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2. Electrophysiological brain imaging based on simulation-driven deep learning in the context of epilepsy

Author

Zuyi Yu, Amar Kachenoura, Régine Le Bouquin Jeannès, Huazhong Shu, Paul Berraute, Anca Nica, Isabelle Merlet, Laurent Albera, and Ahmad Karfoul

Subjects
Electrophysiological source imaging, Inverse problem, Simulation-driven deep learning, Multi-scale strategy, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Identifying the location, the spatial extent and the electrical activity of distributed brain sources in the context of epilepsy through ElectroEncephaloGraphy (EEG) recordings is a challenging task because of the highly ill-posed nature of the underlying Electrophysiological Source Imaging (ESI) problem. To guarantee a unique solution, most existing ESI methods pay more attention to solve this inverse problem by imposing physiological constraints. This paper proposes an efficient ESI approach based on simulation-driven deep learning. Epileptic High-resolution 256-channels scalp EEG (Hr-EEG) signals are simulated in a realistic manner to train the proposed patient-specific model. More particularly, a computational neural mass model developed in our team is used to generate the temporal dynamics of the activity of each dipole while the forward problem is solved using a patient-specific three-shell realistic head model and the boundary element method. A Temporal Convolutional Network (TCN) is considered in the proposed model to capture local spatial patterns. To enable the model to observe the EEG signals from different scale levels, the multi-scale strategy is leveraged to capture the overall features and fine-grain features by adjusting the convolutional kernel size. Then, the Long Short-Term Memory (LSTM) is used to extract temporal dependencies among the computed spatial features. The performance of the proposed method is evaluated through three different scenarios of realistic synthetic interictal Hr-EEG data as well as on real interictal Hr-EEG data acquired in three patients with drug-resistant partial epilepsy, during their presurgical evaluation. A performance comparison study is also conducted with two other deep learning-based methods and four classical ESI techniques. The proposed model achieved a Dipole Localization Error (DLE) of 1.39 and Normalized Hamming Distance (NHD) of 0.28 in the case of one patch with SNR of 10 dB. In the case of two uncorrelated patches with an SNR of 10 dB, obtained DLE and NHD were respectively 1.50 and 0.28. Even in the more challenging scenario of two correlated patches with an SNR of 10 dB, the proposed approach still achieved a DLE of 3.74 and an NHD of 0.43. The results obtained on simulated data demonstrate that the proposed method outperforms the existing methods for different signal-to-noise and source configurations. The good behavior of the proposed method is also confirmed on real interictal EEG data. The robustness with respect to noise makes it a promising and alternative tool to localize epileptic brain areas and to reconstruct their electrical activities from EEG signals.

Published
2024
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5. Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice

Author

Romane Cecchi, Fabien Vinckier, Jiri Hammer, Petr Marusic, Anca Nica, Sylvain Rheims, Agnès Trebuchon, Emmanuel J Barbeau, Marie Denuelle, Louis Maillard, Lorella Minotti, Philippe Kahane, Mathias Pessiglione, and Julien Bastin

Subjects
choice, mood, iEEG, Medicine, Science, Biology (General), QH301-705.5
Abstract

Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n=30) while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affect decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that (1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, (2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain vs. loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.

Published
2022
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7. Surgical Alloplastic Approach with Dual Mesh in a Multisacular, Recurrent Incisional Hernia – Case Presentation

Author

DANIEL MIHALACHE, BOGDAN SOCEA, ALEXANDRU SMARANDA, ANCA NICA, OVIDIU GABRIEL BRATU, ALEXANDU CONSTANTIN CARAP, CEZAR MOCULESCU, DUMITRU CRISTINEL BADIU, DAN NICOLAE PADURARU, MIHAI DIMITRIU, and VLAD DENIS CONSTANTIN

Subjects
dual mesh, recurrence, incisional hernia, Medicine, Medicine (General), R5-920
Abstract

Repairing an incisional ventral hernia represents a challenge for the surgeon. The high recurrence rates observed during hernia repair by tissue approximation leads to development of tension-free procedures by using prosthetic materials. Incisional or ventral hernia is a very common multifactorial pathology that requires surgical intervention to prevent complications, such as pain, discomfort, bowel obstruction or strangulation. To perform the wall repair it is of utmost importance to understand the pathogenesis of the hernia, the anatomy and physiology of the abdominal wall, and surgical techniques. Several repair methods are available, including open suture repair, open mesh repair, the component separation technique, and tissue expansion assisted closure. To perform the ventral hernia repair properly, a full understanding and correct selection of mesh and management of probable complications, such as seroma, bowel injury, enteric fi stulae, and recurrence, is essential. There are lots of scientific debates about an ideal material for mesh parietal repair. In latest years, the tendency is that the continuous decreasing territory of polyester mesh to be slowly replaced by the increasing territory of polypropylene mesh in open procedures for abdominal incisional hernia repair. The goals of incisional hernia repair are the prevention of visceral eventration, incorporation of the abdominal wall in the repair, provision of dynamic muscular support, and restoration of abdominal wall continuity in a tension-free manner. We present the case of a 55 years old woman who had a history of multiple surgical interventions. We performed an open surgical approach, tension free technique using an intraperitoneal dual-mesh.

Published
2019
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8. Research and Science Today No. 1(17)/2019

Author

Snejana SULIMA, Victoria Ogechukwu NWACHUKWU, Chijioke NWACHUKWU, Dorin SAVIN, Hassen NAGESSO, Tariku AYELE, Birhanu NIGUSSIE, Costina SFINTEŞ, Flavius Cristian MĂRCĂU, Paula MUREȘAN, Claudiu – Constantin TALABĂ, Vasile-Cătălin GOLOP, Andrea-Ioana ROȘCA, Angelo PAPA, Iuliu-Marius MORARIU, LE THI NGOC DIEP, Pompiliu-Nicolae CONSTANTIN, Waktole HAILU DUGUMA, Mirabela Rely Odette CURELAR, Najeh LAKHOUA, Corina MEIANU, Carmen PREDA, Gabriel BECHEANU, Cosmin CIORA, Doina PROCA, Mona DUMBRAVA, Alexandru LUPU, Mircea DICULESCU, Bogdan SOCEA, Anca NICA, Alexandru SMARANDA, Alexandru CARÂP, Vlad Dumitru BĂLEANU, Dragoş Virgil DAVIŢOIU, Tiberiu Ştefăniţă ŢENEA-COJAN, Ovidiu BRATU, Vlad CONSTANTIN, Ramona-Mihaela NEDELCUŢĂ, Gigi CĂLIN, Cosmin Alexandru CIORA, and Irene RASANU

Subjects
international relations, engineering, social sciences, law, medicine, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

RESEARCH AND SCIENCE TODAY is a biannual science journal established in 2011. The journal is an informational platform that publishes assessment articles and the results of various scientific research carried out by academics. We provide the authors with the opportunity to create and/or perfect their science writing skills. Thus, each issue of the journal (two per year and at least two supplements) will contain professional articles from any academic field, authored by domestic and international academics. The goal of this journal is to pass on relevant information to undergraduate, graduate, and post-graduate students as well as to fellow academics and researchers; the topics covered are unlimited, considering its multi-disciplinary profile. Regarding the national and international visibility of Research and Science Today, it is indexed in over 30 international databases (IDB) and is present in over 200 online libraries and catalogues; therefore, anybody can easily consult the articles featured in each issue by accessing the databases or simply the website.

