- Email: [email protected]
EP 113. Increased coherence to the midline in interictal EEG predicts generalized seizures in focal epilepsy
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Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
regions of the motor cortex is crucial. In the study presented here, the interaction of different motor related brain regions during simple internally and externally initiated finger movements was investigated during preparation and execution of those movements. To this end, EEG data (64 channel system) were recorded from 18 right-handed healthy participants (22–35 years, 10 female). The participants performed a finger tapping paradigm that contained left and right index finger movements which were triggered either by a visual cue or by voluntary choice. We carried out inter-regional phase-locking analysis of Morlet wavelet phases in delta-theta (2–7 Hz), alpha (8–12 Hz) and beta (13–30 Hz) frequency bands of the Laplacian referenced EEG data in order to identify coupling between brain regions during the motor task. We analyzed connectivity in a network involving electrodes lying above the premotor areas (PM: FC3, FC4), the supplementary motor areas (SMA: Cz, FCz) and the primary motor cortex (M1: C3, C4) as nodes. We found significant changes of synchronization in the deltatheta frequency band during both movement preparation and execution. The construction of lateralization networks revealed that the phase-locking effect in these frequency bands was stronger for connections from motor regions to supplementary motor areas contralaterally to the moving hand than on the ipsilateral side. The interregional synchronizations appeared only when both regions showed strong intraregional phase locking. Thus, intraregional phase locking in the delta-theta frequencies seems to be a prerequisite for interregional phase locking. We hypothesize that both intra- and interregional phase locking form a functional network of synchronous activity. This activity enhances the excitability of the motor system so that transient cue signals are able to induce different kinds of movements during movement preparation. Additionally we found strong synchronization in the betafrequency band that appeared after the movement has been executed for connections from the supplementary motor areas to the primary motor cortex and the pre-motor cortex contralaterally to the moving hand. Since this synchronization effect is expressed significantly stronger during the self-initiated than during visuallytriggered finger movements, we suggest that it might be related to the suppression of the internal ‘‘go” cue after the movement was executed. doi:10.1016/j.clinph.2016.05.154
EP 112. Neurophysiological correlates of cognitive control in patients with major depressive disorder (MDD)—J. Brenner (Universität Tübingen, Institut für Neurophysiologie und interventionelle Neuropsychatrie, Tübingen, Germany)
Affective cognitive control capacity (e.g., the ability to regulate emotions or manipulate emotional material in the service of task goals) is associated with professional and interpersonal success. Impoverished affective control, by contrast, characterizes many neuropsychiatric disorders. Resent studies already showed that patients with major depressive disorder (MDD) for example exhibit an attentional bias, meaning that they had slower reaction time for emotional valent pictures than for neutral pictures (Wolkenstein and Plewnia, 2013)? Our research group moreover discovered that emotional,in contrast to neutral valent pictures lead to an increased LPP (late positive potential) in EEGs of healthy subjects while carrying out a dual working memory task (DWM) (Faehling, 2014)? In our study we want to examine the interaction between emotion regulation,reaction time and working memory performance in
patients with major depressive disorder (MDD).Therefore we used negative and neutral IAPS as distractors in a DWM and linked the task with EEG measurement. Our main hypothesis was that the late positive potential (LPP) over the prefrontal? cortex of depressed subjects, measured while watching negative pictures, increased more as in healthy subjects. Accordingly higher LPP amplitudes show higher cognitive capacity load for affective stimuli. This is in line with the discovered correlation between high LPP amplitudes and task accuracy and high LPP amplitudes and reaction time. doi:10.1016/j.clinph.2016.05.155
EP 113. Increased coherence to the midline in interictal EEG predicts generalized seizures in focal epilepsy—K. Ernst *, E. Hartl, J. Goc, S. Noachtar, C. Vollmar (University of Munich Hospital, Dept. of Neurology, Epilepsy Center, Munich, Germany) ⇑
Corresponding author.
