Cortical stimulation plays an important role in the study of epileptic seizures. We present a num... more Cortical stimulation plays an important role in the study of epileptic seizures. We present a numerical simulation of stimulation using optogenetic channels expressed by excitatory cells in a mean field model of the human cortex. Depolarising excitatory cells in a patch of model cortex using Channelrhodpsin-2 (ChR2) ion channels, we are able to hyper-excite a normally functioning cortex and mimic seizure activity. The temporal characteristics of optogenetic channels, and the ability to control the frequency of synchronous activity using these properties are also demonstrated. Optogenetics is a powerful stimulation technique with high spatial, temporal and cell-type specificity, and would be invaluable in studying seizures and other brain disorders and functions.
The role of extra-synaptic receptors in the regulation of excitation and inhibition in the brain ... more The role of extra-synaptic receptors in the regulation of excitation and inhibition in the brain has attracted increasing attention. Because activity in the extra-synaptic receptors plays a role in regulating the level of excitation and inhibition in the brain, they may be important in determining the level of consciousness. This paper reviews briefly the literature on extra-synaptic GABA and NMDA receptors and their affinity to anesthetic drugs. We propose a neural population model that illustrates how the effect of the anesthetic drug propofol on GABAergic extra-synaptic receptors results in changes in neural population activity and the electroencephalogram (EEG). Our results show that increased tonic inhibition in inhibitory cortical neurons cause a dramatic increase in the power of both δ- and α- bands. Conversely, the effects of increased tonic inhibition in cortical excitatory neurons and thalamic relay neurons have the opposite effect and decrease the power in these bands. Th...
Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severe... more Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and mult...
► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detec... more ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy e...
The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthe... more The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness.
Ketamine has been in clinical use for over half a century, yet its precise mechanisms of action r... more Ketamine has been in clinical use for over half a century, yet its precise mechanisms of action remain mysterious for the large part. Its hypnotic effects appear to be largely mediated by blockade of NMDA and HCN1 receptors, but cholinergic, aminergic, and opioid systems appear to play both a positive and negative modulatory role in both sedation and analgesia. Ketamine's effects in chronic pain, and as an antidepressant, far outlast the actual drug levels, and are probably mediated by a secondary increase in structural synaptic connectivity that is mediated by a neuronal response to the ketamine-induced hyperglutamatergic state.
Over 80% of the head injuries were due to road trauma. Over 60% occurred >30km from th... more Over 80% of the head injuries were due to road trauma. Over 60% occurred >30km from the first admission hospital, 35% were >60km away and 43% took more than 90 minutes to arrive in hospital. Helicopter transport was used for 34% of patients. Hypoxia was present in ...
The re-establishment of conscious awareness after discontinuing general anesthesia has often been... more The re-establishment of conscious awareness after discontinuing general anesthesia has often been assumed to be the inverse of loss of consciousness. This is despite the obvious asymmetry in the initiation and termination of natural sleep. In order to characterize the restoration of consciousness after surgery, we recorded frontal electroencephalograph (EEG) from 100 patients in the operating room during maintenance and emergence from general anesthesia. We have defined, for the first time, 4 steady-state patterns of anesthetic maintenance based on the relative EEG power in the slow-wave (,14 Hz) frequency bands that dominate sleep and anesthesia. Unlike single-drug experiments performed in healthy volunteers, we found that surgical patients exhibited greater electroencephalographic heterogeneity while re-establishing conscious awareness after drug discontinuation. Moreover, these emergence patterns could be broadly grouped according to the duration and rapidity of transitions amongst these slow-wave dominated brain states that precede awakening. Most patients progressed gradually from a pattern characterized by strong peaks of delta (0.5-4 Hz) and alpha/spindle (8-14 Hz) power ('Slow-Wave Anesthesia') to a state marked by low delta-spindle power ('Non Slow-Wave Anesthesia') before awakening. However, 31% of patients transitioned abruptly from Slow-Wave Anesthesia to waking; they were also more likely to express pain in the post-operative period. Our results, based on sleep-staging classification, provide the first systematized nomenclature for tracking brain states under general anesthesia from maintenance to emergence, and suggest that these transitions may correlate with post-operative outcomes such as pain.