Published
2019

11. Probabilistic functional tractography of the human cortex revisited.

Author

Lena Trebaul, Pierre Deman, Viateur Tuyisenge, Maciej Jedynak, Etienne Hugues, David Rudrauf, Manik Bhattacharjee, François Tadel, Blandine Chanteloup-Foret, Carole Saubat, Gina Catalina Reyes Mejia, Claude Adam, Anca Nica, Martin Pail, François Dubeau, Sylvain Rheims, Agnès Trébuchon, Haixiang Wang, and Olivier David 0001

Published
2018
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14. Somatomotor or somatosensory facial manifestations in patients with temporobasal epilepsies

Author

Delphine, Taussig, Olivier, David, Ana Maria, Petrescu, Anca, Nica, Eric, Seigneuret, Georg, Dorfmüller, Mohamed, Choukri, Nozar, Aghakhani, and Viviane, Bouilleret

Subjects
Stereotaxic Techniques, Epilepsy, Epilepsy, Temporal Lobe, Neurology, Seizures, Humans, Electroencephalography, Neurology (clinical), General Medicine, Magnetic Resonance Imaging
Abstract

The semiology of temporo-basal epilepsy has rarely been analysed in the literature. In this paper, we report three patients with proven basal temporal epilepsy with somatomotor or somatosensory facial ictal semiology, highly suggestive of insulo-opercular onset.The three patients had a temporobasal lesion and their drugresistant epilepsy was cured with resection of the lesion (follow-up duration: 7-17 years). We reviewed the medical charts, non-invasive EEG data as well as the stereoelectroencephalography (SEEG) performed in two patients. Quantitative analysis of ictal fast gamma activity was performed for one patient.Early ictal features were orofacial, either somatomotor in two patients or ipsilateral somatosensory in one. The three patients had prior sensations compatible with a temporal lobe onset. Interictal and ictal EEG pointed to the temporal lobe. The propagation of the discharge to the insula and operculum before the occurrence of facial features was seen on SEEG. Facial features occurred 7-20 seconds after electrical onset. Quantitative analysis of six seizures in one patient confirmed the visual analysis, showing statistically significant fast gamma activity originating from basal areas and then propagating to insuloopercular regions after a few seconds.We report three cases of lesional temporo-basal epilepsy responsible for orofacial semiology related to propagation of insulo-opercular ictal discharge. In MRI-negative patients with facial manifestations, this origin should be suspected when EEG is suggestive. These observations may contribute to our understanding of brain networks.

Published
2022

16. Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice

Author

Emmanuel J. Barbeau, Agnès Trébuchon, Sylvain Rheims, Julien Bastin, Marie Denuelle, Lorella Minotti, Philippe Kahane, Petr Marusic, Romane Cecchi, Louis Maillard, Fabien Vinckier, Anca Nica, Jiri Hammer, Mathias Pessiglione, [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Motivation, cerveau et comportement = Motivation, Brain and Behavior [ICM Paris] (MBB), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Paris Cité (UPCité), GHU Paris Psychiatrie et Neurosciences, Charles University [Prague] (CU), CHU Pontchaillou [Rennes], Hôpital de la Timone [CHU - APHM] (TIMONE), Centre de recherche cerveau et cognition (CERCO UMR5549), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Hospices Civils de Lyon (HCL), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), CHU Grenoble, Université Joseph Fourier - Grenoble 1 (UJF)-CHU Grenoble, Barbeau, Emmanuel, Centre Hospitalier Universitaire [Grenoble] (CHU), Motivation, cerveau et comportement = Motivation, Brain and Behavior [Paris] (MBB), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), University Hospital Motol [Prague], Université de Lyon, Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), CHU Toulouse [Toulouse], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
Decision Making, Ventromedial prefrontal cortex, Prefrontal Cortex, [SHS.PSY]Humanities and Social Sciences/Psychology, decision, ventromedial prefrontal cortex, Choice Behavior, broadband gamma, anterior insula, General Biochemistry, Genetics and Molecular Biology, Feedback, Task (project management), [SHS]Humanities and Social Sciences, [SHS.PSY] Humanities and Social Sciences/Psychology, 03 medical and health sciences, Risk-Taking, 0302 clinical medicine, Baseline activity, Mood, Mood state, medicine, Humans, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], reward, 030304 developmental biology, risk, Brain Mapping, 0303 health sciences, Anterior insula, General Immunology and Microbiology, General Neuroscience, oscillatory activity, Brain, General Medicine, electrophysiology, Magnetic Resonance Imaging, Weighting, computational model, Brain state, medicine.anatomical_structure, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SHS] Humanities and Social Sciences, Psychology, 030217 neurology & neurosurgery, Cognitive psychology
Abstract

International audience; Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of subjects (n=30) while they were performing interleaved quiz and choice tasks that were designed to examine how a series of unrelated feedbacks affect decisions between safe and risky options. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that (1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, (2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain vs. loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the evaluation of risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.

Published
2022

19. Epileptogenic zone localization based on partial directed coherence and graph analysis: a case study

Author

Chahira Mahjoub, Sahbi Chaibi, Anca Nica, Abdennaceur Kachouri, Régine Le Bouquin Jeannès, Université de Sfax - University of Sfax, CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche en Information Biomédicale sino-français (CRIBS), Université de Rennes (UR)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), and PHC (Partenariat Hubert Curien) [41711PK, 19G1411]

Subjects
Graph theory, Connectivity, Stereoelectroencephalography, Signal Processing, Partial directed coherence, Epileptogenic zone, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Electrical and Electronic Engineering
Abstract

International audience; The localization of the epileptogenic zone (EZ) is crucial for the successful surgical treatment of epileptic patients who suffer from drug-resistant epilepsy. In this paper, we propose a new approach for EZ localization. The partial directed coherence approach and the outstrength parameter derived from graph theory are used to characterize the synchronization and desynchronization properties of brain structures and to categorize the corresponding channels into three groups referred to as the onset group, early propagation group and late propagation group according to their involvement in the seizure progress. Our results prove the effectiveness of the proposed approach, which corroborates the clinician's visual inspection and makes it possible to identify a set of channels that delimit the epileptogenic zone. The proposed approach for EZ localization can be considered a valuable tool for the successful surgical treatment of epileptic patients that suffer from the type of epilepsy considered.

