Liebig-University Giessen, Giessen, Hessen, 35390 Germany
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A62
Efficacy testing of plant-derived and homeopathic drugs still remains a
challenge in pharmacology. In the past several neurophysiological techniques have been successfully applied. However, interpretation of spectral
power values with respect to different brain regions is contradictory. Conventional quantitative EEG analysis uses averaged data from epochs of 2
or 4 s. Analysis of shorter epoch length of 364 ms has been achieved by
definition of specific frequency ranges [1]. Surprisingly, focal spectral
power within these short periods reached tremendous values (up to
9000 %) at single brain regions when compared to the average of other
assessed regions (global median) [2]. In order to learn more about these
short periods of high electric activity, EEG analysis was combined with
eye tracking. The eye tracking software served to present different cognitive and emotional audio-visual challenges in series. Synchronization of
the gaze overlay video from the eye tracking with screen capture of
the online quantitative EEG analysis was achieved by starting the recording with a gong. The combined technology has been published
[3]. Synchronized scenes were evaluated before and after intake of the
preparations. In the presence of cognition activating drugs (i.e. Zembrin®) more flashing of delta (1.375 - 4.125 Hz) and theta spectral power
(4.125 - 6.875 Hz) was observed in frontal brain in comparison to placebo during performance of psychometric testing. In the presence of
calming drugs (i.e. plant-derived drug Pascoflair®) more flashing of
alpha1 spectral power (6.875 - 9.625 Hz) was recognized in comparison
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
to placebo. The same increase of spectral alpha1 power was detected
after intake of 6 homeopathic Calmvalera Hevert tablets at a time. Since
about 3 pictures per second are difficult to follow, slow motion videos
will be presented. Finally, averaged data were fed into a discriminant
analysis. Comparison of several plant-derived and homeopathic drugs
with each other revealed for example projection of data from 3 calming
drugs in close vicinity to each other.
References
1. Dimpfel, W., Hofmann, H-C. (2014) Neurocode-Tracking Based on Quantitative Fast Dynamic EEG Recording in Combination with Eye-Tracking.
World Journal of Neuroscience 4, 106–119.
2. Dimpfel, W., Chiegoua Dipah, G.N., Gericke, N. (2016) EnkephaloVision:
Anatomical Functionality Indicated by Ultrashort Transient Regional EEG
Spectral Power Changes during Cognitive and Emotional Challenges.
World Journal of Neuroscience, 6, 90–108.
3. Dimpfel, W. (2015) Drug Discovery and Translational Medicine Based on
Neurophysiological Techniques. A holistic approach to saving animals.
Verlag Books on Demand, Norderstedt, Germany.
A63
Quantitative EEG assessment of students with ADHD undergoing
neurofeedback training
Caroline Dupont1,2, Brendan Parsons1, Hélène Brisebois2, Andrea Szabo2
1
Département de psychologie, Université de Montréal, Montréal, Canada;
2
Centre Alpha Neuro, Collège Montmorency, Laval, Canada
Correspondence: Caroline Dupont (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A63
Several studies have demonstrated abnormalities in quantitative electroencephalogram (qEEG) in children and adults with ADHD. Based
on these findings, neurofeedback training (NFT) has emerged has a
new treatment option for ADHD. In this preliminary study, qEEG was
used to assess the efficacy of NFT training for college students with
ADHD. Participants received computer attention training intervention
using NFT two times a week over a period of four months. A group
of college students with ADHD who did not undergo NFT training
was used as a control group. Brain activity was measured using qEEG
prior to, midway through, and post NFT training. ADHD behavioral
symptoms were also assessed pre- and post- training using the Conners’ Adult ADHD Rating Scale (CAARS-S:L) and the IVA-2. Changes in
qEEG were detected following NFT. Significant changes in restingstate brain activity were observed in the experimental group. Participants who underwent training demonstrated significant decreases in
absolute power across a wide spectrum of frequency bands (delta,
theta, alpha and beta) as well as a relative decrease in alpha activity
and increase in delta and beta activity. In order to identify if anomalous patterns of brain activity were related to symptoms of ADHD,
neuroelectric measures were compared to behavioral measures.
Changes in neural activity in the experimental group correlate with
improvements in ADHD symptoms. Although further research is warranted to determine the exact impact of NFT on the neural correlates
of ADHD, these preliminary findings suggest that it might be a promising cognitive training treatment for students with ADHD.
Keywords
qEEG, neurofeedback, ADHD, ADD
A64
Improving drug discovery using brain oscillations as biomarkers
for movement disorders
V Duveau, B Pouyatos, R Maury, B Mandé-Nidergang, C Bouyssières, C
Roucard, Y Roche
SynapCell SAS, Bâtiment Biopolis, 5 avenue du Grand Sablon, 38700 La
Tronche, France
Correspondence: V Duveau (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A64
Movement disorders represent a group of neurological syndromes
characterised by an alteration of voluntary and/or automatic
Page 24 of 34
movements. Here, we focused on Parkinson’s disease (PD) and essential tremor (ET), which are the most common forms of movement
disorders.
Motor symptoms of Parkinson’s disease result from a dysfunction of
cortico-basal ganglia circuits mainly due to dopaminergic neurons
death in the substantia nigra pars compacta. A hypersynchronization
of beta frequency oscillatory activity in these circuits has been described in both patients and animal models of the disease.
Essential tremor (ET) is characterized by the symptom of action
tremor (which intensifies when the affected muscles are used). ET
typically involves a tremor of the arms, hands or fingers. The
classically-used animal model of ET is generated by the administration of the beta-carbolin harmaline in mice. Harmaline induces action
tremors lasting several hours and the classical read-out is the recording of behavioural tremor frequency that occurs between 8 to 10Hz.
The aim of this poster was to provide two examples of the use of
brain oscillations in preclinical drug development for movement disorders. Here, 1) we assessed the use of aberrant cortical oscillations
in the unilateral 6-OHDA injected rat as translational biomarkers for
drug development in PD, and 2) studied the effect of harmalineinduced tremor on cortical and cerebellar oscillatory activities. The
sensitivity of these functional biomarkers was challenged with the
reference drugs for each pathology.
In the 6-OHDA rat model of PD, we found a prominent beta band
(~30Hz) in the motor cortex, which was inexistent in control Sprague–
Dawley rats. Acute injection of the dopaminergic receptor agonist LDOPA (6 and 20 mg/kg) induced body rotations along with a significant
reduction of the beta band. This treatment also induced a prominent
80-100Hz gamma increase. By contrast, the D2/D3/D4 agonist ropinirole at 0.2, 0.4, and 0.8 mg/kg also decreased the beta band but caused
only a slight gamma band increase.
We found that administration of harmaline (10-20-30 mg/kg) in male
C57BL/6 J mice dose-dependently increased the cortical and cerebellar power in a wide 15-60Hz frequency range, along with action
tremors. Pre-treatment with 20 mg/kg propranolol, one of the firstline medications used in ET patients attenuated the tremors and decreased the 35-60Hz range.
In this study, we identified aberrant EEG oscillations in two rodent
models of movement disorders. These oscillations and their pharmacological modulation may represent predictive biomarkers for the
identification, selection and validation of new therapeutics in movement disorders.
A65
Telemetric electroencephalography (EEG) and in vivo microdialysis
to study dopaminergic hyperactivity in freely moving rats
Boris Ferger, Patrizia Voehringer
CNS Diseases Research, Boehringer Ingelheim Pharma GmbH & Co. KG,
Biberach/Riß, Germany
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A65
Dopamine is a key regulator of cognition, mood, reward and movement in the human and rodent brain. The dopamine homeostasis is
tightly controlled by the dopamine transporter (DAT), which is a target for addictive drugs (such as cocaine and amphetamine), and
therapeutic antidepressants.
The present study was designed to investigate the effects of cocaine in
freely moving rats using telemetric electroencephalography (EEG) to
monitor a hyperdopaminergic state. Additionally, in vivo microdialysis
in the nucleus accumbens shell was carried out to measure extracellular
cocaine levels and dopamine itself by LC-MS-MS and HPLC coupled to
electrochemical detection. Behaviour was assessed by an automated
motor activity system using light beam interruptions.
Cocaine (5, 10 and 15 mg/kg, i.p.) dose dependently induced an increase in motor activity, which reached its maximum level after
20 min and lasted for 90 min. In addition, cocaine appeared to affect
the EEG power spectrum, increasing gamma frequency band power
up to 60 min after administration, whilst causing a decrease of power
in delta, theta, alpha, and beta frequencies. Maximum cocaine levels
measured from the dialysates appeared 30 min after dosing
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
(300 nmol/l) and extracellular dopamine levels showed a peak
concentration at 30 min and then returned to basal levels
120 min later.
In conclusion, these results indicate that cocaine induces an increase in dopaminergic transmission in the nucleus accumbens
shell, and as expected, produces hyperactivity. The effect observed on the EEG frequency bands and in vivo microdialysis
could serve as a physiological biomarker of target engagement
studies and to set up a PK-PD relationship in drug discovery
research.
A66
Effects of clozapine on auditory steady-state response in
schizophrenia
Inga Griskova-Bulanova1, Sigita Melynyte1, Kastytis Dapsys2, Aleksandras
Voicikas1
1
Department of Neurobiology and Biophysics, Vilnius University, Vilnius,
Lithuania; 2Republican Vilnius Psychiatric Hospital, Vilnius, Lithuania
Correspondence: Inga Griskova-Bulanova (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A66
Auditory steady-state responses (ASSR) provide a non-invasive
technique to assess neural synchrony at a particular frequency.