The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are close... more The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are closely similar to those seen during slow-wave sleep, the deepest stage of natural sleep; both states show patterns dominated by large amplitude slow waves. Slow oscillations are believed to be important for memory consolidation during natural sleep. Tracking the emergence of slow-wave oscillations during transition to unconsciousness may help us to identify drug-induced alterations of the underlying brain state, and provide insight into the mechanisms of general anesthesia. Although cellular-based mechanisms have been proposed, the origin of the slow oscillation has not yet been unambiguously established. A recent theoretical study by Steyn-Ross et al. (2013) proposes that the slow oscillation is a network, rather than cellular phenomenon. Modeling anesthesia as a moderate reduction in gap-junction interneuronal coupling, they predict an unconscious state signposted by emergent low-frequency...
Monitoring the effect of anesthetic drugs on the central nervous system is a major ongoing challe... more Monitoring the effect of anesthetic drugs on the central nervous system is a major ongoing challenge in anesthesia research. A number of electroencephalogram (EEG)-based monitors of the anesthetic drug effect such as the bispectral (BIS) index have been proposed to analyze the EEG signal during anesthesia. However, the BIS index has received some criticism. This paper offers a method based on the Hilbert-Huang transformation to calculate an index, called the Hilbert-Huang weighted regional frequency (HHWRF), to quantify the effect of propofol on brain activity. The HHWRF and BIS indices are applied to EEG signals collected from nine patients during a controlled propofol induction and emergence scheme. The results show that both the HHWRF and BIS track the gross changes in the EEG with increasing and decreasing anesthetic drug effect (the prediction probability P k of 0.85 and 0.83 for HHWRF and BIS, respectively). Our new index can reflect the transition from unconsciousness to consciousness faster than the BIS, as indicated from the pharmacokinetic and pharmacodynamic modeled parameters and also from the analysis around the point of reawakening. This method could be used to design a new EEG monitoring system to estimate the propofol anesthetic drug effect.
Monitoring depth of anesthesia using the Electroencephalogram (EEG) is a major ongoing challenge ... more Monitoring depth of anesthesia using the Electroencephalogram (EEG) is a major ongoing challenge for anesthetists. The EEG is the recording of brain electrical activity and it contains valuable information related to the different physiological states of the brain. This paper proposes a novel automated method for assessing the anesthesia depth level which consists of two steps. Initially, the sample entropy and permutation entropy features are extracted from the EEG signal. As EEG derived parameters represent different aspects of EEG features, it would be reasonable to use multiple parameters to assess the effect of anesthetic. These features quantify the amount of complexity or irregularity in EEG data and are conceptually simple, computationally efficient and artifact resistant. Then, the extracted features are used as input to an artificial neural network that is a data processing system based on the structure of a biological nervous system. The experimental results indicate that an overall accuracy of 88% can be obtained during sevoflurane in 17 patients to classify the EEG into awake, light, general and deep anesthetised states. Also this method yields a classification accuracy of 92.4% to distinguish between awake and general anesthesia in an independent database of propofol and desflurane in 129 patients. Considering the high accuracy of this method, a new EEG monitoring system could be developed to assist the anesthesiologist to estimate depth of anesthesia quickly and accurately.
Bicoherence quantifies the degree of quadratic phase coupling among different frequency component... more Bicoherence quantifies the degree of quadratic phase coupling among different frequency components within a signal. Previous studies, using Fourier-based methods of bicoherence calculation (FBIC), have demonstrated that electroencephalographic bicoherence can be related to the end-tidal concentration of inhaled anesthetic drugs. However, FBIC methods require excessively long sections of the encephalogram. This problem might be overcome by the use of wavelet-based methods. In this study, we compare FBIC and a recently developed wavelet bicoherence (WBIC) method as a tool to quantify the effect of isoflurane on the electroencephalogram. We analyzed a set of previously published electroencephalographic data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. Nine potential indices of the electroencephalographic anesthetic effect were obtained from the WBIC and FBIC techniques. The relationship between each index and end-tidal concentrations of isoflurane was evaluated using correlation coefficients (r), the inter-individual variations (CV) of index values, the coefficient of determination (R(2)) of the PKPD models and the prediction probability (P(K)). The WBIC-based indices tracked anesthetic effects better than the traditional FBIC-based ones. The DiagBic_En index (derived from the Shannon entropy of the diagonal bicoherence values) performed best [r = 0.79 (0.66-0.92), CV = 0.08 (0.05-0.12), R(2) = 0.80 (0.75-0.85), P(K) = 0.79 (0.75-0.83)]. Short data segments of ∼10-30 s were sufficient to reliably calculate the indices of WBIC. The wavelet-based bicoherence has advantages over the traditional Fourier-based bicoherence in analyzing volatile anesthetic effects on the electroencephalogram.
Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinica... more Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R 2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability P k are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.
Journal of Clinical Monitoring and Computing, 2013
The permutation entropy (PE) of the electroencephalographic (EEG) signals has been proposed as a ... more The permutation entropy (PE) of the electroencephalographic (EEG) signals has been proposed as a robust measure of anesthetic drug effect. The calculation of PE involves the somewhat arbitrary selection of embedding dimension (m) and lag (τ) parameters. Previous studies of PE include the analysis of EEG signals under sevoflurane or propofol anesthesia, where different parameter settings were determined using a number of different criteria. In this study we choose parameter values based on the quantitative performance, to quantify the effect of a wide range of concentrations of isoflurane on the EEG. We analyzed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. PE indices using a range of different parameter settings (m = 3-7, τ = 1-5) were calculated. These indices were evaluated as regards: the correlation coefficient (r) with isoflurane end-tidal concentration, the relationship with isoflurane effect-site concentration assessed by the coefficient of determination (R (2)) of the pharmacokinetic-pharmacodynamic models, and the prediction probability (PK). The embedding dimension (m) and lag (τ) have significant effect on the r values (Two-way repeated-measures ANOVA, p < 0.001). The proposed new permutation entropy index (NPEI) [a combination of PE(m = 3, τ = 2) and PE(m = 3, τ = 3)] performed best among all the parameter combinations, with r = 0.89(0.83-0.94), R (2) = 0.82(0.76-0.87), and PK = 0.80 (0.76-0.85). Further comparison with previously suggested PE measures, as well as other unrelated EEG measures, indicates the superiority of the NPEI. The PE can be utilized to indicate the dynamical changes of EEG signals under isoflurane anesthesia. In this study, the NPEI measure that combines the PE with m = 3, τ = 2 and that with m = 3, τ = 3 is optimal.
A pre-test probability score and D-dimer may reduce the need for ultrasound examinations for excl... more A pre-test probability score and D-dimer may reduce the need for ultrasound examinations for excluding lower limb deep venous thrombosis (DVT). To establish the accuracy of an immunochromatographic D-dimer assay called 'Simplify' for diagnosis of acute DVT by complete (calf veins included) lower limb ultrasound examination. A total of 453 consecutive patients presented to the ED of a tertiary centre with suspected first episode of DVT, were prospectively recruited. A pre-test probability score (Hamilton Score), an immunochromatographic D-dimer and a complete, single, unilateral lower limb ultrasound examination were performed in all patients. All patients with a negative ultrasound examination were followed up for 3 months. There were 159 men and 294 women with a mean age of 55.8 years (SD 20.3). Of the 227 patients with a negative D-dimer, 214 patients had negative ultrasound examinations and 13 patients had isolated calf DVT. Among the 226 patients with a positive D-dimer, 74 patients had DVT and 152 patients had negative ultrasound examinations. The sensitivity, specificity, positive and negative predictive values were 85.1% (75.8-91.8), 58.5% (53.4-63.5), 32.7% (26.6-38.9) and 94.3% (90.4-96.9), respectively. One hundred and sixty-five patients had an unlikely Hamilton Score and a negative D-dimer. The negative predictive value of the immunochromatographic D-dimer in an unlikely Hamilton Score population was 98.8% (95.7-99.8%). An unlikely probability Hamilton Score and a negative immunochromatographic D-dimer reliably exclude both proximal and isolated calf DVT.