Published
2022

20. Adaptive behavior and psychiatric comorbidities in KCNB1 encephalopathy

Author

Claire Bar, Delphine Breuillard, Mathieu Kuchenbuch, Mélanie Jennesson, Gwenaël Le Guyader, Hervé Isnard, Anne Rolland, Diane Doummar, Joel Fluss, Alexandra Afenjar, Patrick Berquin, Anne De Saint Martin, Sophie Dupont, Alice Goldenberg, Damien Lederer, Gaétan Lesca, Hélène Maurey, Pierre Meyer, Cyril Mignot, Anca Nica, Sylvie Odent, Alice Poisson, Emmanuel Scalais, Tayeb Sekhara, Pascal Vrielynck, Giulia Barcia, Rima Nabbout, Université de Paris (UP), CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Unité neurovasculaire et troubles cognitifs (Neuvacod), Université de Poitiers, Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université de Picardie Jules Verne (UPJV), Hôpital de Hautepierre [Strasbourg], CHU Charles Foix [AP-HP], CHU Rouen, Normandie Université (NU), Institut NeuroMyoGène (INMG), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Bicêtre, Physiologie & médecine expérimentale du Cœur et des Muscles [U 1046] (PhyMedExp), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), CHU Pontchaillou [Rennes], Centre de référence Maladies Rares CLAD-Ouest [Rennes], Centre for the Diagnosis and management of genetic psychiatric disorders [Bron] (GénoPsy), Centre Hospitalier le Vinatier [Bron], Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Université Paris Cité (UPCité), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)

Subjects
Adult, Developmental and epileptic encephalopathy, Adaptive behavior, Adolescent, Young Adult, 03 medical and health sciences, Behavioral Neuroscience, Shab Potassium Channels, 0302 clinical medicine, KCNB1, Intellectual Disability, Adaptation, Psychological, Humans, Psychometric evaluation, Autism spectrum disorder, Child, 030304 developmental biology, Brain Diseases, 0303 health sciences, Epilepsy, 3. Good health, Neurology, Child, Preschool, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), 030217 neurology & neurosurgery, Parental questionnaires
Abstract

International audience; Aim: KCNB1 encephalopathy encompasses a broad phenotypic spectrum associating intellectual disability, behavioral disturbances, and epilepsies of various severity. Using standardized parental questionnaires, we aimed to capture the heterogeneity of the adaptive and behavioral features in a series of patients with KCNB1 pathogenic variants.Methods: We included 25 patients with a KCNB1 encephalopathy, aged from 3.2 to 34.1 years (median = 10 years). Adaptive functioning was assessed in all patients using the French version of the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) questionnaire. We screened global behavior with the Childhood Behavioral Check-List (CBCL, Achenbach) and autism spectrum disorder (ASD) with the Social Communication Questionnaire (SCQ). We used a cluster analysis to identify subgroups of adaptive profiles.Results: VABS-II questionnaire showed pathological adaptive behavior in all participants with a severity of adaptive deficiency ranging from mild in 8/20 to severe in 7/20. Eight out of 16 were at risk of Attention Problems at the CBCL and 13/18 were at risk of autism spectrum disorder (ASD). The adaptive behavior composite score significantly decreased with age (Spearman’s Rho=-0.72, p

Published
2022

21. Cardiac Autonomic Dysfunction and Risk of Sudden Unexpected Death in Epilepsy

Author

William Szurhaj, Alexandre Leclancher, Bertille Perin, Marie Faucanie, Marie-Christine Picot, Julien De Jonckheere, Bertrand Godet, Anca Nica, Philippe Convers, Philippe Derambure, L. Mazzola, CHU Amiens-Picardie, CHirurgie, IMagerie et REgénération tissulaire de l’extrémité céphalique - Caractérisation morphologique et fonctionnelle - UR UPJV 7516 (CHIMERE), Université de Picardie Jules Verne (UPJV), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Lille, CHU Saint-Etienne, Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Limoges, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), CIC Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-CHU Saint-Eloi-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Investigation Clinique - Innovation Technologique de Lille - CIC 1403 - CIC 9301 (CIC Lille), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Saint Eloi (CHRU Montpellier), and Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Adult, Male, medicine.medical_specialty, Primary Dysautonomias, 030204 cardiovascular system & hematology, Unexpected death, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Heart Rate, Internal medicine, Hyperventilation, Heart rate, Medicine, Humans, Sudden Unexpected Death in Epilepsy, 10. No inequality, Retrospective Studies, Baseline values, Receiver operating characteristic, business.industry, Electroencephalography, Heart, Middle Aged, medicine.disease, Sympathetic stimulation, Case-Control Studies, Cardiology, Observational study, Female, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Neurology (clinical), medicine.symptom, business, 030217 neurology & neurosurgery
Abstract

ObjectiveWe aimed to test whether patients who died of sudden unexpected death in epilepsy (SUDEP) had an abnormal cardiac autonomic response to sympathetic stimulation by hyperventilation.MethodsWe conducted a retrospective, observational, case-control study of a group of patients who died of SUDEP and controls who were matched to the patients for epilepsy type, drug resistance, sex, age at EEG recording, age at onset of epilepsy, and duration of epilepsy. We analyzed the heart rate (HR) and HR variability (HRV) at rest and during and after hyperventilation performed during the patient's last EEG recording before SUDEP. In each group, changes over time in HRV indexes were analyzed with linear mixed models.ResultsTwenty patients were included in each group. In the control group, the HR increased and the root mean square of successive RR-interval differences (RMSSD) decreased during the hyperventilation and then returned to the baseline values. In the SUDEP group, however, the HR and RMSSD did not change significantly during or after hyperventilation. A difference in HR between the end of the hyperventilation and 4 minutes after its end discriminated well between patients with SUDEP and control patients (area under the receiver operating characteristic curve 0.870, sensitivity 85%, specificity 75%).ConclusionMost of patients with subsequent SUDEP have an abnormal cardiac autonomic response to sympathetic stimulation through hyperventilation. An index reflecting the change in HR on hyperventilation might be predictive of the risk of SUDEP and could be used to select patients at risk of SUDEP for inclusion in trials assessing protective measures.