Attenuated phase-locking (PLI) of ASSRs in gamma frequency
range is observed in schizophrenia and in animal models for
psychosis [1]. State-sensitivity of 40 Hz ASSRs has been shown for
schizophrenia, where PLIs increased with eyes closure in patients
[2]. The effect of clozapine, which is prescribed in cases of
treatment-resistant schizophrenia, on ASSR in humans is not clear.
The aim of this study was to evaluate the effect of clozapine
use on phase-locking of 40Hz ASSR and state-sensitivity in
schizophrenia patients.
48 male patients with schizophrenia (according to ICD-10 criteria)
were recruited from the in-patients of Republican Vilnius Psychiatric Hospital. Patients were divided into two groups: (1) resistant
to standard antipsychotic medication and treated with clozapine
(Cloz, n = 23); and (2) responsive to standard antipsychotic
treatment (NCloz, n = 25). ASSRs to click stimuli at 40Hz were recorded using 9 channels in eyes open and eyes closed conditions, with 60 stimuli presented binaurally per condition. After
conventional cleaning procedures, epochs of 700 ms were created starting at 100 ms prior to the stimulus onset and lasting
for 600 ms post-stimulus. ASSRs were analyzed from Cz location,
showing maximal activity. Mean phase-locking index (PLI) within
38-42Hz window was calculated for 100 ms bins and subjected
to RM-ANOVA with time bin and task as within-subjects factors
and group as a between-subjects factor.
Significant interaction of condition (eyes open vs eyes closed) and
group (Cloz vs NCloz) factors (p = 0.038) was observed. This suggests
that in Cloz group subjects tended to have lower PLIs in open eyes
(p = 0.08), which increased with eyes closure (p < 0.001). In NCloz
group, PLIs did not change with eyes closure (p > 0.05).
Our data propose that state-sensitivity of 40 Hz ASSRs vary
depending on the treatment in patients with schizophrenia,
subject receiving clozapine showing response increase with
eyes closure in contrast to those on standard antipsychotic
treatment.
Competing interests
The author declare that they have no competing interests
Research was supported by the grant MIP-009/2014 from Lithuanian
Research Council.
References
1. O’Donnell BF, Vohs JL, Krishnan GP, Rass O, Hetrick WP, Morzorati SL. The
auditory steady-state response (ASSR): a translational biomarker for
schizophrenia. Suppl Clin Neurophysiol. 2013;62:101–12.
2. Griskova-Bulanova I, Dapsys K, Maciulis V, Arnfred SM. Closed eyes condition increases auditory brain responses in schizophrenia. Psychiatry Res
Neuroimaging. 2013;211(2):183–5.
Page 25 of 34
A67
Neuro-Cardiac-Guided TMS (NCG TMS): a new and cost-effective
method for accurately localizing the DLPFC in the treatment of
depression
Tabitha Iseger1,2 & Martijn Arns1,2,3
1
Dept. of Experimental Psychology, Utrecht University, Utrecht, The
Netherlands; 2Research Institute Brainclinics, Nijmegen, The Netherlands;
3
neuroCare Group, Munich, Germany
Correspondence: Tabitha Iseger (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A67
Background
The efficacy of rTMS in the treatment of major depressive disorder
(MDD) has been well established in recent years. Most studies to
date have employed the ‘5-cm’ rule for targeting stimulation of the
Dorsolateral Prefrontal Cortex (DLPFC). New variations and improvements of this targeting technique include a ‘6-cm’ rule, the Beam-F3
method, and neuronavigated rTMS. Furthermore, it has been proposed that the efficacy of rTMS in MDD is more related to stimulating the area that is functionally connected to the subgenual anterior
cingulate cortex (sgACC) rather than to specific cortical areas (Fox
et al., 2012). Therefore, we set-out to develop and test a new method
that employs knowledge about the functional role of the sgACC to
establish in real time if the right cortical area is targeted.
Method
Several studies have shown that areas in the ventromedial prefrontal
cortex are involved in parasympathetic regulation such as heart rate
and respiration, and that neurostimulation of these areas led to heart
rate decreases (Makovac et al., 2016), most likely through connectivity with the nervus vagus. Therefore, based on the notion that rTMS
aims to transsynaptically stimulate the sgACC, we used electrocardiogram (ECG) R-peak triggered single pulse TMS to various frontal
locations to establish the location that most consistently resulted in
a lengthening of the R-R latency (reflective of a heart rate deceleration). This method of Neuro-Cardiac-Guided TMS or NCG TMS thus
could be the equivalent of what the Motor Threshold is for the motor
system, but then for the DLPFC with heart rate as an output.
Results
First preliminary results using a burst of 10 Hz TMS stimulation demonstrated that in a subject with a relatively large head circumference,
no response was found at the ‘5 cm’ site (corresponding to FC4 in
this subject), whereas the F4 location did result in a consistent heart
rate deceleration. More data are currently being collected using a single pulse R-peak triggered approach and data will be presented. This
method is pending for patent. Dutch Patent office: P100241NL00
Conclusions
In the treatment of MDD, Neuro-Cardiac-Guided TMS has the potential to become the equivalent of the ‘motor threshold’ for the DLPFC,
and thereby would be a cost-effective and easy to use method for localizing the right stimulation target in the treatment of MDD, and
also serve as a real-time control of adequate coil contact in patients
undergoing rTMS treatment.
A68
Electroencephalogram connectivity in frontal networks to predict
outcome of electroconvulsive therapy in major depressive disorder
Alexandra Kirsten, Sebastian Olbrich
Department of Psychiatry, Psychotherapy and Psychosomatics, University
of Zurich, Zurich, Switzerland
Correspondence: Alexandra Kirsten (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A68
Background
Major depressive disorder (MDD) is a common and potentially lethal
disorder affecting up to 14 % of all persons worldwide. However, 1/3 to
2/3 of patients are non-responders to first line therapy [1]. Even the
electroconvulsive therapy (ECT) as the option of choice in therapyresistant MDD still shows a high proportion of non-responders [2]. Due
to the invasive nature of the ECT it would be desirable to know which
subjects are likely to respond. In case of a predicted non-response to
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
ECT, e.g. by means of electrophysiological electroencephalogram (EEG)
parameters, other therapies of MDD (e.g. augmentation, polypharmacy
etc.) could be chosen.
Methods
In this study, we retrospectively analysed two minute resting state
EEG from patients with MDD who underwent ECT (4–12 sessions with
3/week) between 2005–2015 at the University Hospital of Zurich. Following several lines of evidence, we hypothesized altered non-linear
connectivity in frontal networks including subgenual-, dorsolateraland medio- prefrontal cortices being predictive for treatment outcome. Symptom severity and response/remission rates were assessed
using the Global Clinical Impression (GCI) rating scale. Source estimates and connectivity measures were mapped using Low Resolution Brain Tomography (LORETA).
Results
Responders in comparison to non-responders showed a significant
stronger non-linear connectivity in the frontal network within the EEG
delta, alpha 1 and beta 1 frequency bands, while connectivity was
weaker in theta, alpha 2, beta 2 and gamma frequency bands. Additionally, there were several non-significant correlations (from r = .15.20) between symptom change and source estimates with e.g. a low
midline theta-activity being associated with response to ECT.
Conclusions
Pre-treatment EEG-connectivity in frontal networks seems to have a
predictive value for the efficacy of ECT treatment. Prospective trials
and larger study groups are needed to further validate these markers
and pave the way for possible usage in the clinical context.
Trial registration
Project ID: 2016–00562, Swissethics
No competing interests
References
1. Bromet E, Andrade LH, et al. Cross-national epidemiology of DSM-IV major
depressive episode. BMC Med. 2011 Jul 26;9:90. DOI: 10.1186/1741-7015-9-90
2. Dierckx B, Heijnen WT, et al. Efficacy of electroconvulsive therapy in
bipolar versus unipolar major depression: a meta-analysis. Bipolar Disorders. 2012 Mar 14, Issue 2,146–150. DOI: 10.1111/j.1399-5618.2012.00997.x
A69
Modulation of the serotonin system in an animal model of
psilocin-induced psychosis: a network clustering approach
Vlastimil Koudelka1, Filip Tylš1,2, Čestmír Vejmola1,2, Lukáš Kadeřábek1,2, Václava
Piorecká1,3, Tomáš Novák1,2, Martin Brunovský1,2 & Tomáš Páleníček1,2
1
National Institute of Mental Health, Topolová 748, 250 67, Klecany,
Czech Republic; 23rd Faculty of Medicine, Charles University in Prague,
Prague, Czech Republic; 3Faculty of Biomedical Engineering, Czech
Technical University in Prague, Prague, Czech Republic
Correspondence: Vlastimil Koudelka (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A69
Introduction
The present contribution deals with a particular study on animal
model of psilocin-induced psychosis. QEEG methods addressing brain
activity under certain set of conditions are usually based on bottomup strategy preserving the low-level information e.g. coherence between two electrodes within particular frequency band at certain
time after administration of a specific drug. Unfortunately, this approach leads to a combinatorial explosion if the effects of more
drugs and their combinations are to be analyzed. This phenomenon
makes data difficult to interpret. Here, we propose a way towards
top-down strategy based on capturing an interpretable substance
fingerprints. We show that unique functional brain clusters coherently modulated by a particular substance are embedded in multidimensional space of coherences and can be extracted by appropriate dimensional reduction technique [1].