Computational and Mathematical Methods in Medicine, 2012
This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a co... more This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these domains. The event related multiple EEG recordings of the chronic pain patients and non-pain controls with somatosensory stimuli (pain, random pain, touch, random touch) are analyzed. Multiple linear regression (MLR) is applied to describe the effects of aging on the frequency response differences between patients and controls. The results show that the somatosensory cortical responses occurred around 250 ms in both groups. In the frequency domain, the neural response frequency in the pain group (around 4 Hz) was less than that in the control group (around 5.5 Hz) under the somatosensory stimuli. In the channel domain, cortical activation was predominant in the frontal region for the chronic pain group and in the central region for controls. The indices of active ratios were statistical significant between the two groups in the frontal and central regions. These findings demonstrate that the PARAFAC is an interesting method to understanding the pathophysiological characteristics of chronic pain.
Fourier bicoherence has previously been applied to investigate phase coupling in the EEG in anaes... more Fourier bicoherence has previously been applied to investigate phase coupling in the EEG in anaesthesia. However, there are significant theoretical limitations regarding its sensitivity in detecting transient episodes of inter-frequency coupling. Therefore, we used a recently developed wavelet bicoherence method to investigate the cross-frequency coupling in the EEG of patients under isoflurane anaesthesia; examining the relationship between the patterns of wavelet bicoherence and the isoflurane concentrations. We analysed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane anaesthesia. Artifact-free, 1 min EEG segments at different isoflurane concentrations were extracted from each subject and the wavelet bicoherence calculated for all pairs of frequencies from 0.5 to 20 Hz. Isoflurane caused two peaks in the α (6-13 Hz) and slow δ (<1 Hz) regions of the bicoherence matrix diagonal. Higher concentrations of isoflurane shifted the α peak to lower frequencies [11.3 (0.9) Hz at 0.3% to 7.1 (1.2) Hz at 1.5%], as has been previously observed in the power spectra. Outside the diagonal, we also found a significant α peak that was phase-coupled to the slow δ waves; higher concentrations of isoflurane shifted this peak to lower frequencies [10.8 (1.2) to 7.7 (0.7) Hz]. Isoflurane caused cross-frequency coupling between α and slow δ waves. Increasing isoflurane concentration slowed the α frequencies where the coupling had occurred. This phenomenon of α-δ coupling suggests that slow cortical oscillations organize the higher α band activity, which is consistent with other studies in natural sleep.
Cortical stimulation plays an important role in the study of epileptic seizures. We present a num... more Cortical stimulation plays an important role in the study of epileptic seizures. We present a numerical simulation of stimulation using optogenetic channels expressed by excitatory cells in a mean field model of the human cortex. Depolarising excitatory cells in a patch of model cortex using Channelrhodpsin-2 (ChR2) ion channels, we are able to hyper-excite a normally functioning cortex and mimic seizure activity. The temporal characteristics of optogenetic channels, and the ability to control the frequency of synchronous activity using these properties are also demonstrated. Optogenetics is a powerful stimulation technique with high spatial, temporal and cell-type specificity, and would be invaluable in studying seizures and other brain disorders and functions.
The role of extra-synaptic receptors in the regulation of excitation and inhibition in the brain ... more The role of extra-synaptic receptors in the regulation of excitation and inhibition in the brain has attracted increasing attention. Because activity in the extra-synaptic receptors plays a role in regulating the level of excitation and inhibition in the brain, they may be important in determining the level of consciousness. This paper reviews briefly the literature on extra-synaptic GABA and NMDA receptors and their affinity to anesthetic drugs. We propose a neural population model that illustrates how the effect of the anesthetic drug propofol on GABAergic extra-synaptic receptors results in changes in neural population activity and the electroencephalogram (EEG). Our results show that increased tonic inhibition in inhibitory cortical neurons cause a dramatic increase in the power of both δ- and α- bands. Conversely, the effects of increased tonic inhibition in cortical excitatory neurons and thalamic relay neurons have the opposite effect and decrease the power in these bands. Th...
Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severe... more Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and mult...
► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detec... more ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy e...
The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthe... more The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness.
Ketamine has been in clinical use for over half a century, yet its precise mechanisms of action r... more Ketamine has been in clinical use for over half a century, yet its precise mechanisms of action remain mysterious for the large part. Its hypnotic effects appear to be largely mediated by blockade of NMDA and HCN1 receptors, but cholinergic, aminergic, and opioid systems appear to play both a positive and negative modulatory role in both sedation and analgesia. Ketamine's effects in chronic pain, and as an antidepressant, far outlast the actual drug levels, and are probably mediated by a secondary increase in structural synaptic connectivity that is mediated by a neuronal response to the ketamine-induced hyperglutamatergic state.