Background: Presurgical evaluation of patients with focal epilepsy relies strongly on EEG. Usually, interictal EEG is analyzed for spikes and regional slowing, providing localizing information, and ictal EEG allows to localize electrical activity during a seizure, including seizure onset and secondary propagation. EEG coherence analyses allow to make inferences on the synchronization between different brain regions, but are rarely used in epilepsy. Here we evaluate the clinical value of interictal EEG coherence analyses to contribute clinically relevant information during the presurgical evaluation of epilepsy patients. Methods: Nineteen patients with focal epilepsy were included in this study. To avoid effects from major structural lesions on the EEG, we included only patients with no structural lesion (n = 10) or small lesions, less than 2 cm diameter (n = 9). All patients had continuous video EEG monitoring for 5–12 days, where 40 channel EEG was recorded with a sampling rate of 512 Hz. We have selected 5 epochs of awake, artifact free, interictal EEG, with a duration of 4–10 min for each patient. EEG coherence was analyzed using Matlab and fieldtrip software. Coherence was calculated between all possible pairs of electrodes, for five different frequency bands. Coherence values between neighboring pairs of electrodes were averaged for a total of 17 anatomical brain regions (7 left, 7 right, 3 midline) and were analyzed for asymmetries between the left and right hemisphere. Coherence data was correlated with clinical information from the video EEG monitoring. Results: Regional coherence changes were seen in 17 of 19 patients (89%). Two different patterns were observed: In 10 patients (53%) we saw an increased coherence between the epileptogenic region and the midline regions, and 7 of these 10 showed a reduced coherence within the hemisphere ipsilateral to the epileptogenic zone. In the other 7 patients (37%) there was increased coherence within the epileptogenic hemisphere and 5 of these 7 showed decreased coherence between the epileptogenic region and the midline regions. Nine of the 10 patients with increased coherence between the epileptogenic region and the midline regions had clinical signs of fast propagation, such as predominant bilateral seizure pattern in EEG, or frequent and fast clinical evolution to generalized tonic clonic seizures. On the other hand, none of the patients with decreased coherence to the midline had contralateral spikes, bilateral seizure onset in ictal EEG or frequent generalized seizures. Conclusions: Coherence analysis of interictal EEG seems to be able to distinguish two patient groups. Those with an increased coherence between the epileptigenic zone and midline regions also had frequent clinical signs of a more widespread pathology, including a
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
higher risk for fast propagation and generalization. Patients with increased coherence exclusively within the epileptigenic hemisphere, on the other hand, also had more clearly lateralized clinical signs and less frequent generalized seizure, potentially making them better candidates for resective surgery. doi:10.1016/j.clinph.2016.05.156
EP 114. Uncovering epileptic seizures – A feasibility study for the semiological analysis of hidden patient motion during epileptic seizures—F. Achilles a,b,*, H.M.P. Choupina a,c, A.M. Loesch a, J.P. S. Cunha c, J. Remi a, C. Vollmar a, F. Tombari a,d, N. Navab a,e, S. Noachtar a (a University of Munich, Epilepsy Center, Department of Neurology, Munich, Germany, b Technische Universität München, Computer Aided Medical Procedures, Munich, Germany, c University of Porto, INESC TEC, Porto, Portugal, d University of Bologna, DISI, Bologna, Germany, e Johns Hopkins University, Computer Aided Medical Procedures, Germany) ⇑
Corresponding author.