Methods
The proposed technique takes coherences from 36 electrode pairs
calculated in six discrete frequency bands (1-40Hz) at four specific
time intervals (base line record, 20–30, 50–60, and 80–90 min post
Page 26 of 34
administration) and returns coherent topographic clusters. Our approach can be described in five following steps:
Coherence partial differences are calculated to extract functional
changes between time intervals.
Coherence differences are processed by t-Distributed Stochastic
Neighbor embedding (t-SNE) [2] to reduce data dimensionality on
one hand and encode the original data structure on the other hand.
The silhouette clustering criterion is employed to determine a number of clusters in data [3]
The k-means algorithm categorizes data into clusters determined in
step 2 and 3.
Obtained electrode pair clusters are visualized in topographic view.
Results
Psilocin clearly shows four functional clusters which are precisely
symmetric in topographic view and which exhibit a global maximum
of clustering criterion. In similar way, 5HT2A antagonist MDL100907,and clozapine result in three clusters. This is in contrast with
saline solution exhibiting no clustering and no global extremes of
clustering criterion. Generally, all antagonists in combination with
psilocin lead to less or no clusters.
Conclusions
The proposed technique is capable to contrast long term dynamics
of coherences and find functional brain structures coherently modulated by a particular drug. This allows us to further study the mechanism behind the psilocin induced functional disconnection – the
functional changes are specifically organized. All antagonists seem to
compensate the psilocin induced organization. Our next step is to
apply the technique in human psilocybin model of psychosis and
search a new translation bridge between animal and human models.
This study was supported by project “National Institute of Mental
Health (NIMH–CZ), number ED2.1.00/03.0078 and the grant AZV from
MHCR no. 15-29370A.
I declare no conflict of interests.
References
1. Birjandtalab, J., Pouyan, M. B., & Nourani, M. (2016, February). Nonlinear
dimension reduction for EEG-based epileptic seizure detection. In 2016
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) (pp. 595–598). IEEE.
2. Maaten, L. V. D., & Hinton, G. (2008). Visualizing data using t-SNE. Journal
of Machine Learning Research, 9(Nov), 2579–2605.
3. Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation
and validation of cluster analysis. Journal of computational and applied
mathematics, 20, 53–65.
A70
Clonidine Augmentation Therapy in Schizophrenia “CATS-Study”:
a promising new treatment strategy in resistant schizophrenia
Caitlyn Kruiper, Iris E Sommer, Bob Oranje
Dept. of Psychiatry, Brain Center Rudolf Magnus, University Medical
Center Utrecht, Utrecht, the Netherlands
Correspondence: Caitlyn Kruiper (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A70
Background
Deviations in basic information processing, such as sensory gating,
are thought to underlie cognitive deficits in schizophrenia. Treatment
with the current first- and second-generation antipsychotics show
almost no improvement in these early information processes. In parallel, there is little or no success in treating cognitive deficits with
these drugs. In a recently conducted pilot-study from our laboratory
we found that administering a single dose of clonidine, a noradrenergic α2A-receptor agonist, restored sensory gating in patients with
schizophrenia to a level that no longer differed from an age and
gender matched control group. It is expected that improvement of
early information processing leads to improvement in cognition.
Goal
Improving currently available antipsychotic medication by normalizing
early information processing.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Methods
Randomized Clinical Trial (RCT), conform to a randomized, balanced
placebo-controlled design with two arms: in condition 1, patients (n =
25) will receive 6 weeks of additional clonidine treatment to their
current medication, in condition 2, patients (n = 25) will receive 6 weeks
of additional placebo treatment to their current medication. In addition,
25 age and gender matched healthy subjects will function as controls.
Primary outcome is change in symptom severity, expressed as a
change in total score on the Positive and Negative Symptom Scale
(PANSS) from baseline to end of the 6-week treatment. Secondary outcomes are changes in cognitive functioning (measured through the
Brief Assessment of Cognition in Schizophrenia; BACS and Cambridge
Neuropsychological Test Automated Battery; CANTAB), change in GAF
(global assessment of functioning) scores and the measurement of various psychophysiological parameters of basic information processing,
such as P50 suppression, prepulse inhibition of the startle reflex (PPI)
and mismatch negativity (MMN).
Results
In line with our pilot-study it is expected that early information processing will improve. We predict that this will lead to an improvement in cognitive functioning after six weeks, which expectantly
leads to lower symptom severity and a better quality of life.
Trial Registration
EudraCT Number: 2014-003008-53
A71
Isolated epileptiform discharges: an electroencephalographic
abnormality underlying medication failure in autism spectrum disorder
Erin K MacInerney1, Ronald J Swatzyna1, Jay D Tarnow1, Robert P
Turner2, Alexandra J Roark1, and Gerald P Kozlowski3
1
Tarnow Center for Self-Management, Houston, TX, USA; 2Network
Neurology LLC, Charleston, SC, USA; 3Saybrook University, Oakland, CA,
USA
Correspondence: Erin K MacInerney (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A71
Background
Autism Spectrum Disorder (ASD) often presents a treatment challenge
due to the variety of symptoms that make each case unique. Medication prescribed to manage ASD associated symptoms such as anxiety,
depression, attention issues, and behavioral problems often fail to alleviate symptoms and can produce undesirable side effects. The question
is, why are the stimulants, selective serotonin reuptake inhibitors, and
antipsychotics prescribed to alleviate these issues [1] effective in some
patients but fail in others? The answer could be related to the increased
prevalence of electroencephalographic abnormalities in psychiatric patients [2]. The presence of isolated epileptiform discharges (IEDs) may
account for the treatment failure of these medications, especially antipsychotics, because these drugs lower seizure threshold, thus resulting
in increased epileptiform activity. Electroencephalography (EEG) can be
used to document the presence of IEDs that would otherwise go undetected. The purpose of the study was to reveal the prevalence of
IEDs in the ASD patient population and to demonstrate the usefulness
of the EEG for providing data to psychiatrists, neurologists, and developmental pediatricians to improve medication selection and outcomes
for patients with ASD.
Method
The data was obtained from an Institution Review Board approved
data archive from a multidisciplinary practice that treats a wide variety of refractory and neuroatypical patients. The study is comprised
of 140 non-epileptic children, adolescents, and adults diagnosed with
ASD, ages 4 to 25. A board certified electroencephalographer interpreted the EEGs in order to identify abnormalities.
Results
Of the 140 patients with ASD, 36.4 percent were found to have IEDs
after an EEG screening. Chi-square analysis found no significant difference between genders among the three age groups. The findings
indicate a high prevalence of IEDs among individuals with ASD.
Page 27 of 34
Conclusion
Our results find that compared to the healthy population, a large
number of patients with ASD have IEDs despite never having a
seizure. The findings support the use of EEG in children,
adolescents, and young adults with ASD, regardless of gender or
age. This is particularly true for those who have failed prior
medication attempts with stimulants, antidepressants, and/or antipsychotics. Utilizing the EEG for refractory cases in a psychiatric
practice allows for more individualized and precise medication
selection.
Consent to publish
This study does not contain details relating to individual participants.
Competing interests
The authors declare that they have no competing interests.
References
1. Oswald DP, Sonenklar NA. Medication use among children with autism
spectrum disorders. J Child Adolesc Psychopharmacol. 2007;17(3):348–
355. doi: 10.1089/cap.2006.17303.
2. Zimmerman EM, Konopka LM. Preliminary findings of single- and
multifocused epileptiform discharges in nonepileptic psychiatric patients.
Clin EEG Neurosci. 2014;45(4):285–292. doi: 10.1177/1550059413506001.
A72
Neuromodulation using maintenance TDCS optimized by qEEG
leads to full recovery from myalgic encephalopathy/chronic
fatigue syndrome: a case report
Shelly M Menolascino, Mitchell Belgin, Genevieve N Izzo, Lillian E Fisher
Washington Square Psychiatry & TMS, New York, NY, 10011, USA
Correspondence: Shelly M Menolascino
(
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A72
Background
A 61-year-old man with progressive myalgic encephalopathy/chronic
fatigue syndrome was referred for neuromodulation. His condition,
likely virally induced decades ago, was characterized by recurring periods of extreme fatigue, lasting months at a time. Severe fatigue
had become unrelenting over the prior two years, impairing many dimensions of his life. Multiple immunological and neurological workups were negative and fibromyalgia had been ruled out. Patient
failed many medically advised approaches, including antidepressants,
acupuncture and a gluten-free diet.
Methods
Genetic analysis suggested he would respond to dopaminergic
agents and to neuromodulation [1]. Trials of both amphetamines and
methylphenidate ultimately failed but modafinil 200 mg did provide
partial relief. Distance from the office precluded daily treatment with
repetitive transcranial magnetic stimulation (rTMS). Transcranial direct
current stimulation (tDCS) was chosen as a safe alternative feasible
treatment [2], allowing cumulative, ongoing treatment to target ongoing inflammation. We used neurophysiological state markers of
qEEG. Patient was trained with tDCS in the office and then treatment
was self-applied at home daily with anode on left dorsal-lateral prefrontal cortex (LDLPFC), cathode on right (RDLPFC), 2 mA/min,
20 min, 40 mA total dose, using 1.5” diameter electrode pads. After
four weeks, maintenance tDCS sessions were increased to twice daily
(6 AM and 12 Noon) and modafinil was lowered to 100 mg.