Published
2021

22. SUBCAPSULAR HAEMATOMA OF THE SPLEEN - A COMPLICATION OF ACUTE PANCREATITIS

Author

Alexandru C. Smaranda, Vlad Denis Constantin, Ovidiu Gabriel Bratu, Alexandru Carâp, Cristina Bogaciu, Vladimir Ciobotaru, Bogdan Socea, and Anca Nica

Subjects
Pathology, medicine.medical_specialty, business.industry, Inflammation, Spleen, medicine.disease, medicine.anatomical_structure, Splenic Hilum, Splenic infarction, medicine, General Earth and Planetary Sciences, Pancreatitis, Acute pancreatitis, cardiovascular diseases, medicine.symptom, Pancreas, Complication, business, General Environmental Science
Abstract

The intimate relationship of the tail of the pancreas and the splenic hilum makes the spleen vulnerable to the inflammation of the body and the tail of the pancreas. The involvement of the spleen in pancreatitis is increasing and it includes lesions like perisplenic or intrasplenic pseudocysts, subcapsular hematomas, intrasplenic haemorrhage, splenic infarction and splenic rupture. We present the case of a nontraumatic subcapsular haematoma of the spleen in a patient with alcohol related pancreatitis

Published
2020

23. A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials

Author

Jean-Didier, Lemaréchal, Maciej, Jedynak, Lena, Trebaul, Anthony, Boyer, François, Tadel, Manik, Bhattacharjee, Pierre, Deman, Viateur, Tuyisenge, Leila, Ayoubian, Etienne, Hugues, Blandine, Chanteloup-Forêt, Carole, Saubat, Raouf, Zouglech, Gina Catalina, Reyes Mejia, Sébastien, Tourbier, Patric, Hagmann, Claude, Adam, Carmen, Barba, Fabrice, Bartolomei, Thomas, Blauwblomme, Jonathan, Curot, François, Dubeau, Stefano, Francione, Mercedes, Garcés, Edouard, Hirsch, Elizabeth, Landré, Sinclair, Liu, Louis, Maillard, Eeva-Liisa, Metsähonkala, Ioana, Mindruta, Anca, Nica, Martin, Pail, Ana Maria, Petrescu, Sylvain, Rheims, Rodrigo, Rocamora, Andreas, Schulze-Bonhage, William, Szurhaj, Delphine, Taussig, Antonio, Valentin, Haixiang, Wang, Philippe, Kahane, Nathalie, George, Olivier, David, Elisa, Nacci, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Le Centre de Magnétoencéphalographie et d'Electroencéphalographie [CHU Pitié-Salpêtrière] (MEG-EEG), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Service de neurochirurgie pédiatrique [CHU Necker], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Hospital Universitario y Politécnico La Fe [Valencia, Spain], CHU Strasbourg, Centre Hospitalier Sainte Anne [Paris], Jinan University [Guangzhou], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), University Emergency Hospital [Bucharest], Laboratoire Traitement du Signal et de l'Image (LTSI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), University Hospital Brno, AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), IMIM-Hospital del Mar, Generalitat de Catalunya, Freiburg University Medical Center, CHU Lille, Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Tsinghua University [Beijing] (THU), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Università degli Studi di Firenze = University of Florence (UniFI), Centre de recherche cerveau et cognition (CERCO UMR5549), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Hospital Universitari i Politècnic La Fe = University and Polytechnic Hospital La Fe, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universitäts Klinikum Freiburg = University Medical Center Freiburg (Uniklinik), The research leading to these results has received funding from the European Research Councilunder the European Union's Seventh Framework Programme (FP/2007-2013)/ERC GrantAgreement no. 616268 F-TRACT, the European Union’s Horizon 2020 FrameworkProgramme for Research and Innovation under Specific Grant Agreement No. 785907 and945539 (Human Brain Project SGA2 and SGA3), and from the French 'Investissementsd’avenir' programme under grant numbers ANR-11-INBS-0006 and ANR-10-IAIHU-06. PHwas supported by Swiss National Science Foundation grant #CRSII5_170873, ANR-11-INBS-0006,FLI,France Life Imaging(2011), European Project: 616268,EC:FP7:ERC,ERC-2013-CoG,F-TRACT(2014), European Project: 785907,H2020,HBP SGA2(2018), European Project: 945539,H2020,H2020-SGA-FETFLAG-HBP-2019,HBP SGA3(2020), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Gestionnaire, Hal Sorbonne Université, Infrastructures - France Life Imaging - - FLI2011 - ANR-11-INBS-0006 - INBS - VALID, Functional Brain Tractography - F-TRACT - - EC:FP7:ERC2014-08-01 - 2019-07-31 - 616268 - VALID, Human Brain Project Specific Grant Agreement 2 - HBP SGA2 - - H20202018-04-01 - 2020-03-31 - 785907 - VALID, and Human Brain Project Specific Grant Agreement 3 - HBP SGA3 - - H20202020-01-01 - 2023-09-30 - 945539 - VALID

Subjects
neural mass models, 0303 health sciences, Brain Mapping, Epilepsy, cortico-cortical evoked potential, Brain, Bayes Theorem, Electric Stimulation, dynamic causal modelling, 03 medical and health sciences, 0302 clinical medicine, axonal conduction delay, Humans, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], synaptic time constant, Evoked Potentials, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (

Published
2021

24. Stereoelectroencephalography (SEEG) and epilepsy surgery in posttraumatic epilepsy: A multicenter retrospective study

Author

Anca Nica, Fabrice Bartolomei, Agnès Trébuchon, Romain Carron, Alexane Fierain, Luc Valton, Stanislas Lagarde, Aileen McGonigal, Sylvain Rheims, Hélène Catenoix, Hôpital de la Timone [CHU - APHM] (TIMONE), Université Catholique de Louvain = Catholic University of Louvain (UCL), Cliniques Universitaires Saint-Luc [Bruxelles], Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Jonchère, Laurent, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
medicine.medical_specialty, Hemispherectomy, Traumatic brain injury, SEEG, Context (language use), Stereoelectroencephalography, Stereotaxic Techniques, 03 medical and health sciences, Behavioral Neuroscience, Epilepsy, Young Adult, 0302 clinical medicine, Epilepsy surgery, Medicine, Humans, Ictal, 030212 general & internal medicine, Young adult, Retrospective Studies, [SDV.IB] Life Sciences [q-bio]/Bioengineering, business.industry, Retrospective cohort study, Electroencephalography, Focal epilepsy, medicine.disease, Magnetic Resonance Imaging, 3. Good health, Neurology, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Neurology (clinical), Radiology, business, 030217 neurology & neurosurgery
Abstract

International audience; Purpose: Posttraumatic epilepsy (PTE) is a common cause of drug-resistant epilepsy, especially in young adults. Nevertheless, such patients are not common candidates for intracranial presurgical evaluation. We investigated the role of stereoelectroencephalography (SEEG) in defining epileptogenicity and surgical strategy in patients with PTE.Methods: We analyzed ictal SEEG recordings from 18 patients. We determined the seizure onset zone (SOZ) by quantifying the epileptogenicity of the sampled structures, using the \"epileptogenicity index\" (EI). We also identified seizure onset patterns (SOPs) through visual and frequency analysis. Postsurgical outcome was assessed by Engel's classification.Results: The SOZ in PTE was most often located in temporal lobes, followed by frontal lobes. The SOZ was network-organized in the majority of the cases. Half of the SOP did not contain fast discharges. Half of the recordings showed SOZ that were less extensive than the posttraumatic lesions seen on brain magnetic resonance imaging (MRI). All but one operated patient benefited from tailored cortectomy. Only 3 patients were contraindicated for surgical resection due to bilateral epileptogenicity. The overall surgical outcome was good in majority of patients (67% Engel I).Conclusion: Despite the potential risk of bilateral or multifocal epilepsy, patients with PTE may benefit from presurgical assessment in well-selected cases. In this context, SEEG allows guidance of tailored resections adapted to the SOZ.