Over 80% of the head injuries were due to road trauma. Over 60% occurred >30km from th... more Over 80% of the head injuries were due to road trauma. Over 60% occurred >30km from the first admission hospital, 35% were >60km away and 43% took more than 90 minutes to arrive in hospital. Helicopter transport was used for 34% of patients. Hypoxia was present in ...
The re-establishment of conscious awareness after discontinuing general anesthesia has often been... more The re-establishment of conscious awareness after discontinuing general anesthesia has often been assumed to be the inverse of loss of consciousness. This is despite the obvious asymmetry in the initiation and termination of natural sleep. In order to characterize the restoration of consciousness after surgery, we recorded frontal electroencephalograph (EEG) from 100 patients in the operating room during maintenance and emergence from general anesthesia. We have defined, for the first time, 4 steady-state patterns of anesthetic maintenance based on the relative EEG power in the slow-wave (,14 Hz) frequency bands that dominate sleep and anesthesia. Unlike single-drug experiments performed in healthy volunteers, we found that surgical patients exhibited greater electroencephalographic heterogeneity while re-establishing conscious awareness after drug discontinuation. Moreover, these emergence patterns could be broadly grouped according to the duration and rapidity of transitions amongst these slow-wave dominated brain states that precede awakening. Most patients progressed gradually from a pattern characterized by strong peaks of delta (0.5-4 Hz) and alpha/spindle (8-14 Hz) power ('Slow-Wave Anesthesia') to a state marked by low delta-spindle power ('Non Slow-Wave Anesthesia') before awakening. However, 31% of patients transitioned abruptly from Slow-Wave Anesthesia to waking; they were also more likely to express pain in the post-operative period. Our results, based on sleep-staging classification, provide the first systematized nomenclature for tracking brain states under general anesthesia from maintenance to emergence, and suggest that these transitions may correlate with post-operative outcomes such as pain.
The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are close... more The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are closely similar to those seen during slow-wave sleep, the deepest stage of natural sleep; both states show patterns dominated by large amplitude slow waves. Slow oscillations are believed to be important for memory consolidation during natural sleep. Tracking the emergence of slow-wave oscillations during transition to unconsciousness may help us to identify drug-induced alterations of the underlying brain state, and provide insight into the mechanisms of general anesthesia. Although cellular-based mechanisms have been proposed, the origin of the slow oscillation has not yet been unambiguously established. A recent theoretical study by Steyn-Ross et al. (2013) proposes that the slow oscillation is a network, rather than cellular phenomenon. Modeling anesthesia as a moderate reduction in gap-junction interneuronal coupling, they predict an unconscious state signposted by emergent low-frequency...
Monitoring the effect of anesthetic drugs on the central nervous system is a major ongoing challe... more Monitoring the effect of anesthetic drugs on the central nervous system is a major ongoing challenge in anesthesia research. A number of electroencephalogram (EEG)-based monitors of the anesthetic drug effect such as the bispectral (BIS) index have been proposed to analyze the EEG signal during anesthesia. However, the BIS index has received some criticism. This paper offers a method based on the Hilbert-Huang transformation to calculate an index, called the Hilbert-Huang weighted regional frequency (HHWRF), to quantify the effect of propofol on brain activity. The HHWRF and BIS indices are applied to EEG signals collected from nine patients during a controlled propofol induction and emergence scheme. The results show that both the HHWRF and BIS track the gross changes in the EEG with increasing and decreasing anesthetic drug effect (the prediction probability P k of 0.85 and 0.83 for HHWRF and BIS, respectively). Our new index can reflect the transition from unconsciousness to consciousness faster than the BIS, as indicated from the pharmacokinetic and pharmacodynamic modeled parameters and also from the analysis around the point of reawakening. This method could be used to design a new EEG monitoring system to estimate the propofol anesthetic drug effect.