Results
Follow-up qEEG testing was done one year after the initial qEEG
when patient was in full recovery. Comparison of pre-treatment and
post-treatment qEEG findings show minor improvement in excessive
hypercoherent frontal alpha, a substantial 50 % drop in excess left
temporal alpha, and a normalization at the very low end of the qEEG
spectrum (less than 1 Hz). The patient noted: “[this treatment] has
given me sustained relief from a chronic fatigue condition from
which I’ve suffered throughout my adult life.”
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Conclusions
Maintenance treatment with daily tDCS and modafinil likely exerted
synergistic effects on the brain and immune system. The clinical recovery with notable improved sleep, energy, and ability to tolerate exercise
are most likely to be reflected in slow wave oscillation changes. This
case supports the need to look more closely at glial as well as neuronal
impact, perhaps expanding qEEG to include slow wave markers. Clinicians are eager to have qEEG personalized biomarkers to optimize adjunctive tDCS stimulation in chronic psychiatric and neurological
conditions, so often neuroinflammatory in nature [3].
Keywords
tDCS, myalgic encephalopathy, chronic fatigue syndrome, neuroinflammation, qEEG biomarker, personalized medicine
Consent to publish
Informed consent was obtained and the subject’s rights were protected.
Competing interests
No competing interests.
References
1. Oral A, Ilieva E, Küçükdeveci A, Varela E, Valero R, Verteanu M,
Christodoulou N. Generalised and regional soft tissue pain syndromes.
The role of physical and rehabilitation medicine physicians. The
European perspective based on the best evidence. A paper by the
UEMS-PRM Section Professional Practice Committee. Eur J Phys Rehabil
Med. 2013; 49: 535–549.
2. Bikson M, Grossman P, Thomas C, Zannou A, Jiang, J, Adnan, et al., Safety
of transcranial direct current stimulation: Evidence based update 2016.
Brain Stim. 2016; 9: 641–661.
3. Yokoi Y, Sumiyoshi T. Application of transcranial direct current stimulation
to psychiatric disorders: trends and perspectives. Neuropsychiatric
Electrophysiology. 2015;1:10. doi: 10.1186/s40810-015-0012-x.
A73
Changes of CNS- and ANS arousal levels following successful
antidepressant treatment with ketamine: a case series
Torsten Meyer, Annette Brühl, Sebastian Olbrich
Department for Psychiatry, Psychosomatics and Psychotherapy,
University of Zurich, 8032, Zurich, Switzerland
Correspondence: Torsten Meyer (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A73
Introduction
Ketamine has been established as an alternative in the treatment of
therapy-resistant major depressive disorder (MDD). Although response rates are reportedly high with up to 60-70 %, until now no
biomarkers that could predict treatment response exist. As a first
step, this case series aimed at identifying electrophysiological
markers of arousal that reflect alterations of ongoing neuronal activity after treatment with ketamine.
Methods
Two patients (one 65-year-old female, one 78-year-old male) with
therapy-resistant depression (> two treatment -approaches with
SSRIs, SNRIs or TCAs) were treated with ketamine infusion four times
respectively six times during three weeks. Resting state electroencephalogram (EEG) and electrocardiogram (ECG) were recorded at
baseline and after treatment with four/six time ketamine infusion.
Central nervous system (CNS) arousal was assessed using Vigilance
Algorithm Leipzig (VIGALL). Autonomous nervous system (ANS)
function was quantified using heart rate and heart rate variability
measures (HRV). Changes of depressive symptoms were assessed
using Hamilton Depression Rating Scale (HDRS).
Results
Both patients showed a marked decrease of depressive symptoms with
a drop from 28 HDRS to 9 HDRS after four ketamine infusions and from
20 HDRS to 6 HDRS after six infusions respectively. In parallel, both patients showed a decrease of CNS arousal levels as assessed by VIGALL
with increased amounts of low vigilance stages and decreased EEGalpha peak frequencies after therapy in comparison to baseline EEG recording. Further, both patients revealed a lowered ANS arousal level as
Page 28 of 34
assessed by a reduction of heart rate >24 h after the last ketamine infusion in comparison to pretreatment condition.
Discussion
Following the arousal framework in MDD with a suggested high EEGvigilance level in depression, the found decrease of CNS-arousal
could be interpreted as a consequence of the anesthetic, i.e. vigilance decreasing effect of ketamine. In contrast, the decrease of
heart rate remains elusive in the light of an initial increase of sympathetic function following infusion of ketamine. However, decrease of
CNS- and ANS arousal level could lead to less pronounced MDD related behavioral aspects such as withdrawal and sleep disturbances.
The predictive value of the EEG in ketamine treatment should be in
the focus of further prospective randomized studies.
Consent to publish
Written informed consent has been obtained by all patients prior to
publication.
Competing interests
The authors report no competing interests.
A74
ECoG spectral analysis of the Interaction between caffeine and
nicotine
Haitham S Mohammed1, Iman M Mourad2, Neveen A Noor2, Heba S
Aboul Ezz2 and Yasser A Khadrawy3
1
Biophysics Department, Faculty of Science, Cairo University, Giza, Egypt;
2
Zoology Department, Faculty of Science, Cairo University, Giza, Egypt;
3
Medical Physiology Department, Medical Division, National Research
Center, Giza, Egypt
Correspondence: Haitham S Mohammed (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A74
Caffeine and nicotine are the most consumed psychostimulants
worldwide. Although the electrophysiological effects of each drug
alone were studied extensively, the literature on the effects of
their combined treatments on brain electrical activity is scarce.
The present study aims to investigate the effects of the intraperitoneal injection of caffeine followed by the subcutaneous injection of nicotine after 1 h on electrical activity recorded from the
cortex of rats (ECoG). It was found that the successive injection
of caffeine and nicotine resulted in a significant increase in the
power of delta frequency band but a significant decrease in the
power of theta, beta-1 and beta-2. It was suggested that the caffeine and nicotine interaction could have an adverse effect by altering the cortical electrical activity that may indicate impair in
memory encoding.
A75
Dishabituation of central nervous system to tonic pain following
chiropractic care - a standardized low resolution brain
electromagnetic tomography (sLORETA) based study
Muhammad Samran Navid1,2,3, Dina Lelic1, Imran Khan Niazi3,4,5, Kelly Holt3,
Esben Bolvig Mark1, Asbjørn Mohr Drewes1,2, Heidi Haavik3
1
Mech-Sense, Department of Gastroenterology and Hepatology, Aalborg
University Hospital, 9000 Aalborg, Denmark; 2Department of Clinical Medicine,
Aalborg University, 9100 Aalborg, Denmark; 3Centre for Chiropractic Research,
New Zealand College of Chiropractic, Auckland 1060, New Zealand; 4Faculty
of Health & Environmental Sciences, Health & Rehabilitation Research Institute,
AUT University, Auckland 1010, New Zealand; 5Centre for Sensory-Motor
Interactions (SMI), Department of Health Science and Technology, Aalborg
University, 9100 Aalborg, Denmark
Correspondence: Muhammad Samran Navid (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A75
It has been demonstrated that after chiropractic spinal manipulation
neural plastic changes occur in different areas of the brain. Different
methods have been utilized to assess these changes, but the majority
of the measurements to find the involved brain areas have been indirect. The objective of this study was to determine the changes in brain
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
activity during tonic pain after single session of chiropractic care
in a sub-clinical pain population by using source localization of
the EEG.
Fifteen healthy volunteers (10 males, 32.1 ± 7.2 years) participated in
two experimental sessions on separate days; chiropractic or control
(sham) session in random order. The EEG was recorded continuously
using a 61-channel system before and after either intervention during 72 s of cold pressor test at 2 °C (left hand). The pain and unpleasantness ratings were obtained on two separate numeric scales
(range: 0 = no unpleasantness/pain to 10 = maximum unpleasantness/pain). The EEG was divided into 9 epochs (8 s each), which were
separated into four frequency bands: delta (1–4 Hz), theta (4–8 Hz),
alpha (8–12 Hz) and beta (12–32 Hz). Subsequently, standardized low
resolution brain electromagnetic tomography (sLORETA) was done
on these frequency bands.
In the control experiment, the brain activity decreased in all frequency bands (all p ≤ 0.05), whereas no change in activity was seen
after the chiropractic session (all p > 0.05). The decrease in activity in
the control arm was specifically seen in the limbic (delta), frontal
(theta) and temporal (alpha and beta) lobes The pain scores decreased in control arm (p < 0.05) whereas the unpleasantness scores
decreased for both interventions (all p < 0.05).
The decrease in brain activity in the control arm reflects central habituation which occurs due to repetitive painful stimulation. The lack
of this phenomenon in the chiropractic arm could imply that the
chiropractic care normalizes the central nervous system leading to
central dishabituation.
A76
Animal 3D brain-mapping
Václava Piorecká1,2, Vladimír Krajča1,2 & Tomáš Páleníček1,3
1
Faculty of Biomedical Engineering, Czech Technical University in
Prague, Prague, Czech Republic; 2National Institute of Mental Health
Topolová 748, 250 67, Klecany, Czech Republic; 33rd Faculty of Medicine,
Charles University in Prague, Prague, Czech Republic
Correspondence: Václava Piorecká (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A76
Introduction
To this date there are no standardized mapping methods that display animal cortical EEG on the brain surface. Therefore, this study
describes a 3D imaging method to be used for EEG mapping on the
surface of the rat brain. The aim of our study was to develop a software module and a standard for statistical brain mapping. Animal
EEG data recorded during behavioral activity and inactivity served as
a subject for analysis and brain mapping.