Published
2020

25. Developmental and epilepsy spectrum of KCNB1 encephalopathy with long‐term outcome

Author

Rima Nabbout, Patrick Berquin, Sylvie Odent, Mathieu Kuchenbuch, Gwenaël Le Guyader, Marieke F. van Dooren, Jamel Chelly, Edor Kabashi, Melanie Jennesson, Giulia Barcia, Cyril Mignot, Tayeb Sekhara, Alexandra Afenjar, Marlène Rio, Anne Rolland, Claude Besmond, Andrés Rodríguez-Sacristán Cascajo, Gaetano Terrone, Isabelle Marey, Boris Keren, Alice Goldenberg, A.S. Lebre, Heather C Mefford, Gaetan Lesca, Anne de Saint Martin, Susanna Negrin, Nathalie Dorison, Hélène Maurey, Agnès Guët, David Geneviève, Marie Claire Y. de Wit, Jeremy L. Freeman, Pierre Meyer, Thierry Billette de Villemeur, Ingrid E. Scheffer, Katherine B. Howell, Anca Nica, Raphael Levy, Martino Montomoli, Renzo Guerrini, Elena Parrini, Candace T. Myers, Bertrand Isidor, Alice Poisson, Marion Gérard, Salima El Chehadeh, Lynette G. Sadleir, Julien Durigneux, Pascal Vrielynck, Amy L Schneider, Emmanuel Scalais, Laurence Hubert, Sophie Dupont, Vesna Brankovic, Damien Lederer, Hervé Isnard, Delphine Breuillard, Claire Bar, Alberto Danieli, Diane Doummar, Arnold Munnich, CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Unité neurovasculaire et troubles cognitifs (Neuvacod), Université de Poitiers, Institut NeuroMyoGène (INMG), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), CHU Strasbourg, Centre for the Diagnosis and management of genetic psychiatric disorders [Bron] (GénoPsy), Centre Hospitalier le Vinatier [Bron], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), CHU Rouen, Normandie Université (NU), CHU Amiens-Picardie, Physiologie & médecine expérimentale du Cœur et des Muscles [U 1046] (PhyMedExp), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Département de génétique médicale, maladies rares et médecine personnalisée [CHRU Montpellier], Cellules Souches, Plasticité Cellulaire, Médecine Régénératrice et Immunothérapies (IRMB), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), CHU Pitié-Salpêtrière [AP-HP], FP7 Ideas: European Research Council, National Health and Medical Research Council, Health Research Council of New Zealand, ANR‐10-IAHU‐01, Agence Nationale de la Recherche, Fondation Bettencourt Schueller, 602531, Seventh Framework Programme, ANR-10-IAHU-0001,Imagine,Institut Hospitalo-Universitaire Imagine(2010), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), ANR‐10IAHU‐01, Agence Nationale de la Recherche, Clinical Genetics, Neurology, and Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1)

Subjects
0301 basic medicine, Adult, Male, Pediatrics, medicine.medical_specialty, Time Factors, Adolescent, autism spectrum disorders, [SDV]Life Sciences [q-bio], Encephalopathy, Severe epilepsy, Imaging data, Cohort Studies, 03 medical and health sciences, Epilepsy, Young Adult, 0302 clinical medicine, Shab Potassium Channels, drug-resistant epilepsy, Intellectual disability, medicine, Missense mutation, Humans, In patient, developmental and epileptic encephalopathy, Child, ComputingMilieux_MISCELLANEOUS, Retrospective Studies, Brain Diseases, sudden unexpected death in epilepsy, developmental encephalopathy, business.industry, Genetic Variation, Infant, Cognition, Electroencephalography, medicine.disease, potassium channels, 3. Good health, 030104 developmental biology, Treatment Outcome, Neurology, Child, Preschool, Female, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

Objective: We aimed to delineate the phenotypic spectrum and long-term outcome of individuals with KCNB1 encephalopathy. Methods: We collected genetic, clinical, electroencephalographic, and imaging data of individuals with KCNB1 pathogenic variants recruited through an international collaboration, with the support of the family association “KCNB1 France.” Patients were classified as having developmental and epileptic encephalopathy (DEE) or developmental encephalopathy (DE). In addition, we reviewed published cases and provided the longterm outcome in patients older than 12 years from our series and from literature. Results: Our series included 36 patients (21 males, median age = 10 years, range = 1.6 months-34 years). Twenty patients (56%) had DEE with infantile onset seizures (seizure onset = 10 months, range = 10 days-3.5 years), whereas 16 (33%) had DE with late onset epilepsy in 10 (seizure onset = 5 years, range = 18 months-25 years) and without epilepsy in six. Cognitive impairment was more severe in individuals with DEE compared to those with DE. Analysis of 73 individuals with KCNB1 pathogenic variants (36 from our series and 37 published individuals in nine reports) showed developmental delay in all with severe to profound intellectual disability in 67% (n = 41/61) and autistic features in 56% (n = 32/57). Long-term outcome in 22 individuals older than 12 years (14 in our series and eight published individuals) showed poor cognitive, psychiatric, and behavioral outcome. Epilepsy course was variable. Missense variants were associated with more frequent and more severe epilepsy compared to truncating variants. Significance: Our study describes the phenotypic spectrum of KCNB1 encephalopathy, which varies from severe DEE to DE with or without epilepsy. Although cognitive impairment is worse in patients with DEE, long-term outcome is poor for most and missense variants are associated with more severe epilepsy outcome. Further understanding of disease mechanisms should facilitate the development of targeted therapies, much needed to improve the neurodevelopmental prognosis.