Aims: Semiological analysis of epileptic seizures is performed to categorize resection candidates and provides valuable information about lateralization and localization of the epileptogenic zone. Seizure related movements of inpatients are evaluated based on video-EEG recordings, but can be hidden during seizures through e.g. blanket occlusion, staff in front of the camera, image blurring or if the patient is outside of the field of view. Based on this problem, we propose the use of accelerometer sensors attached to the patient extremities, which allows the continuous extraction of motion features, even under occlusion. In this study we focus our analysis on the separation of ictal and postictal movement. Methods: From 15 patients with 57 motor seizures, we selected the most suitable patient that consistently performed both ictal and postictal movements in all of his seizures (n = 6). Half of those occurred while the patient was completely covered by the blanket. The accelerometers (Shimmer) were attached to the wrists and ankles of the patient. The remaining three seizures allowed a clear view on the patient, allowing to manually track movements with a commercial videobased system (MaxTRAQ). Ictal and postictal phase of all seizures were determined by video-EEG analysis. Comparative measurements were made for the manual tracking and the accelerometer data. We developed a new metric for accelerometers, which we call agility, accounting for rotation as well as for rapid movement of the extremities. The agility is the sum over absolute changes in the acceleration vector divided by the elapsed time. Results: To evaluate the metrics, we chose the threshold that provides 90% sensitivity for the ictal phase and report the respective specificity. Video-analysis: In related works, the trajectory-length of a bodypart in 2D successfully distinguished movements of interest (MOIs) in frontal lobe and temporal lobe epilepsy. In this study, the trajectory-length in [pixels] was 1780 ± 702 during ictal and 935 ± 783 during postictal phase, yielding a specificity of 66.7% (threshold 1150). Furthermore, the covered area has previously been used to separate MOIs in hypermotor and automotor seizures. This area in [pixels2] reached 45,160 ± 44,563 during ictal and 16,535 ± 10,702 during postictal phase with a specificity of 61.1% (threshold 22,250). Accelerometer-analysis: For hypermotor seizure detection, the standard deviation of the acceleration was used in current literature. In the three completely occluded seizures, this value in [m/s2] was 1.8 ± 0.6 during ictal and 2.50.9 during postictal phase at a 55.6% specificity (threshold 2.8). The new agility metric in [Hz] yielded
e289
3.1 ± 0.9 during ictal and 5.8 ± 3.0 during postictal phase, providing a separation specificity of 66.7% (threshold 4.2) at 90% sensitivity, thus matching the best video-based metric. Conclusions: While video tracking and accelerometers measure different aspects of the seizure related movements, their accuracies are on par, showing that accelerometer data are suitable for the quantification of seizures occurring under a blanket. Interestingly, video metrics based on the range of movements are higher in the ictal phase, while the metrics we calculated from accelerometer data are higher in the postictal phase. We deem further research for these complementary quantification approaches extremely valuable, as it opens up new possibilities for continuous quantitative semiological analysis. doi:10.1016/j.clinph.2016.05.157
EP 115. Effective connectivity of subcortical–cortical networks revealed by simultaneous scalp and depth EEG recordings in humans—R. Hashemiyoon a,*, M. Tomescu b, A. Coito c, T. Schüller d, E. Sildatke d, J. Kuhn d,e, V. Visser-Vandewalle a, C. Michel b (a Universitätsklinikum Köln, Klinik für Stereotaxie und Funktionelle Neurochirurgie, Köln, Germany, b University Geneva, Dept. of Fundamental Neuroscience, Geneva, Switzerland, c University Hospital, Neurology Clinic, Geneva, Switzerland, d University Hospital of Cologne, Department of Psychiatry and Psychotherapy, Köln, Germany, e Johanniter Hospital, EVKLN, Oberhausen, Germany) ⇑
Corresponding author.
Functional magnetic resonance imaging (fMRI) studies showed that the brain at rest exhibits spontaneous BOLD (Blood Oxygenation Level Dependent) fluctuations over time that correlate between functionally connected brain areas (Biswal et al., 1995). However, the lower temporal resolution of fMRI precludes the study of neuronal coding and temporal information flow with an appropriate level of temporal acuity in these networks. EEG is better suited for the study of the temporal dynamics in such networks because of its millisecond resolution; however, due to its limited spatial resolution, contributions from subcortical structures are likely not well represented. Not surprisingly though, results from fMRI resting state studies clearly indicate that subcortical structures are important key players in these networks. In order to gain better insights into the interactions of cortical– subcortical circuits at rest, we performed recordings from multiple scalp electrodes simultaneously with chronically implanted deep brain stimulation electrodes in subcortical targets of human subjects. Computed partial directed coherence based on Granger causality (Plomp et al., 2014) was performed to identify the major drivers of the network and the sites that were subject to them. Here we report on obsessive–compulsive disorder patients who were bilaterally implanted in the nucleus accumbens as well as Tourette syndrome patients with bilateral thalamic implants. In all patients, local circumscribed networks surrounding specific subcortical electrodes were identified as major drivers of the larger pathological network. Recordings which were performed with 256-channel scalp EEG electrodes were subject to source localization methods and connectivity analysis was performed in the source space (Coito et al., 2015). Our cortical–subcortical simultaneous recordings provide the platform for a deeper understanding of the temporal dynamics of whole-brain networks in humans, which includes the intimate contribution of deep structures and opens new ways of identifying neurophysiological markers of these psychiatric diseases.