Methods
In this study we measured electrical activity of the rat brain. For imaging purpose, we used 3D brain model from atlas [1] and adjusted
it for our own module. We confirmed the validity of the 3D brain
model by comparing the dimensions of normalized brain scans of 9
rats of the Wistar strain typically used in our laboratories. We have
created a MATLAB module for brain mapping with the use of the rat
brain model and a possibility to place any number of electrodes on
the surface of the rat brain. The spline interpolation was used for
imaging activity on surface of the brain [2] and statistical brainmapping was used to compare the two example behavioral
conditions.
Results
The module was effectively used to display EEG activity on the 3D
surface and to display the statistical group differences in the sample
of the animal data between behavioral activity and inactivity. The
module can also compare data from individual measurement with a
group mean.
Conclusions
This study describes computation of splines interpolation curves that
are important for the brain mapping in rats. This approach will be
used for effective comparisons of brain activity of rats under various
conditions and with variable number and placement of cortical
electrodes.
Page 29 of 34
This study was supported by the project Nr. LO1611 from the MEYS
under the NPU I program, by project “National Institute of Mental
Health (NIMH–CZ) (grant number ED2.1.00/03.0078 from the
European Regional Development Fund), by Czech Technical
University research program SGS (SGS15/229/OHK4/3 T/17), MH CZ DRO („National Institute of Mental Health – NIMH) project nr.: 00023752
and PRVOUK34.
I declare no conflict of interests.
References
1. MAJKA, Piotr, Jakub M. KOWALSKI, Natalia CHLODZINSKA a Daniel K.
WÓJCIK. 3D Brain Atlas Reconstructor Service—Online Repository of
Three-Dimensional Models of Brain Structures. Neuroinformatics [online]. 2013, 11(4), 507–518 [cit. 2016-08-24]. DOI: 10.1007/s12021-0139199-9. ISSN 15392791. Online: http://link.springer.com/10.1007/
s12021-013-9199-9
2. PERRIN, F., J. PERNIER, O. BERTRAND a J.F. ECHALLIER. Spherical splines for
scalp potential and current density mapping. Electroencephalography
and Clinical Neurophysiology. 1989, 72(2), 184–187. DOI: 10.1016/00134694(89)90180-6. ISSN 00134694. Online: http://linkinghub.elsevier.com/
retrieve/pii/0013469489901806
A77
Effects of γ-aminobutyric acid-modulating drugs on resting state brain
oscillations and executive function in healthy volunteers: a pilot study
Sara de la Salle1, Joelle Choueiry2, Danielle Impey1, Dylan Smith2, Robert
Aidelbaum3, Ashley Baddeley4, Molly Hyde1, Brittany Duncan3, Justin
Piché1, Noreen Rahmani1, Vadim Ilivitsky5, Verner Knott1–5
1
School of Psychology, University of Ottawa, Ottawa, Ontario, K1Z 7 K4,
Canada; 2Cellular and Molecular Medicine, University of Ottawa, Ottawa,
Ontario, K1N 6 N5, Canada; 3Department of Psychology, Carleton
University, Ottawa, Ontario, K1S 5B6, Canada; 4Institute of Mental Health
Research, Ottawa, Ontario, K1Z 7 K4, Canada; 5Department of Psychiatry,
University of Ottawa, Ottawa, ON, K1N 6 N5, Canada.
Correspondence: Sara de la Salle (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A77
Background
Recent findings have suggested a relationship between abnormal γaminobutyric acid (GABA) function, disordered neuronal oscillations,
and impaired executive function in schizophrenia. Additionally, there
has been an increasing amount of interest in the therapeutic potential of these drugs in the treatment of this disorder. However, the
neural oscillations that underlie the effects of GABA-modulating
drugs on cognitive functioning require further work.
Objective
In an attempt to begin identifying which receptor subtypes may alter
the neural oscillations underlying executive function via selective
agonist actions, the study examined the effects of: a) a benzodiazepine drug with broad spectrum agonist actions at all GABA receptors
containing the α1, α2, α3, and α5 subunits, and the γ subunit (in
addition to the obligatory β subunit) and b) a drug with agonist actions at GABAB receptors. The objective of this pilot study was to
examine the effects of single doses of these GABA enhancing drugs
on resting state brain oscillations and executive function in healthy
volunteers stratified by executive function performance.
Method
30 participants were assessed in a randomized, double-blind, placebocontrolled design. Three minutes of eyes closed resting state brain oscillations were measured from 8 electrode sites in response to an acute
administration of lorazepam (Ativan®; 1.0 mg), a GABAA receptor positive allosteric modulator, and baclofen (Lioresal®; 10 mg), a GABAB receptor agonist. Executive function was assessed using the Groton Maze
Learning Task (GMLT) of the CogState Schizophrenia Battery.
Results
Spectral analysis revealed overall reductions in alpha and theta oscillations with the lorazepam treatment. Follow-up analyses indicated
that these reductions were in the better performing participants. Correlational analyses revealed that greater lorazepam-induced reductions in alpha and theta oscillations were associated with greater
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
lorazepam-induced cognitive impairment. Reduced theta at placebo
was also associated with worse performance. Additionally, smaller
theta activity at placebo was associated with greater lorazepaminduced cognitive impairment.
Conclusion
The results suggest that GABAA-modulated alpha and theta oscillations are involved in the neural underpinnings of executive
processing.
A78
EEG machine learning for enhanced monitoring of Alzheimer’s
disease and cholinergic modulation
Sonja Simpraga1, Ricardo Alvarez-Jimenez2, Huibert D. Mansvelder1, Joop
MA van Gerven2, Geert Jan Groeneveld2,3, Simon-Shlomo Poil1,4*, Klaus
Linkenkaer-Hansen1*
1
Dept. Integrative Neurophysiology, CNCR, Neuroscience Campus
Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;
2
Dept. Clinical Pharmacology, Centre for Human Drug Research, Leiden,
Netherlands; 3Dept. Neurology, VU University Medical Center,
Amsterdam, Netherlands; 4NBT Analytics BV, Amsterdam, Netherlands
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A78
*
These authors contributed equally
Scopolamine is a muscarinic acetylcholine receptor antagonist
(mAChR) that induces cognitive impairments resembling those
observed in Alzheimer’s disease (AD) and schizophrenia. It is used
in drug development to demonstrate the reversal of the temporary scopolamine-induced cognitive deficits by a cognition enhancing compound. However, there is an urgent need for biomarkers
that monitor therapeutic response; current biomarkers lack the
desired accuracy, because of the large variability in healthy subjects and the often subtle disease-related changes. In EEG, pathophysiology is often expressed in multiple ways. Here we show
that an integrative approach in which any biomarker that carries
complementary information about a disease or therapeutic intervention can result in an accurate diagnostic index for better decision making in clinical trials.
Recently, we showed that EEG biomarker integration improves the
prediction of conversion from mild cognitive impairment to
Alzheimer’s disease (AD) compared with a single-biomarker based
prediction [1]. The integrative biomarker index can be used for stratification of patients at recruitment in clinical studies and for documenting and quantifying effects of intervention. Here, we provide
additional proof-of-concept that EEG-based prediction can be improved with the integrative biomarker approach in clinical trials
where a drug is tested in a scopolamine challenge model in healthy
subjects.
For this purpose, we have developed an integrative EEGbiomarker index (mAChR index) that is optimally sensitive to the
CNS effects of scopolamine, to objectively determine whether
reversal of scopolamine effects by a cholinergic compound is
successful. The mAChR index yielded higher classification performance than any individual EEG biomarker with accuracy, sensitivity, specificity and precision ranging from 88–92 %. This
significantly outperforms the single-best EEG biomarker (relative
delta power). Validation on an independent dataset indicated the
robustness of the index. To support the validity of scopolamine
as a model for AD pathophysiology, we show that the mAChR
index discriminates healthy elderly from patients with AD.
We address this by using novel features of the Neurophysiological
Biomarker Toolbox (http://www.nbtwiki.net/), which employ datamining algorithms to combine the information from multiple biomarkers. Our results demonstrate that integrating information from
multiple EEG biomarkers can enhance the accuracy of identifying disease or drug intervention, which should be of interest to a wide
range of clinical trials.
Page 30 of 34
References
1. Poil SS, de Haan W, van der Flier WM, Mansvelder HD, Scheltens P,
Linkenkaer-Hansen K. Integrative EEG biomarkers predict progression to
Alzheimer’s disease at the MCI stage. Front Aging Neurosci. 2013; 5:58.
A79
Midfrontal theta dynamics reflect the ability to overcome
motivational biases in decision making
Jennifer C Swart1, Jessica I Määttä1, Roshan Cools1,2, & Hanneke EM den
Ouden1
1
Donders Institute for Brain, Cognition and Behavior, Radboud
University, Nijmegen, The Netherlands; 2Dept psychiatry, Radboud
University Medical Centre, Nijmegen, The Netherlands
Correspondence: Jennifer C Swart (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A79
Our motivations influence our actions in predictable ways. The promise of a reward promotes behavioural activation, while the threat of a
punishment context promotes inhibition. However, these motivational biases can at times be at odds with our goals. At such times,
we need to be able to suppress them, which has been suggested to
be implemented by the midfrontal cortex. We developed a novel
paradigm and computational models of behavior to disentangle the
impact of such motivational response biases, from the impact of
learning from reward and punishment outcomes. Participants (N =
34) completed this task while recording surface EEG. As expected,
cue valence strongly biased action. Midfrontal theta-band oscillatory
activity was increased in those trials, where the motivational response bias conflicted with the required response, particularly
when subjects successfully suppressed the motivational bias. We
will present further analyses to dissociate the role of midfrontal
cortex in learning from reward and punishment outcomes. This
work will allow us to characterize how motivations drive biases in
both choice and learning, and how we may learn to suppress
these when they are at odds with our instrumental goals. This
work has relevant implications for a range of psychiatric disorders
associated with a maladaptive reliance on impulsive, motivationdriven responding including addiction, impulse control and
ADHD.