Published
2020

27. Recursive Model Identification for the Analysis of Cardiovascular Autonomic Modulation during Epileptic Seizure

Author

Virginie Le Rolle, Arnaud Biraben, Benoot Martin, Quentin Gillardin, Anca Nica, Alfredo Hernandez, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Agence Nationale de la Recherche, ANR, FrenchRegional Council of Brittany (Project CRAMSIE), ANR-17-CE19-0001,AdaptVNS,Stimulation auto-adaptative et sujet-spécifique du nerf vague(2017), Martin, Benoît, Stimulation auto-adaptative et sujet-spécifique du nerf vague - - AdaptVNS2017 - ANR-17-CE19-0001 - AAPG2017 - VALID, and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
0301 basic medicine, [SDV]Life Sciences [q-bio], Cardiology, Neurophysiology, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Heart rate, medicine, Autonomic nervous system, Ictal, Root mean squared errors, Autonomic modulation, System-level modeling, Modulation, Ictal bradycardia, Recursive identification algorithms, business.industry, Tikhonov regularization, Neurodegenerative diseases, Mean square error, medicine.disease, [SDV] Life Sciences [q-bio], Identification (information), 030104 developmental biology, Computational modelling, Parameter optimization, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Epileptic seizure, medicine.symptom, business, Neuroscience, 030217 neurology & neurosurgery
Abstract

International audience; Significant cardio-respiratory fluctuations are often observed during and after an epileptic seizure event. The mechanisms underlying these acute modifications are considered to be involved in sudden and unexpected death in epilepsy (SUDEP). We hypothesize that these acute events are mediated by specific dynamics of the autonomic nervous system (ANS). However, the evaluation of the ANS during seizures remains particularly challenging, mainly due to the lack of observability. Computational modelling could help to override these limitations, to assess ANS modulation and to evaluate this hypothesis. In this study, we propose and apply a recursive identification algorithm of a system-level model of the autonomic modulation of the sino-atrial node, integrating a Tikhonov regularization, in order to assess sympathetic and parasympathetic activities during ictal tachy-bradycardia events. We evaluate the feasibility of the method on heart rate (HR) data from 4 seizures observed in the same patient. After parameter optimization and identification we were able to reproduce observed HR data with a maximum root mean squared error equals to 1.7bpm. The estimated autonomic series show sympathetic activation and parasympathetic inhibition at the seizure onset, and a massive vagal discharge as the leading factor to ictal bradycardia. © 2020 Creative Commons; the authors hold their copyright.

Published
2020

28. Dynamic brain effective connectivity analysis based on low-rank canonical polyadic decomposition: application to epilepsy

Author

Pierre-Antoine Chantal, Ahmad Karfoul, Regine Le Bouquin Jeannes, Anca Nica, Laboratoire Traitement du Signal et de l'Image (LTSI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), CHU Pontchaillou [Rennes], Jonchère, Laurent, and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Rank (linear algebra), Computer science, 0206 medical engineering, Physics::Medical Physics, Biomedical Engineering, Context (language use), 02 engineering and technology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Seizures, Tensor (intrinsic definition), Humans, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Effective connectivity, Canonical polyadic decomposition, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Ground truth, Sequence, Brain Mapping, Epilepsy, Quantitative Biology::Neurons and Cognition, business.industry, Partial directed coherence, Brain, Pattern recognition, Electroencephalography, Coherence (statistics), Directed graph, 020601 biomedical engineering, Computer Science Applications, Graph (abstract data type), [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; In this paper, a new method to track brain effective connectivity networks in the context of epilepsy is proposed. It relies on the combination of partial directed coherence with a constrained low-rank canonical polyadic tensor decomposition. With such combination being established, the most dominating directed graph structures underlying each time window of intracerebral electroencephalographic signals are optimally inferred. Obtained time and frequency signatures of inferred brain networks allow respectively to track the time evolution of these networks and to define frequency bands on which they are operating. Besides, the proposed method allows also to track brain connectivity networks through several epileptic seizures of the same patient. Understanding the most dominating directed graph structures over epileptic seizures and investigating their behavior over time and frequency plans are henceforth possible. Since only few but the the most important directed connections in the graph structure are of interest and also for a meaningful interpretation of obtained signatures to be guaranteed, the low-rank canonical polyadic tensor decomposition is prompted respectively by the sparsity and the non-negativity constraints on the tensor loading matrices. The main objective of this contribution is to propose a new way of tracking brain networks in the context of epileptic iEEG data by identifying the most dominant effective connectivity patterns underlying the observed iEEG signals at each time window. The performance of the proposed method is firstly evaluated on simulated data imitating brain activities and secondly on real intracerebral electroencephalographic signals obtained from an epileptic patient. The partial directed coherence-based tensor has been decomposed into space, time, and frequency signatures in accordance with the expected ground truth for each consecutive sequence of the simulated data. The method is also in accordance with the clinical expertise for iEEG epileptic signals, where the signatures were investigated through a simultaneous multi-seizure analysis.

Published
2020

29. Epileptic seizure detection using Multivariate Empirical Mode Decomposition and Support Vector Machines

Author

Regine Le Bouquin Jeannes, Fatma Krikid, Abdennaceur Kachouri, Anca Nica, Chahira Mahjoub, Sahbi Chaibi, Laboratoire d'électronique et des technologies de l'Information [Sfax] (LETI), École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax (ENIS), CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), 19G1411Providence Health Care, PHC: 41711PK, and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, Feature extraction, 02 engineering and technology, 01 natural sciences, Stereoelectroencephalography, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, medicine, Entropy (energy dispersal), 010306 general physics, Epilepsy, Support vector machines, Multivariate empirical mode decomposition, business.industry, Pattern recognition, Support vector machine, Nonlinear system, Statistical classification, ComputingMethodologies_PATTERNRECOGNITION, [SDV.IB]Life Sciences [q-bio]/Bioengineering, 020201 artificial intelligence & image processing, Epileptic seizure, Artificial intelligence, medicine.symptom, business
Abstract

International audience; Automatic detection of epileptic seizures is a very crucial step for diagnosing patients with drug-resistant epilepsies. If visual analysis of long-term electroencephalographic signals is the most reliable technique, automatic seizures detection can help the physicians in comparing seizures and extracting common patterns. In this paper, a new approach to classify background activity and pre-ictal stereoelectroencephalographic signals is proposed. Linear and nonlinear features are extracted directly from the derived intrinsic mode functions of multivariate empirical mode decomposition technique and the classification is performed using support vector machines. The effectiveness of the proposed approach is evaluated using real datasets. Our results show good performance of the proposed approach since an accuracy of 100% is achieved using the first intrinsic mode function and a window size of 1024 samples. © 2020 IEEE.