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
regions of the motor cortex is crucial. In the study presented here, the interaction of different motor related brain regions during simple internally and externally initiated finger movements was investigated during preparation and execution of those movements. To this end, EEG data (64 channel system) were recorded from 18 right-handed healthy participants (22–35 years, 10 female). The participants performed a finger tapping paradigm that contained left and right index finger movements which were triggered either by a visual cue or by voluntary choice. We carried out inter-regional phase-locking analysis of Morlet wavelet phases in delta-theta (2–7 Hz), alpha (8–12 Hz) and beta (13–30 Hz) frequency bands of the Laplacian referenced EEG data in order to identify coupling between brain regions during the motor task. We analyzed connectivity in a network involving electrodes lying above the premotor areas (PM: FC3, FC4), the supplementary motor areas (SMA: Cz, FCz) and the primary motor cortex (M1: C3, C4) as nodes. We found significant changes of synchronization in the deltatheta frequency band during both movement preparation and execution. The construction of lateralization networks revealed that the phase-locking effect in these frequency bands was stronger for connections from motor regions to supplementary motor areas contralaterally to the moving hand than on the ipsilateral side. The interregional synchronizations appeared only when both regions showed strong intraregional phase locking. Thus, intraregional phase locking in the delta-theta frequencies seems to be a prerequisite for interregional phase locking. We hypothesize that both intra- and interregional phase locking form a functional network of synchronous activity. This activity enhances the excitability of the motor system so that transient cue signals are able to induce different kinds of movements during movement preparation. Additionally we found strong synchronization in the betafrequency band that appeared after the movement has been executed for connections from the supplementary motor areas to the primary motor cortex and the pre-motor cortex contralaterally to the moving hand. Since this synchronization effect is expressed significantly stronger during the self-initiated than during visuallytriggered finger movements, we suggest that it might be related to the suppression of the internal ‘‘go” cue after the movement was executed. doi:10.1016/j.clinph.2016.05.154
EP 112. Neurophysiological correlates of cognitive control in patients with major depressive disorder (MDD)—J. Brenner (Universität Tübingen, Institut für Neurophysiologie und interventionelle Neuropsychatrie, Tübingen, Germany)
Affective cognitive control capacity (e.g., the ability to regulate emotions or manipulate emotional material in the service of task goals) is associated with professional and interpersonal success. Impoverished affective control, by contrast, characterizes many neuropsychiatric disorders. Resent studies already showed that patients with major depressive disorder (MDD) for example exhibit an attentional bias, meaning that they had slower reaction time for emotional valent pictures than for neutral pictures (Wolkenstein and Plewnia, 2013)? Our research group moreover discovered that emotional,in contrast to neutral valent pictures lead to an increased LPP (late positive potential) in EEGs of healthy subjects while carrying out a dual working memory task (DWM) (Faehling, 2014)? In our study we want to examine the interaction between emotion regulation,reaction time and working memory performance in
patients with major depressive disorder (MDD).Therefore we used negative and neutral IAPS as distractors in a DWM and linked the task with EEG measurement. Our main hypothesis was that the late positive potential (LPP) over the prefrontal? cortex of depressed subjects, measured while watching negative pictures, increased more as in healthy subjects. Accordingly higher LPP amplitudes show higher cognitive capacity load for affective stimuli. This is in line with the discovered correlation between high LPP amplitudes and task accuracy and high LPP amplitudes and reaction time. doi:10.1016/j.clinph.2016.05.155
EP 113. Increased coherence to the midline in interictal EEG predicts generalized seizures in focal epilepsy—K. Ernst *, E. Hartl, J. Goc, S. Noachtar, C. Vollmar (University of Munich Hospital, Dept. of Neurology, Epilepsy Center, Munich, Germany) ⇑
Corresponding author.