A80
Neurophysiological substrates of memory processes: assessment
of glutamatergic and cholinergic modulation of sharp wave ripples
in rats
K Tahon1, DA Jackson1, S Jacob1,2, WH Drinkenburg1
1
Department of Neuroscience Discovery, Janssen Research &
Development, a Division of Janssen Pharmaceutica NV, B-2340, Beerse,
Belgium; 2Laboratory of Biological Psychology, University of Leuven, B3000, Leuven, Belgium
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A80
Sharp wave ripples (SPW-Rs) represent the most synchronous
population patterns observed in the mammalian brain and are
considered a cognitive biomarker for episodic memory and
planning. SPW-Rs occur during several off-line states of the
brain including non-REM sleep; are modulated by many neurotransmitter systems; and affect both cortical and subcortical
structures by their excitatory output. Selective disruption of
SPW-Rs impairs memory formation and pathological SPW-Rs
have been observed in rodent models for neurodegenerative
diseases. Quantification of these synchronous population patterns associated with memory processes is instrumental for a
better comprehension of neurodegenerative diseases as well as
for assessing the efficacy of novel pharmacological treatments.
The purpose of this study was twofold: first, to develop and val-
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
idate a novel computer-automated touchscreen-based spatial
search task assessing either working memory or memory consolidation in Long-Evans rats; second, to quantify SPW-Rs’ activity in this spatial search task during working memory or
memory consolidation combined with pharmacological glutamatergic and cholinergic modulation. For the working memory
component of the task, rats had to find a hidden location on
the touchscreen with either a short (2 s) or long (10 s) delay
between 10 consecutive trials with each delay having 4 different locations presented within one session. During these delays;
hippocampal SPW-Rs from the CA1 stratum pyramidal cell layer
were measured following each completed trial, using implanted
4-shank silicon electrodes. Here, SPW-Rs were measured when
the rat was moving at speeds of less than 4 cm/s, by use of
video monitoring to ensure events analyzed were associated
with quiescent periods only. Results indicate that Scopolamine
0.1 mg/kg but not 0.05 mg/kg decreased performance for the
long but not for the short delay. For the memory consolidation
component of the task, rats received 1-day or 4-day acquisition
session/s of a single hidden location with variable encoding
strength using few (<10) or many (>40) trials per session. Memory consolidation of the location was measured 24 h after acquisition
by the use of a probe trial. SPW-Rs were measured when the rats were
asleep both before and after the acquisition session. A differential effect
on encoding versus consolidation was addressed using pharmacological manipulation of glutamatergic and cholinergic systems. This
study reinforces the strength of combining neurophysiological and
cognitive behavioral assessment to further understand memory processes and effects of pharmacological treatments thereon.
A81
Glutamatergic deficit and negative symptoms: new evidence from
the ketamine model of schizophrenia
Stephanie Thiebes1, Gregor Leicht1, Stjepan Curic1, Saskia
Steinmann1, Nenad Polomac1, Iris Eichler2, Lars Eichler2, Christian
Zöllner2, Jürgen Gallinat3, Ileana Hanganu-Opatz4, Christoph Mulert1
1
Psychiatry Neuroimaging Branch, Department of Psychiatry and
Psychotherapy, University Medical Center Hamburg-Eppendorf,
20251Hamburg, Germany; 2Department of Anesthesiology, University
Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany;
3
Department of Psychiatry and Psychotherapy, University Medical
Center Hamburg-Eppendorf, 20251 Hamburg, Germany;
4
Developmental Neurophysiology, Institute of Neuroanatomy,
University Medical Center Hamburg-Eppendorf, 20251 Hamburg,
Germany
Correspondence: Stephanie Thiebes (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A81
Targeting the N-methyl-D-aspartate-receptor (NMDAR) is a major approach for treating negative symptoms of schizophrenia. The ketamine model of schizophrenia has the advantage of comprehensively
producing schizophrenia like symptoms such as positive, cognitive
and negative symptoms in healthy volunteers. The amplitude of the
Mismatch Negativity (MMN), a neurophysiological parameter related
to infrequent stimuli, is known to be significantly reduced in schizophrenic patients but also in healthy controls receiving ketamine [1,
2]. Accordingly, it was the aim of the present study to investigate
whether changes of MMN during ketamine administration are related
to the emergence of negative symptoms in healthy subjects.
Therefore, we examined the impact of ketamine on MMN
amplitudes and its sources (sources localization approach: low
resolution electromagnetic tomography (LORETA)) by means of
64-channel electroencephalography (EEG) recording during
performance of an auditory MMN paradigm and assessed the
psychopathological status using the Altered State of Consciousness (5D-ASC) Rating Scale and the Positive and Negative Syndrome Scale (PANSS). Twenty-four male, healthy volunteers
were measured with pharmacological EEG using a single-blind,
randomized, placebo-controlled crossover design.
Page 31 of 34
We identified significant changes of the MMN response, to both duration and frequency deviants, under ketamine condition as well as a
significant increase in all PANSS scores. Reductions of MMN amplitudes were significantly correlated with more pronounced negative
symptoms, assessed by the PANSS.
Accordingly, the MMN might represent a biomarker for negative
symptoms in schizophrenia related to an insufficient NMDAR
system and could be used to identify schizophrenia patients with
negative symptoms due to NMDAR dysfunction and thus to determine a maximal benefit of drugs modulating neurotransmission at the NMDAR.
Competing interests
The authors declare that they have no competing interests.
References
1. Shelley AM, Ward PB, Catts SV, Michie PT, Andrews S, McConaghy N.
Mismatch negativity: an index of a preattentive processing deficit in
schizophrenia. Biol Psychiatry. 1991; 30(10):1059–1062.
2. Umbricht D, Koller R, Vollenweider FX, Schmid L. Mismatch negativity
predicts psychotic experiences induced by NMDA receptor antagonist in
healthy volunteers. Biol Psychiatry. 2002; 51(5):400–406.
A82
Modulation of the serotonin system in an animal model of
psilocin-induced psychosis – time course of quantitative eeg
changes
Filip Tylš1,2, Čestmír Vejmola1,2, Lukáš Kadeřábek1,2, Václava Piorecká1,3,
Vlastimil Koudelka1, Tomáš Novák1,2, Tomáš Páleníček1,2
1
National Institute of Mental Health Topolová 748, 250 67, Klecany,
Czech Republic; 23rd Faculty of Medicine, Charles University in Prague,
Prague, Czech Republic; 3Faculty of Biomedical Engineering, Czech
Technical University in Prague, Prague, Czech Republic
Correspondence: Filip Tylš (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A82
Introduction
The serotonergic hallucinogen psilocybin and its active metabolite
psilocin nowadays receive a lot of attention in the scientific community as a research tool for modeling psychosis. First experiments
assessing brain activity after psilocybin administration in humans
using PET and fMRI found contradictory results [1,2]. More recently, a
study directly measuring neuronal activity using MEG confirmed
massive inhibition of brain activity [3]. The aim of our animal study
was to assess psilocin-induced changes in quantitative EEG (QEEG) in
rats in order to explore the role of different serotonergic receptors in
psilocin action.
Methods
The substances used were: psilocin (4 mg/kg s.c.), 5HT1A antagonist
WAY 100635 maleate (1 mg/kg s.c.), 5HT2A antagonist MDL-100907
tartarate (0.5 mg/kg s.c.), 5HT2C antagonist SB-242084 (1 mg/kg s.c.),
haloperidol 0.1 mg/kg s.c. and clozapine 5 mg/kg i.p. For EEG experiments, rats were stereotactically implanted with 12 active electrodes
onto the surface of the cortex under isoflurane anesthesia. EEG was
recorded in freely moving rats after one-week recovery from surgery.
EEG power spectra (local synchronization) and coherence (long projections) were subsequently analyzed comparing the drugs’ effect in
time (20–30, 50–60 and 80–90 min post administration) to the baseline record. To avoid moving artifacts and effects of behavior on EEG,
only EEG traces corresponding to behavioral inactivity were included
in the analysis.
Results
Psilocin generally decreased both EEG absolute spectral power and
EEG coherences. The changes in spectral power induced by psilocin
were normalized partially by all substances used, mainly in the lower
frequency bands. However, only 5HT1A and 5HT2A antagonists partially normalized the psilocin-induced decrease of EEG coherences.
The specific QEEG pattern of each substance and the temporal
dynamics of QEEG changes will be presented.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
Conclusions
Psilocin-induced changes in QEEG in rats are very similar to our recent human data with psilocybin and are in accordance with the
concept of psychosis as a disconnection syndrome. All the specific
5HT antagonists and both antipsychotic drugs specifically affected
the EEG spectral power induced by psilocin. Surprisingly, only 5HT1A
and 5HT2A antagonists were able to partially reverse psilocininduced disconnection. These results indicate that 5HT1A and 5HT2A
receptors might be involved in the increase of entropic brain activity
during psychedelic state as well as acute psychosis.
This study was supported by the grant IGA MHCR NT/13897, by
Charles University research program PRVOUK P34, by project
“National Institute of Mental Health (NIMH–CZ)”, grant number
ED2.1.00/03.0078, and by the European Regional Development Fund.