Published
2020

30. Expanding the genetic and phenotypic relevance of KCNB1 variants in developmental and epileptic encephalopathies: 27 new patients and overview of the literature

Author

Delphine Breuillard, Isabelle Marey, Claire Bar, Tayeb Sekhara, Candace T. Myers, Diane Doummar, Alice Poisson, Hervé Isnard, Nathalie Dorison, Gwenaël Le Guyader, Arnold Munnich, Alexandra Afenjar, Anne de Saint Martin, Jamel Chelly, Gaetan Lesca, Gaetano Terrone, Rima Nabbout, Jeremy L. Freeman, David Geneviève, Sophie Dupont, Cyril Mignot, Katherine B. Howell, Giulia Barcia, Melanie Jennesson, Patrick Berquin, Sylvie Odent, Boris Keren, Ingrid E. Scheffer, Renzo Guerrini, Emmanuel Scalais, Thierry Billette de Villemeur, Martino Montomoli, Agnès Guët, Pierre Meyer, Anca Nica, Anne-Sophie Lebre, Edor Kabashi, Carla Marini, Amy L Schneider, Marion Gérard, Salima El Chehadeh, Heather C Mefford, Lynette G. Sadleir, Imagine - Institut des maladies génétiques (IMAGINE - U1163), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), American Memorial Hospital, Centre hospitalier universitaire de Poitiers (CHU Poitiers), University of Melbourne, CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hospices Civils de Lyon (HCL), A Meyer Children's Hospital, Service de Génétique Cytogénétique et Embryologie [CHU Pitié-Salpêtrière], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (CNC), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Equipe NEMESIS - Centre de Recherches de l'Institut du Cerveau et de la Moelle épinière (NEMESIS-CRICM), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), CHU Amiens-Picardie, Physiologie & médecine expérimentale du Cœur et des Muscles [U 1046] (PhyMedExp), Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Département de génétique médicale, maladies rares et médecine personnalisée [CHRU Montpellier], Hôpital de Hautepierre [Strasbourg], Hôpitaux Universitaires de Strasbourg, Hôpital Louis-Mourier, Colombes, France., Centre Hospitalier de Luxembourg [Luxembourg] (CHL), Rothschild Foundation Hospital, Paris., University of Washington [Seattle], Royal Children's Hospital, University of Melbourne, Melbourne, Victoria, Australia., A.Meyer Children's Hospital, CHU Pontchaillou [Rennes], Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Section of Pediatrics-Child Neurology Unit, Federico II University, 80131, Naples, Italy, Centre Hospitalier Interrégional Edith Cavell (CHIREC), Service de génétique [Reims], Centre Hospitalier Universitaire de Reims (CHU Reims), Institut de Génétique et Développement de Rennes (IGDR), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), CLAD-Ouest, CHU Rennes, France., University of Otago [Dunedin, Nouvelle-Zélande], Pediatric Neurology & Neurogenetics Unit and Laboratories, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI)-Children's Hospital A. Meyer, Epilepsy Research Centre, The Florey Institute of Neurosciences and Mental Health, Heidelberg, Victoria, Australia., Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Centre de référence des épilepsies rares [CHU Pitié-Salpêtrière], Unité fonctionnelle d'épilepsie [CHU Pitié-Salpêtrière], Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-IFR70-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Service de Neurologie [CHU Pitié-Salpêtrière], H2020 European Research Council, Health Research Council of New Zealand, Agence Nationale de la Recherche, Seventh Framework Programme, Fondation Bettencourt Schueller, European Research Council, Bar, C, Barcia, G, Jennesson, M, Le Guyader, G, Schneider, A, Mignot, C, Lesca, G, Breuillard, D, Montomoli, M, Keren, B, Doummar, D, de Villemeur, Tb, Afenjar, A, Marey, I, Gerard, M, Isnard, H, Poisson, A, Dupont, S, Berquin, P, Meyer, P, Genevieve, D, De Saint Martin, A, El Chehadeh, S, Chelly, J, Guët, A, Scalais, E, Dorison, N, Myers, Ct, Mefford, Hc, Howell, Kb, Marini, C, Freeman, Jl, Nica, A, Terrone, G, Sekhara, T, Lebre, A, Odent, S, Sadleir, Lg, Munnich, A, Guerrini, R, Scheffer, Ie, Kabashi, E, Nabbout, R, Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pitié-Salpêtrière [APHP], Service de Génétique et Cytogénétique [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Hôpital Armand Trousseau, Hôpital Armand Trousseau, Paris, France., Centre de Référence déficiences intellectuelles de causes rares, GH Pitie-Salpêtrière-Charles Foix, F-, 75013, Paris, France., Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Département de génétique médicale, maladies rares et médecine personnalisée [CHRU de Montpellier], Centre Hospitalier de Luxembourg, C.H.I.R.E.C, Brussels, Belgium., Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Children's Hospital A. Meyer-University of Florence (UNIFI), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [APHP], Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (ISC-MJ), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Fondation Ophtalmologique Adolphe de Rothschild [Paris], Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Naples Federico II = Università degli studi di Napoli Federico II, Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Università degli Studi di Firenze = University of Florence (UniFI)-Children's Hospital A. Meyer, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Children's Hospital A. Meyer-Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-IFR70-CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Service de Neurologie [CHU Pitié-Salpêtrière]

Subjects
Genotype, [SDV]Life Sciences [q-bio], Biology, Structure-Activity Relationship, 03 medical and health sciences, Epilepsy, Shab Potassium Channels, KCNB1, Intellectual disability, Genetic variation, Genetics, medicine, Humans, Missense mutation, Genetic Predisposition to Disease, Allele, developmental and epileptic encephalopathy, Alleles, Genetic Association Studies, Genetics (clinical), ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, 030305 genetics & heredity, Genetic Variation, medicine.disease, Axon initial segment, Phenotype, Neurodevelopmental Disorders, epilepsy, potassium channel
Abstract

International audience; Developmental and epileptic encephalopathies (DEE) refer to a heterogeneous group of devastating neurodevelopmental disorders. Variants in KCNB1 have been recently reported in patients with early-onset DEE. KCNB1 encodes the alpha subunit of the delayed-rectifier voltage-dependent potassium channel Kv 2.1. We review the 37 previously reported patients carrying 29 distinct KCNB1 variants and significantly expand the mutational spectrum describing 18 novel variants from 27 unreported patients. Most variants occur de novo and mainly consist of missense variants located on the voltage sensor and the pore domain of Kv 2.1. We also report the first inherited variant (p.Arg583*). KCNB1-related encephalopathies encompass a wide spectrum of neurodevelopmental disorders with predominant language difficulties and behavioral impairment. Eighty-five percent of patients developed epilepsies with variable syndromes and prognosis. Truncating variants in the C-terminal domain are associated with a less severe epileptic phenotype. Overall, this report provides an up-to-date review of the mutational and clinical spectrum of KCNB1, strengthening its place as a causal gene in DEEs and emphasizing the need for further functional studies to unravel the underlying mechanisms.