Background: Presurgical evaluation of patients with focal epilepsy relies strongly on EEG. Usually, interictal EEG is analyzed for spikes and regional slowing, providing localizing information, and ictal EEG allows to localize electrical activity during a seizure, including seizure onset and secondary propagation. EEG coherence analyses allow to make inferences on the synchronization between different brain regions, but are rarely used in epilepsy. Here we evaluate the clinical value of interictal EEG coherence analyses to contribute clinically relevant information during the presurgical evaluation of epilepsy patients. Methods: Nineteen patients with focal epilepsy were included in this study. To avoid effects from major structural lesions on the EEG, we included only patients with no structural lesion (n = 10) or small lesions, less than 2 cm diameter (n = 9). All patients had continuous video EEG monitoring for 5–12 days, where 40 channel EEG was recorded with a sampling rate of 512 Hz. We have selected 5 epochs of awake, artifact free, interictal EEG, with a duration of 4–10 min for each patient. EEG coherence was analyzed using Matlab and fieldtrip software. Coherence was calculated between all possible pairs of electrodes, for five different frequency bands. Coherence values between neighboring pairs of electrodes were averaged for a total of 17 anatomical brain regions (7 left, 7 right, 3 midline) and were analyzed for asymmetries between the left and right hemisphere. Coherence data was correlated with clinical information from the video EEG monitoring. Results: Regional coherence changes were seen in 17 of 19 patients (89%). Two different patterns were observed: In 10 patients (53%) we saw an increased coherence between the epileptogenic region and the midline regions, and 7 of these 10 showed a reduced coherence within the hemisphere ipsilateral to the epileptogenic zone. In the other 7 patients (37%) there was increased coherence within the epileptogenic hemisphere and 5 of these 7 showed decreased coherence between the epileptogenic region and the midline regions. Nine of the 10 patients with increased coherence between the epileptogenic region and the midline regions had clinical signs of fast propagation, such as predominant bilateral seizure pattern in EEG, or frequent and fast clinical evolution to generalized tonic clonic seizures. On the other hand, none of the patients with decreased coherence to the midline had contralateral spikes, bilateral seizure onset in ictal EEG or frequent generalized seizures. Conclusions: Coherence analysis of interictal EEG seems to be able to distinguish two patient groups. Those with an increased coherence between the epileptigenic zone and midline regions also had frequent clinical signs of a more widespread pathology, including a
Abstracts / Clinical Neurophysiology 127 (2016) e210–e303
higher risk for fast propagation and generalization. Patients with increased coherence exclusively within the epileptigenic hemisphere, on the other hand, also had more clearly lateralized clinical signs and less frequent generalized seizure, potentially making them better candidates for resective surgery. doi:10.1016/j.clinph.2016.05.156
EP 114. Uncovering epileptic seizures – A feasibility study for the semiological analysis of hidden patient motion during epileptic seizures—F. Achilles a,b,*, H.M.P. Choupina a,c, A.M. Loesch a, J.P. S. Cunha c, J. Remi a, C. Vollmar a, F. Tombari a,d, N. Navab a,e, S. Noachtar a (a University of Munich, Epilepsy Center, Department of Neurology, Munich, Germany, b Technische Universität München, Computer Aided Medical Procedures, Munich, Germany, c University of Porto, INESC TEC, Porto, Portugal, d University of Bologna, DISI, Bologna, Germany, e Johns Hopkins University, Computer Aided Medical Procedures, Germany) ⇑
Corresponding author.