I declare no conflict of interests.
References
1. Vollenweider F.X., Leenders K.L, Scharfetter C., Maquire P., Stadelmann O.,
Angst J., 1997. Positron emission tomography and fluorodeoxyglucose
studies of metabolic hyperfrontality and psychopathology in the
psilocybin model of psychosis. Neuropsychopharmacol, 16(5):357–372.
2. Carhart-Harris R.L., Erritzoe D., Williams T., Stone J.M., Reed L.J., Colasanti
A., Tyacke R.J., Leech R., Malizia A.L., Murphy K., Hobden P., Evans J., Feilding A., Wise R.G., Nutt D.J., 2012. Neural correlates of the psychedelic state
as determined by fMRI studies with psilocybin. Proc Natl Acad Sci USA,
109(6):2138–2143.
3. Muthukumaraswamy S.D., Carhart-Harris R.L., Moran R.J., Brookes M.J., Williams T.M., Errtizoe D., Sessa B., Papadopoulos A., Bolstridge M., Singh K.D.,
Feilding A., Friston K.J., Nutt D.J., 2013. Broadband cortical
desynchronization underlies the human psychedelic state. J Neurosci,
33(38):15171–15183.
A83
Novel methods assessing electrophysiological alterations by 5HT2C receptor agonist CP-809,101 in sleep EEG and power spectral
activity
Peter Veselcic, Jennifer Mollon, Emmanouil Spanakis, Maria Vasileva,
Karsten Wicke
AbbVie Deutschland GmbH & Co.KG, Knollstrasse, 67061 Ludwigshafen,
Germany
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A83
The serotonergic 5-HT2C receptor is a key contributor to a variety
of medical conditions including psychiatric and neurological diseases. The development of therapeutic approaches at this receptor, with both, agonists and antagonists continues to be in focus
[1]. Using a novel wireless EEG device (Neural Activity Tracker-1)
and a novel in-house developed statistical algorithm we investigated electrophysiological changes in sleep structure and EEG
power spectral distribution caused by the highly selective 5-HT2C
receptor agonist CP-809,101.
In two independent studies, male Fischer rats with chronically implanted supracortical EEG-electrodes were treated with 10 mg/kg of
CP-809,101. In the 1st study, sleep structure changes in terms of total
sleep time, percent of time spent in different vigilance states, the
number of rapid eye movement (REM) episodes, and latency to first
sleep and REM episode were analyzed. Treatment with CP-809,101
led to attenuation of time spent in mild, deep, and REM sleep. It increased time spent in wake state and latency to first sleep and first
REM episode.
The 2nd study investigated power spectral distribution changes. A refined statistical method of baseline-adjusted power spectral changes
revealed an attenuation of delta and theta band by CP-809,101 in
comparison to vehicle recordings while maintaining the delta/theta
ratio. Our results clearly demonstrate that acute treatment with CP809,101 changes both sleep architecture and power spectral parameters in Fischer rats.
Page 32 of 34
5-HT2C agonists have been suggested to exhibit antidepressant-like
profile that fits to the sleep changes observed in our study. Further,
5-HT2C agonists have been reported to inhibit theta oscillation, desynchronizing the EEG and leading to shifts to lower frequencies
[2,3]. Yet, despite the inhibition of theta oscillation and
desynchronization of the EEG by CP-809,101, the ratio between
delta/theta revealed no changes underlying the wake-promoting
effects of CP-809,101.
Disclosures
All authors are employees of AbbVie. The design, study conduct, and
financial support for this research was provided by AbbVie. AbbVie
participated in the interpretation of data, review, and approval of the
publication.
References
1. Cunningham, K. A., Fox, R. G., Anastasio, N. C., Bubar, M. J., Stutz, S. J.,
Moeller, F. G., … & Rosenzweig-Lipson, S. (2011). Selective serotonin 5-HT
2C receptor activation suppresses the reinforcing efficacy of cocaine and
sucrose but differentially affects the incentive-salience value of cocainevs. sucrose-associated cues. Neuropharmacology, 61(3), 513–523.
2. Hajós, M., Hoffmann, W. E., & Weaver, R. J. (2003). Regulation of septohippocampal activity by 5-hydroxytryptamine2C receptors. Journal of
Pharmacology and Experimental Therapeutics, 306(2), 605–615.
3. Sörman, E., Wang, D., Hajos, M., & Kocsis, B. (2011). Control of
hippocampal theta rhythm by serotonin: role of 5-HT2c receptors. Neuropharmacology, 61(3), 489–494.
A84
P300 in pharmacological models of psychosis
Michaela Viktorinova1,2, Filip Tyls1,2, Tomas Novak1,2, Anna Bravermanova1,2,
Vlastimil Koudelka1,2, Martin Brunovsky1,2 & Tomas Palenicek1,2
1
National Institute of Mental Health Topolová 748, 250 67, Klecany,
Czech Republic; 23rd Faculty of Medicine, Charles University in Prague,
Prague, Czech Republic
Correspondence: Michaela Viktorinova (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A84
Background
P300 (P3) is an index of focal attention processes and memory updating. Impaired cognition is one of hallmark features of psychotic
disorders. Both psilocybin (5-HT2A agonist) and cannabinoids induce
acute transient psychotic symptoms and have previously been used
as putative models for psychosis. In order to investigate the extent of
cognitive disruption during psilocybin and cannabis intoxication, information processing was evaluated by means of both sensory event
related potentials (P2, N2) and cognitive potential P3.
Methods
Data from two separate studies are presented.
1) In a placebo-controlled design, 20 healthy adults were administered a dose of psilocybin per os (0,26 mg/kg) and placebo during 2
separate sessions.
2) In an ecologically valid model of cannabis intoxication, 34 recreational users, 32 chronic users and 30 healthy age- and gendermatched cannabis non-users were recruited. ERPs were recorded in a
sound-attenuated room with each participant lying down with their
eyes closed in a comfortable setting with two sitters (male and female)
being present for the whole time. An oddball paradigm with 120 frequent and 30 target tones presented binaurally in a pseudo-random
order was used. Data were acquired with a standard 32-channel digital
EEG amplifier BrainScope (unimedis, Prague) with 20 active scalp electrodes and oculogram according to the 10/20 system.
Results
Psilocybin: A repeated-measures ANOVA on latencies and amplitudes
of P2, N2 and P3 revealed significant effect of psilocybin only on P3
amplitude. Further analysis showed correlations between P3 amplitude and selected variables from objective and subjective rating
scales. Cannabis: While the groups did not differ in P3 latency or
amplitude, ANOVA revealed a main effect of group for P2
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
component with recreational users displaying smaller amplitudes
than healthy controls. Furthermore, N2 latency in recreational users
was shorter when compared to healthy controls.
Conclusion
In line with previous findings, psilocybin induced abnormalities in
higher-order cognition. Impaired processing is likely to be related to
heightened activity of the serotonergic system at the peak of psilocybin intoxication. Although P2 findings in cannabis model indicate
attention difficulties, non-significant P3 results need to be considered
as well and are discussed in light of the ecological validity of the
model.
This study was supported by the grant IGA MHCR NT/13897, by
Charles University research program PRVOUK P34, by project “National Institute of Mental Health (NIMH–CZ)”, grant number ED2.1.00/
03.0078, and by the European Regional Development Fund.
I declare no conflict of interests.
A85
Frontal alpha asymmetry in depression: fact or fiction?
A meta-analysis
Nikita van der Vinne1,2, Madelon A Vollebregt2,3, Martijn Arns2,4
1
Synaeda Psychomedical Center, Leeuwarden, The Netherlands;
2
Research Institute Brainclinics, Nijmegen, The Netherlands; 3Radboud
University Medical Centre, Donders Institute for Brain, Cognition and
Behaviour, Department of Cognitive Neuroscience, Nijmegen, The
Netherlands; 4Department of Experimental Psychology, Utrecht
University, Utrecht, The Netherlands
Correspondence: Nikita van der Vinne (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A85
In major depressive disorder (MDD) research, frontal alpha asymmetry (FAA) has frequently been reported as a potential discriminator between depressed and healthy individuals, although
contradicting studies and non-significant results have been published [1, 2]. Locating an MDD biomarker could benefit many
people, as MDD is predicted by the WHO to become the second
most debilitating disease by 2020. The aim of the current metaanalysis is to clarify the relationships between MDD and FAA further,
through analyzing new research from the last decade and put it in
perspective by comparing current and past findings (for example a
meta-analysis [1]).
Cohen’s d will be calculated from the means and standard deviations for FAA measures (subtracting mean log transformed left
midfrontal alpha from mean log transformed right midfrontal
alpha [ln(F4)-ln(F3)]), or a similar measure. Possible covariates including age, gender, handedness, year of publication, country of
residence, depression severity, medication, EEG recording length,
keeping eyes either open, closed or both, EEG reference, and
used alpha frequency will be explored. A study will be included
if the article (1) reports on both depressed and healthy individuals, (2) provides an FAA measure involving F3 and F4, and (3)
provides all data regarding above mentioned covariates (reported
either directly or obtained through contact with corresponding
authors).