Monitoring depth of anesthesia using the Electroencephalogram (EEG) is a major ongoing challenge ... more Monitoring depth of anesthesia using the Electroencephalogram (EEG) is a major ongoing challenge for anesthetists. The EEG is the recording of brain electrical activity and it contains valuable information related to the different physiological states of the brain. This paper proposes a novel automated method for assessing the anesthesia depth level which consists of two steps. Initially, the sample entropy and permutation entropy features are extracted from the EEG signal. As EEG derived parameters represent different aspects of EEG features, it would be reasonable to use multiple parameters to assess the effect of anesthetic. These features quantify the amount of complexity or irregularity in EEG data and are conceptually simple, computationally efficient and artifact resistant. Then, the extracted features are used as input to an artificial neural network that is a data processing system based on the structure of a biological nervous system. The experimental results indicate that an overall accuracy of 88% can be obtained during sevoflurane in 17 patients to classify the EEG into awake, light, general and deep anesthetised states. Also this method yields a classification accuracy of 92.4% to distinguish between awake and general anesthesia in an independent database of propofol and desflurane in 129 patients. Considering the high accuracy of this method, a new EEG monitoring system could be developed to assist the anesthesiologist to estimate depth of anesthesia quickly and accurately.
Bicoherence quantifies the degree of quadratic phase coupling among different frequency component... more Bicoherence quantifies the degree of quadratic phase coupling among different frequency components within a signal. Previous studies, using Fourier-based methods of bicoherence calculation (FBIC), have demonstrated that electroencephalographic bicoherence can be related to the end-tidal concentration of inhaled anesthetic drugs. However, FBIC methods require excessively long sections of the encephalogram. This problem might be overcome by the use of wavelet-based methods. In this study, we compare FBIC and a recently developed wavelet bicoherence (WBIC) method as a tool to quantify the effect of isoflurane on the electroencephalogram. We analyzed a set of previously published electroencephalographic data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. Nine potential indices of the electroencephalographic anesthetic effect were obtained from the WBIC and FBIC techniques. The relationship between each index and end-tidal concentrations of isoflurane was evaluated using correlation coefficients (r), the inter-individual variations (CV) of index values, the coefficient of determination (R(2)) of the PKPD models and the prediction probability (P(K)). The WBIC-based indices tracked anesthetic effects better than the traditional FBIC-based ones. The DiagBic_En index (derived from the Shannon entropy of the diagonal bicoherence values) performed best [r = 0.79 (0.66-0.92), CV = 0.08 (0.05-0.12), R(2) = 0.80 (0.75-0.85), P(K) = 0.79 (0.75-0.83)]. Short data segments of ∼10-30 s were sufficient to reliably calculate the indices of WBIC. The wavelet-based bicoherence has advantages over the traditional Fourier-based bicoherence in analyzing volatile anesthetic effects on the electroencephalogram.
Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinica... more Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R 2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability P k are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.
Journal of Clinical Monitoring and Computing, 2013
The permutation entropy (PE) of the electroencephalographic (EEG) signals has been proposed as a ... more The permutation entropy (PE) of the electroencephalographic (EEG) signals has been proposed as a robust measure of anesthetic drug effect. The calculation of PE involves the somewhat arbitrary selection of embedding dimension (m) and lag (τ) parameters. Previous studies of PE include the analysis of EEG signals under sevoflurane or propofol anesthesia, where different parameter settings were determined using a number of different criteria. In this study we choose parameter values based on the quantitative performance, to quantify the effect of a wide range of concentrations of isoflurane on the EEG. We analyzed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane general anesthesia combined with epidural anesthesia. PE indices using a range of different parameter settings (m = 3-7, τ = 1-5) were calculated. These indices were evaluated as regards: the correlation coefficient (r) with isoflurane end-tidal concentration, the relationship with isoflurane effect-site concentration assessed by the coefficient of determination (R (2)) of the pharmacokinetic-pharmacodynamic models, and the prediction probability (PK). The embedding dimension (m) and lag (τ) have significant effect on the r values (Two-way repeated-measures ANOVA, p < 0.001). The proposed new permutation entropy index (NPEI) [a combination of PE(m = 3, τ = 2) and PE(m = 3, τ = 3)] performed best among all the parameter combinations, with r = 0.89(0.83-0.94), R (2) = 0.82(0.76-0.87), and PK = 0.80 (0.76-0.85). Further comparison with previously suggested PE measures, as well as other unrelated EEG measures, indicates the superiority of the NPEI. The PE can be utilized to indicate the dynamical changes of EEG signals under isoflurane anesthesia. In this study, the NPEI measure that combines the PE with m = 3, τ = 2 and that with m = 3, τ = 3 is optimal.
