Papers by Jens Schwarzbach
Pharmacopsychiatry, May 23, 2023
Introduction There is a need for novel anxiolytics with improved side effect profiles compared to... more Introduction There is a need for novel anxiolytics with improved side effect profiles compared to benzodiazepines. A promising candidate with alternative pharmacodynamics is the translocator protein ligand, etifoxine. Methods To get further insight into its mechanisms of action and side effects compared to the benzodiazepine alprazolam, we performed a double-blind, placebo-controlled, repeated-measures study in 36 healthy male subjects. Participants were examined for trait anxiety and side effects and underwent repeated transcranial magnetic stimulation (TMS) assessments, including motor evoked potentials (MEP), short intracortical inhibition (SICI), intracortical facilitation (ICF), and cortical silent period (CSP). Results We observed attenuation of MEPs by alprazolam but not by etifoxine. SICI was not significantly affected by alprazolam or etifoxine. However, the response pattern indicated a lowered SICI threshold after the administration of etifoxine and alprazolam compared to the placebo. ICF and CSP were influenced by neither medication. Alprazolam led to higher sedation and subjective impairment of concentration compared to etifoxine. Individual anxiety trait scores did not affect TMS parameters. Discussion This study indicated a favorable side effect profile of etifoxine in healthy volunteers. Moreover, it revealed differential GABA-related effects on neuromuscular function by means of TMS. The side effects and TMS profile of etifoxine are compatible with the involvement of neurosteroidogenesis and a predominant α3 subunit modulation compared to alprazolam.
Molecular Psychiatry, Apr 20, 2022
Neuromodulation, Dec 1, 2019
Human Brain Mapping, 2019
Resting state fMRI is a tool for studying the functional organization of the human brain. Ongoing... more Resting state fMRI is a tool for studying the functional organization of the human brain. Ongoing brain activity at “rest” is highly dynamic, but procedures such as correlation or independent component analysis treat functional connectivity (FC) as if, theoretically, it is stationary and therefore the fluctuations observed in FC are thought as noise. Consequently, FC is not usually used as a single‐subject level marker and it is limited to group studies. Here we develop an imaging‐based technique capable of reliably portraying information of local dynamics at a single‐subject level by using a whole‐brain model of ongoing dynamics that estimates a local parameter, which reflects if each brain region presents stable, asynchronous or transitory oscillations. Using 50 longitudinal resting‐state sessions of one single subject and single resting‐state sessions from a group of 50 participants we demonstrate that brain dynamics can be quantified consistently with respect to group dynamics u...
Frontiers in Neuroimaging, Nov 30, 2023
Bullet points Local brain dynamics are consistent across scans. Four scans of five minutes each a... more Bullet points Local brain dynamics are consistent across scans. Four scans of five minutes each are enough to get highly reliable and consistent results.
The Journal of Neuroscience, Sep 5, 2012
The effects of transcranial magnetic stimulation (TMS) vary depending on the brain state at the s... more The effects of transcranial magnetic stimulation (TMS) vary depending on the brain state at the stimulation moment. Four mechanisms have been proposed to underlie these effects: (1) virtual lesion-TMS suppresses neural signals; (2) preferential activation of less active neurons-TMS drives up activity in the stimulated area, but active neurons are saturating; (3) noise generation-TMS adds random neuronal activity, and its effect interacts with stimulus intensity; and (4) noise generation-TMS adds random neuronal activity, and its effect depends on TMS intensity. Here we explore these hypotheses by investigating the effects of TMS on early visual cortex by assessing the contrast response function while varying the adaptation state of the observers. We tested human participants in an orientation discrimination task, in which performance is contingent upon contrast sensitivity. Before each trial, neuronal activation of visual cortex was altered through contrast adaptation to two flickering gratings. In a factorial design, with or without adaptation, a single TMS pulse was delivered simultaneously with targets of varying contrast. Adaptation decreased contrast sensitivity. The effect of TMS on performance was state dependent: TMS decreased contrast sensitivity in the absence of adaptation but increased it after adaptation. None of the proposed mechanisms can account for the results in their entirety, in particular, for the facilitatory effect at intermediate to high contrasts after adaptation. We propose an alternative hypothesis: TMS effects are activity dependent, so that TMS suppresses the most active neurons and thereby changes the balance between excitation and inhibition.
Frontiers in Neurology, Oct 11, 2018
Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central ner... more Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.