Preliminary results of our currently ongoing meta-analysis will be presented. On the one hand, previous studies have reported relative
more left-sided alpha in MDD (sometimes only for higher frequency
alpha and not for every EEG montage). On the other hand, nonsignificant and even opposite results have been reported, showing
no baseline FAA differences between depressed patients and controls, or finding relatively more right-sided frontal alpha. Our expectation is that there will be no difference in FAA between MDD and
non-MDD groups, based on more recent studies reporting contradicting results, as well as today’s largest investigated sample regarding
this topic, the iSPOT-D study [2], showing non-significant results. If
non-significance is indeed demonstrated, the use of FAA as a
diagnostic tool can be questioned. Nevertheless, its contribution to
other applications (such as treatment prediction) could be further
explored.
Page 33 of 34
References
1. Thibodeau R, Jorgensen R, Kim S. Depression, Anxiety, and Resting
Frontal EEG Asymmetry: A Meta-Analytic Review. J Abnorm Psychol.
2006; 115;715–729.
2. Arns M, Bruder G, Hegerl U, Spooner C, Palmer D, Etkin A, Fallahpour K,
Gatt J, Hirshberg L, Gordon E. EEG alpha asymmetry as a gender-specific
predictor of outcome to acute treatment with different antidepressant
medications in the randomized iSPOT-D study. Clin Neurophysiol. 2016;
127:509–519.
A86
Neuropharmacological profile of selected areas responsible for the
inhibition of P50 wave: from the P50 wave to off-label treatment
of schizophrenia
Premysl Vlcek, Barbora Kohutova, Jakub Polak, Martin Brunovsky
National Institute of Mental Health, Klecany; The Department of Applied
Brain Electrophysiology (ABEP), Klecany, Czech Republic
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A86
Patients suffering from schizophrenia have been shown to exhibit impaired P50 ERP amplitude-reduction to the second (S2)
relative to the first (S1) of identical brief auditory stimuli. This
reduction is often mentioned in connection with the inability
to filter redundant sensory stimuli typically manifested as inability to gate neuronal responses related to the P50 wave [1,
2]. The key neuronal structure responsible for the sensory gating process is the hippocampus. Inhibition of redundant stimuli
in the hippocampus is affected via the release of glutamate
from excitatory pathways, which is controlled by GABAB receptors. It is closely connected with a physiological deficit of
hippocampal GABAergic interneurons, which demonstrates
neuropathological changes in schizophrenia. Several drugs are
able to improve sensory gating, the effect of which is explained by their ability to disinhibit GABAergic neurons in the
hippocampus. The effect of setrons may be an example of such
effective gabaergic interneurons disinhibition. This antagonist
of 5-HT 3 receptors increased (by disinhibition of gabaergic interneurons) release of acetylcholine, which by agonism of
alpha7 nicotinic receptors improved auditory gating [3]. Besides the hippocampus the prefrontal cortex is an important
neuronal part of the sensory gating. Patients with a prefrontal
damage fail to suppress irrelevant sensory information, which
leads to increased neural noise and inability to inhibit taskirrelevant information during behavioral tasks requiring performance over a delay. Some of the P50 source analysis leads
to the conclusion that while the temporal cortices are the
main generator of the P50 component, the prefrontal cortex
seems to be a main contributor to the process of sensory gating (P50 amplitude reduction) [4]. As in the case of the hippocampus, there are drugs that improve sensory gating by acting
on the prefrontal cortex. Clonidine acts as an agonist of α2A
noradrenergic receptors and has a proven restorative effect on
sensory gating. Stimulation of α2A noradrenergic receptors on
PFC spines by clonidine leads to strengthening of network connectivity, increase in neuronal PFC firing, and thus improves
PFC regulation of sensory gating [5]. The aim of our poster is
to interlink a pharmacological profile of neuronal areas that
are involved in the inhibition of P50 wave with clinical treatment of schizophrenia. We believe that the neuropharmacological aspects of P50 wave offer an interesting hypothesis
relating mainly to the pharmacological augmentation strategies. Some of them are suggested and explained further in
our poster communication.
This work was supported by the project „National Institute of Mental
Health (NIMH-CZ)“, under grant number ED2.1.00/03.0078, the
European Regional Development Fund, the Charles University
research program PRVOUK P34, and the travel grant of the Czech
neuropsychopharmacological society.
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):8
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2. Vlcek P, Bob P, Raboch J. Sensory disturbances, inhibitory deficits, and the
P50 wave in schizophrenia. Neuropsychiatr Dis Treat. 2014;10:1309–15.
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Page 34 of 34
(1,86) = 8.602, p = .004, d = −0.449), while data from participants
lacking the DRD4 7R genotype did not differ.
Conclusions
These results provide evidence that factors around birth influence
adult performance and may strengthen or weaken the risk to
develop attention related problems once already genetically at risk.
Results also further strengthen the hypothesis that a relationship between solar irradiation and ADHD exists, possibly mediated by the
dopamine DRD4 receptor.
References
1. Arns, M., van der Heijden K.B., Arnold L.E., Kenemans J.L. Geographic
variation in the prevalence of attention-deficit/hyperactivity disorder: the
sunny perspective. Biol psychiat. 2013 Oct 15;74(8):585–90.
2. Seeger, G., Schloss, P., Schmidt, M.H., Rüter-Jungfleisch, A., Henn, F.A. (2004).
Gene-environment interaction in hyperkinetic conduct disorder (HD + CD)
as indicated by season of birth variations in dopamine receptor (DRD4)
gene polymorphism. Neuroscience Letters, 366, 282–286.
A87
Dopamine under the influence of sunlight? Transitions in solar
irradiation explaining attentional performance in DRD4 7R carriers
Madelon A Vollebregt1,2, Martijn Arns1,3
1
Research Institute Brainclinics, Nijmegen, The Netherlands; 2Department
of Cognitive Neuroscience, Donders Institute for Brain, Cognition and
Behaviour, Radboud University Medical Centre, Nijmegen, The
Netherlands; 3Dept. of Experimental Psychology, Utrecht University,
Utrecht, The Netherlands
Correspondence: Madelon A Vollebregt (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A87
A88
A pilot study of sucrose-induced effect in resting alpha asymmetry
Grace Y Wang1, Lin Tiffany2, Nazimah Hamid2, Alex Sumich3
1
Division of Psychology, Auckland University of Technology, Auckland,
New Zealand; 2School of Applied Sciences, Auckland University of
Technology, Auckland,New Zealand; 3Division of Psychology, School of
Social Sciences, Nottingham Trent University, Nottingham, UK
Correspondence: Grace Y Wang (
[email protected])
Neuropsychiatric Electrophysiology 2016, 2(Suppl 1):A88
Background
Previous research suggests that high exposure to solar irradiation
has a preventive effect on the development of attention-deficit/
hyperactivity disorder (ADHD) [1]. Note that the Dopaminergic
DRD4 receptor is involved in phototransduction in the retina. Interestingly, being a DRD4 7R carrier while being born in spring and
summer has been demonstrated to result in a 2.8 higher likelihood
of developing hyperkinetic disorder, equivalent to ADHD [2]. These
findings suggested a possible gene X environment interaction between the DRD4 7R allele and season of birth. The current study focused on the influence of solar irradiation exposure around birth on
adult attentional performance.
Methods
We used an RDoC approach focusing on “inattention” operationalized
as false negative errors, i.e. missed targets, from two cognitive tasks;
the auditory oddball task and the continuous performance task.
DRD4 genotype was regarded a vulnerability to develop ADHD, i.e.
high inattention. We specifically aimed to test hypotheses that we
generated based on previous studies. We distinguished the solar irradiation at birth-month from the difference in the solar irradiation
between the month after birth and the month of birth to further
understand previous results. Data of 277 healthy adult participants
were extracted from the Brain Resource International Database. This
database contains data from multiple laboratories (New York, Rhode
Island, Nijmegen, Sydney, and Adelaide) creating variability in solar
irradiation data.
Results
Results showed an interaction between DRD4 genotype and transition in solar irradiation following birth on the number of inattention
errors made (F(1, 269) = 6.785, p = .010). More specifically, a one-way
ANOVA for the DRD4 7R carrier group showed a significant difference between positive and negative transition in solar irradiation
Background and aim
Prospective studies have linked sucrose consumption to weight gain
and obesity, which are in turn associated with the development of a
range of adverse health effects including diabetes and premature
cardiovascular disease, both identified as leading causes of health
loss in New Zealand and Europe. Recent work has also reported that
there are cognitive deficits induced by elevated intake of sugars.
There is the need to improve understanding of how the processes involved in the deterioration of cognitive functions and mechanisms
are modulated by the sucrose. The present study was to investigate
the effect of sucrose on resting EEG alpha asymmetry using EEG.
Methods
We recorded resting, spontaneous EEG from 64 scalp electrodes according to the international 10/20 system (NeuroScan, A/D rate: 1000 Hz)
while healthy volunteers (N = 10) were orally administered sucrose (with
1 % sweetness) and placebo solutions. The participants held these solutions in their mouth, still with eyes closed. EEG spectral indices from the
left and right frontal (F3, F4), central (C4, C3) and posterior regions (P4,
P3) of the scalp were extracted by a continuous wavelet transform and
normalised into spectral distribution in the alpha (8–12 Hz) band.
Sucrose-induced change in alpha asymmetry was analysed using ANOVA,
with conditions (sucrose, placebo), hemisphere (left, right) and regions
(frontal, central and posterior) as the within-subjects factors.
Results
Our results showed that there was no significant condition* hemisphere effect. However, a medium effect size (r = 0.33) may indicate
some effect which did not turn out to be significant due to the limited
sample size. A tendency for a reduced asymmetry value (i.e. F4-F3) was
observed when the group was exposed to sucrose.
Discussion
Our findings provide preliminary evidence of sucrose-induced change
in brain activity.