A pre-test probability score and D-dimer may reduce the need for ultrasound examinations for excl... more A pre-test probability score and D-dimer may reduce the need for ultrasound examinations for excluding lower limb deep venous thrombosis (DVT). To establish the accuracy of an immunochromatographic D-dimer assay called 'Simplify' for diagnosis of acute DVT by complete (calf veins included) lower limb ultrasound examination. A total of 453 consecutive patients presented to the ED of a tertiary centre with suspected first episode of DVT, were prospectively recruited. A pre-test probability score (Hamilton Score), an immunochromatographic D-dimer and a complete, single, unilateral lower limb ultrasound examination were performed in all patients. All patients with a negative ultrasound examination were followed up for 3 months. There were 159 men and 294 women with a mean age of 55.8 years (SD 20.3). Of the 227 patients with a negative D-dimer, 214 patients had negative ultrasound examinations and 13 patients had isolated calf DVT. Among the 226 patients with a positive D-dimer, 74 patients had DVT and 152 patients had negative ultrasound examinations. The sensitivity, specificity, positive and negative predictive values were 85.1% (75.8-91.8), 58.5% (53.4-63.5), 32.7% (26.6-38.9) and 94.3% (90.4-96.9), respectively. One hundred and sixty-five patients had an unlikely Hamilton Score and a negative D-dimer. The negative predictive value of the immunochromatographic D-dimer in an unlikely Hamilton Score population was 98.8% (95.7-99.8%). An unlikely probability Hamilton Score and a negative immunochromatographic D-dimer reliably exclude both proximal and isolated calf DVT.
Computational and Mathematical Methods in Medicine, 2012
This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a co... more This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these domains. The event related multiple EEG recordings of the chronic pain patients and non-pain controls with somatosensory stimuli (pain, random pain, touch, random touch) are analyzed. Multiple linear regression (MLR) is applied to describe the effects of aging on the frequency response differences between patients and controls. The results show that the somatosensory cortical responses occurred around 250 ms in both groups. In the frequency domain, the neural response frequency in the pain group (around 4 Hz) was less than that in the control group (around 5.5 Hz) under the somatosensory stimuli. In the channel domain, cortical activation was predominant in the frontal region for the chronic pain group and in the central region for controls. The indices of active ratios were statistical significant between the two groups in the frontal and central regions. These findings demonstrate that the PARAFAC is an interesting method to understanding the pathophysiological characteristics of chronic pain.
Fourier bicoherence has previously been applied to investigate phase coupling in the EEG in anaes... more Fourier bicoherence has previously been applied to investigate phase coupling in the EEG in anaesthesia. However, there are significant theoretical limitations regarding its sensitivity in detecting transient episodes of inter-frequency coupling. Therefore, we used a recently developed wavelet bicoherence method to investigate the cross-frequency coupling in the EEG of patients under isoflurane anaesthesia; examining the relationship between the patterns of wavelet bicoherence and the isoflurane concentrations. We analysed a set of previously published EEG data, obtained from 29 patients who underwent elective abdominal surgery under isoflurane anaesthesia. Artifact-free, 1 min EEG segments at different isoflurane concentrations were extracted from each subject and the wavelet bicoherence calculated for all pairs of frequencies from 0.5 to 20 Hz. Isoflurane caused two peaks in the α (6-13 Hz) and slow δ (<1 Hz) regions of the bicoherence matrix diagonal. Higher concentrations of isoflurane shifted the α peak to lower frequencies [11.3 (0.9) Hz at 0.3% to 7.1 (1.2) Hz at 1.5%], as has been previously observed in the power spectra. Outside the diagonal, we also found a significant α peak that was phase-coupled to the slow δ waves; higher concentrations of isoflurane shifted this peak to lower frequencies [10.8 (1.2) to 7.7 (0.7) Hz]. Isoflurane caused cross-frequency coupling between α and slow δ waves. Increasing isoflurane concentration slowed the α frequencies where the coupling had occurred. This phenomenon of α-δ coupling suggests that slow cortical oscillations organize the higher α band activity, which is consistent with other studies in natural sleep.
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Papers by Jamie Sleigh