Human Brain Mapping, Jul 30, 2023
The complexity of our actions and thinking is likely reflected in functional brain networks. Inde... more The complexity of our actions and thinking is likely reflected in functional brain networks. Independent component analysis (ICA) is a popular data‐driven method to compute group differences between such networks. A common way to investigate network differences is based on ICA maps which are generated from study‐specific samples. However, this approach limits the generalizability and reproducibility of the results. Alternatively, network ICA templates can be used, but up to date, few such templates exist and are limited in terms of the functional systems they cover. Here, we propose a simple two‐step procedure to obtain ICA‐templates corresponding to functional brain systems of the researcher's choice: In step 1, the functional system of interest needs to be defined by means of a statistical parameter map (input), which one can generate with open‐source software such as NeuroSynth or BrainMap. In step 2, that map is correlated to group‐ICA maps provided by the Human Connectome Project (HCP), which is based on a large sample size and uses high quality and standardized acquisition procedures. The HCP‐provided ICA‐map with the highest correlation to the input map is then used as an ICA template representing the functional system of interest, for example, for subsequent analyses such as dual regression. We provide a toolbox to complete step 2 of the suggested procedure and demonstrate the usage of our pipeline by producing an ICA templates that corresponds to “motor function” and nine additional brain functional systems resulting in an ICA maps with excellent alignment with the gray matter/white matter boundaries of the brain. Our toolbox generates data in two different file formats: volumetric‐based (NIFTI) and combined surface/volumetric files (CIFTI). Compared to 10 existing templates, our procedure output component maps with systematically stronger contribution of gray matter to the ICA z‐values compared to white matter voxels in 9/10 cases by at least a factor of 2. The toolbox allows users to investigate functional networks of interest, which will enhance interpretability, reproducibility, and standardization of research investigating functional brain networks.
Many investigations into emotion processing contend that emotions can be reduced to a set of lowe... more Many investigations into emotion processing contend that emotions can be reduced to a set of lower dimensions (e.g., valence and arousal). Additionally, emotion dysregulation is associated with numerous psychiatric disorders, whose treatment(s) may require inspiration from personalized medicine. To translate emotion research to the clinical domain, one may therefore need to investigate at the individual level, employing datadriven methods and forgoing classical assumptions regarding emotions. To this end, we explored the relative structure of emotion information resulting from 85 participants organizing emotionally-charged images following their own emotional responses to the pictures. Using cluster analyses and multidimensional scaling, we investigated the underlying composition of individuals' emotion spaces. Hierarchical clustering revealed five subtypes that reflect differing layouts of the emotion space; multidimensional scaling of each subtype's representative emotion space demonstrated that, although valence explained the primary organization of all emotion spaces, arousal as a secondary explanatory variable played a reduced role differentially for the subtypes, suggesting intrinsic differences in emotion information processing. Such data-driven methods yield new, unbiased ways of studying emotions and may reveal limitations of classic models or idiosyncrasies of individuals, which can inform future neuroimaging research and offer new approaches for studying emotions and emotion dysfunctions in psychiatric disorders.
Human Brain Mapping
The complexity of our actions and thinking is likely reflected in functional brain networks. Inde... more The complexity of our actions and thinking is likely reflected in functional brain networks. Independent component analysis (ICA) is a popular data‐driven method to compute group differences between such networks. A common way to investigate network differences is based on ICA maps which are generated from study‐specific samples. However, this approach limits the generalizability and reproducibility of the results. Alternatively, network ICA templates can be used, but up to date, few such templates exist and are limited in terms of the functional systems they cover. Here, we propose a simple two‐step procedure to obtain ICA‐templates corresponding to functional brain systems of the researcher's choice: In step 1, the functional system of interest needs to be defined by means of a statistical parameter map (input), which one can generate with open‐source software such as NeuroSynth or BrainMap. In step 2, that map is correlated to group‐ICA maps provided by the Human Connectome P...
Many investigations into emotion processing contend that emotions can be reduced to a set of lowe... more Many investigations into emotion processing contend that emotions can be reduced to a set of lower dimensions (e.g., valence and arousal). Additionally, emotion dysregulation is associated with numerous psychiatric disorders, whose treatment(s) may require inspiration from personalized medicine. To translate emotion research to the clinical domain, one may therefore need to investigate at the individual level, employing data-driven methods and forgoing classical assumptions regarding emotions. To this end, we explored the relative structure of emotion information resulting from 85 participants organizing emotionally-charged images following their own emotional responses to the pictures. Using cluster analyses and multidimensional scaling, we investigated the underlying composition of individuals’ emotion spaces. Hierarchical clustering revealed five subtypes that reflect differing layouts of the emotion space; multidimensional scaling of each subtype’s representative emotion space d...
Right hand finger tapping performed for 10 sec at a rate of 3-4 taps per second alternating with ... more Right hand finger tapping performed for 10 sec at a rate of 3-4 taps per second alternating with a mean rest period of 25 sec (sd = 1.39) repeated for 20 blocks. Data acquisition and processing: Data for one participant was collected at the Stanford NIRS Lab [2,3] with an ETG-4000 Hitachi System. One 4x4 probe covered the motor cortex contralateral to the effector activated. We applied a bandpass filter (0.01 -0.5Hz). We examined 4 channels that showed the typical delayed hemodynamic response time-locked to stimulus presentation (peak around 8 sec). Two of them (channels 13 and 20) showed a decrease in the oxy-Hb component peaking at 1.5 sec, whereas in channels 10 and 9 the initial dip was absent. We used the slope of the timecourse of these respective concentration parameters as summary statistics. HbO and HbD (difference between oxy-and deoxy-Hb [4]) slopes were computed for 4 time windows of interest: from 0 to 2 sec in steps of 0.5 sec Classification analysis: We trained a line...
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Papers by Jens Schwarzbach