Aims: Semiological analysis of epileptic seizures is performed to categorize resection candidates and provides valuable information about lateralization and localization of the epileptogenic zone. Seizure related movements of inpatients are evaluated based on video-EEG recordings, but can be hidden during seizures through e.g. blanket occlusion, staff in front of the camera, image blurring or if the patient is outside of the field of view. Based on this problem, we propose the use of accelerometer sensors attached to the patient extremities, which allows the continuous extraction of motion features, even under occlusion. In this study we focus our analysis on the separation of ictal and postictal movement. Methods: From 15 patients with 57 motor seizures, we selected the most suitable patient that consistently performed both ictal and postictal movements in all of his seizures (n = 6). Half of those occurred while the patient was completely covered by the blanket. The accelerometers (Shimmer) were attached to the wrists and ankles of the patient. The remaining three seizures allowed a clear view on the patient, allowing to manually track movements with a commercial videobased system (MaxTRAQ). Ictal and postictal phase of all seizures were determined by video-EEG analysis. Comparative measurements were made for the manual tracking and the accelerometer data. We developed a new metric for accelerometers, which we call agility, accounting for rotation as well as for rapid movement of the extremities. The agility is the sum over absolute changes in the acceleration vector divided by the elapsed time. Results: To evaluate the metrics, we chose the threshold that provides 90% sensitivity for the ictal phase and report the respective specificity. Video-analysis: In related works, the trajectory-length of a bodypart in 2D successfully distinguished movements of interest (MOIs) in frontal lobe and temporal lobe epilepsy. In this study, the trajectory-length in [pixels] was 1780 ± 702 during ictal and 935 ± 783 during postictal phase, yielding a specificity of 66.7% (threshold 1150). Furthermore, the covered area has previously been used to separate MOIs in hypermotor and automotor seizures. This area in [pixels2] reached 45,160 ± 44,563 during ictal and 16,535 ± 10,702 during postictal phase with a specificity of 61.1% (threshold 22,250). Accelerometer-analysis: For hypermotor seizure detection, the standard deviation of the acceleration was used in current literature. In the three completely occluded seizures, this value in [m/s2] was 1.8 ± 0.6 during ictal and 2.50.9 during postictal phase at a 55.6% specificity (threshold 2.8). The new agility metric in [Hz] yielded
e289
3.1 ± 0.9 during ictal and 5.8 ± 3.0 during postictal phase, providing a separation specificity of 66.7% (threshold 4.2) at 90% sensitivity, thus matching the best video-based metric. Conclusions: While video tracking and accelerometers measure different aspects of the seizure related movements, their accuracies are on par, showing that accelerometer data are suitable for the quantification of seizures occurring under a blanket. Interestingly, video metrics based on the range of movements are higher in the ictal phase, while the metrics we calculated from accelerometer data are higher in the postictal phase. We deem further research for these complementary quantification approaches extremely valuable, as it opens up new possibilities for continuous quantitative semiological analysis. doi:10.1016/j.clinph.2016.05.157
EP 115. Effective connectivity of subcortical–cortical networks revealed by simultaneous scalp and depth EEG recordings in humans—R. Hashemiyoon a,*, M. Tomescu b, A. Coito c, T. Schüller d, E. Sildatke d, J. Kuhn d,e, V. Visser-Vandewalle a, C. Michel b (a Universitätsklinikum Köln, Klinik für Stereotaxie und Funktionelle Neurochirurgie, Köln, Germany, b University Geneva, Dept. of Fundamental Neuroscience, Geneva, Switzerland, c University Hospital, Neurology Clinic, Geneva, Switzerland, d University Hospital of Cologne, Department of Psychiatry and Psychotherapy, Köln, Germany, e Johanniter Hospital, EVKLN, Oberhausen, Germany) ⇑
Corresponding author.
Functional magnetic resonance imaging (fMRI) studies showed that the brain at rest exhibits spontaneous BOLD (Blood Oxygenation Level Dependent) fluctuations over time that correlate between functionally connected brain areas (Biswal et al., 1995). However, the lower temporal resolution of fMRI precludes the study of neuronal coding and temporal information flow with an appropriate level of temporal acuity in these networks. EEG is better suited for the study of the temporal dynamics in such networks because of its millisecond resolution; however, due to its limited spatial resolution, contributions from subcortical structures are likely not well represented. Not surprisingly though, results from fMRI resting state studies clearly indicate that subcortical structures are important key players in these networks. In order to gain better insights into the interactions of cortical– subcortical circuits at rest, we performed recordings from multiple scalp electrodes simultaneously with chronically implanted deep brain stimulation electrodes in subcortical targets of human subjects. Computed partial directed coherence based on Granger causality (Plomp et al., 2014) was performed to identify the major drivers of the network and the sites that were subject to them. Here we report on obsessive–compulsive disorder patients who were bilaterally implanted in the nucleus accumbens as well as Tourette syndrome patients with bilateral thalamic implants. In all patients, local circumscribed networks surrounding specific subcortical electrodes were identified as major drivers of the larger pathological network. Recordings which were performed with 256-channel scalp EEG electrodes were subject to source localization methods and connectivity analysis was performed in the source space (Coito et al., 2015). Our cortical–subcortical simultaneous recordings provide the platform for a deeper understanding of the temporal dynamics of whole-brain networks in humans, which includes the intimate contribution of deep structures and opens new ways of identifying neurophysiological markers of these psychiatric diseases.