Published
2020

31. On the origin of epileptic High Frequency Oscillations observed on clinical electrodes

Author

Fabrice Wendling, Wassim El Falou, Mohamad Khalil, Anca Nica, Mohamad Shamas, Isabelle Merlet, Pascal Benquet, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Lebanese University [Beirut] (LU), French ANR and GDOS, AZM and SAADE Association (Tripoli, Lebanon), ANR-13-PRTS-0011,VIBRATIONS,Interprétation des signaux électrophysiologiques en épilepsie basée sur un cerveau virtuel(2013), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
0301 basic medicine, Drug Resistant Epilepsy, Depolarizing GABA, High frequency oscillations, Neurotransmission, 03 medical and health sciences, 0302 clinical medicine, Physiology (medical), [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Humans, 3d geometry, Cerebral Cortex, Physics, Brain Mapping, Oscillation, Generation mechanisms, Depth-EEG, Electroencephalography, Depolarization, Synaptic Potentials, Neurophysiology, Sensory Systems, Electrodes, Implanted, Out of phase, 030104 developmental biology, Neurology, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], GABAergic, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), Spatial extent, Neuroscience, Neuronal population model, 030217 neurology & neurosurgery
Abstract

Objective In this study we aim to identify the key (patho)physiological mechanisms and biophysical factors which impact the observability and spectral features of High Frequency Oscillations (HFOs). Methods In order to accurately replicate HFOs we developed virtual-brain/virtual-electrode simulation environment combining novel neurophysiological models of neuronal populations with biophysical models for the source/sensor relationship. Both (patho)physiological mechanisms (synaptic transmission, depolarizing GABAA effect, hyperexcitability) and physical factors (geometry of extended cortical sources, size and position of electrodes) were taken into account. Simulated HFOs were compared to real HFOs extracted from intracerebral recordings of 2 patients. Results Our results revealed that HFO pathological activity is being generated by feed-forward activation of cortical interneurons that produce fast depolarizing GABAergic post-synaptic potentials (PSPs) onto pyramidal cells. Out of phase patterns of depolarizing GABAergic PSPs explained the shape, entropy and spatiotemporal features of real human HFOs. Conclusions The terminology “high-frequency oscillation” (HFO) might be misleading as the fast ripple component (200–600 Hz) is more likely a “high-frequency activity” (HFA), the origin of which is independent from any oscillatory process. Significance New insights regarding the origins and observability of HFOs along depth-EEG electrodes were gained in terms of spatial extent and 3D geometry of neuronal sources.

Published
2018

32. French guidelines on stereoelectroencephalography (SEEG)

Author

Agnès Trébuchon, Vincent Navarro, Hélène Catenoix, Fabrice Bartolomei, Louis Maillard, Aileen McGonigal, Axel Lebas, Francine Chassoux, Delphine Taussig, William Szurhaj, Anne-Sophie Job-Chapron, Maria Paola Valenti-Hirsch, Lorella Minotti, Anca Nica, Mathilde Chipaux, Luc Valton, Vianney Gilard, Stéphane Derrey, Marc Guénot, Jean-Christophe Sol, Julia Scholly, Georg Dorfmüller, Pierre Bourdillon, Marie Denuelle, Stéphane Clemenceau, Jean-Pierre Vignal, Nicolas Reyns, Louise Tyvaert, Bertrand Devaux, Alexandra Montavont, Sophie Colnat-Coulbois, Paul Sauleau, Elisabeth Landré, Jean Isnard, CHU Lille, CNRS, Inserm, Université de Lille, Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189, Troubles cognitifs dégénératifs et vasculaires - U1171, Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI], Troubles cognitifs dégénératifs et vasculaires - U 1171 [TCDV], Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie-Explorations Fonctionnelles, Université de Rennes (UR), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de neuro-chirurgie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre Hospitalier Saint-Anne (GHU Paris), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Service de neurochirurgie [CHU Rouen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Nutrition, inflammation et dysfonctionnement de l'axe intestin-cerveau (ADEN), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institute for Research and Innovation in Biomedicine (IRIB), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Normandie Université (NU)-Normandie Université (NU), Service de psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Hôpital Sainte-Anne, Service de neurochirurgie pédiatrique [Fondation Rothschild, Paris], Fondation Ophtalmologique Adolphe de Rothschild [Paris], Endothélium microcirculatoire cérébral et lésions du système nerveux central au cours du développement (Néovasc), Normandie Université (NU)-Normandie Université (NU)-Institute for Research and Innovation in Biomedicine (IRIB), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Neurologie [Lyon], CHU Lyon, Université de Lyon, [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Strasbourg, Troubles cognitifs dégénératifs et vasculaires - U 1171 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Comportement et noyaux gris centraux = Behavior and Basal Ganglia [Rennes], Université de Rennes (UR)-Université européenne de Bretagne - European University of Brittany (UEB)-CHU Pontchaillou [Rennes]-Institut des Neurosciences Cliniques de Rennes = Institute of Clinical Neurosciences of Rennes (INCR), The authors would like to thank the Société de Neurophysiologie Clinique de Langue Française (SNCLF) and the Ligue Française Contre l’Épilepsie (LFCE) for their logistic and financial support for this work., Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre Hospitalier Saint-Anne, Service de Neurochirurgie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), CHU Toulouse [Toulouse], Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fondation Rothschild, Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université européenne de Bretagne - European University of Brittany (UEB)-CHU Pontchaillou [Rennes]-Institut des Neurosciences Cliniques de Rennes (INCR), Centre de recherche en neurosciences de Lyon ( CRNL ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Neurosciences des Systèmes ( INS ), Aix Marseille Université ( AMU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute ( ICM ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique ( CNRS ), Centre Hospitalier Régional Universitaire de Nancy ( CHRU Nancy ), Nutrition, inflammation et dysfonctionnement de l'axe intestin-cerveau ( ADEN ), Université de Rouen Normandie ( UNIROUEN ), Normandie Université ( NU ) -Normandie Université ( NU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Endothélium microcirculatoire cérébral et lésions du système nerveux central au cours du développement ( Néovasc ), Institute for Research and Innovation in Biomedicine ( IRIB ), Normandie Université ( NU ) -Normandie Université ( NU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Rouen Normandie ( UNIROUEN ), Normandie Université ( NU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Grenoble Institut des Neurosciences ( GIN ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Centre Hospitalier Universitaire [Grenoble] ( CHU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Centre de Recherche en Automatique de Nancy ( CRAN ), Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Troubles cognitifs dégénératifs et vasculaires ( DN2M ), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] ( CHRU Lille ) -INSERM, Centre de recherche cerveau et cognition ( CERCO ), Université Paul Sabatier - Toulouse 3 ( UPS ) -Centre National de la Recherche Scientifique ( CNRS ), Comportement et noyaux gris centraux [Rennes], Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Université européenne de Bretagne ( UEB ) -CHU Pontchaillou [Rennes]-Institut des Neurosciences Cliniques de Rennes (INCR), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Troubles cognitifs dégénératifs et vasculaires - U 1171 - EA 1046 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Centre Hospitalier Saint-Anne, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Cortex et Epilepsie [Paris], Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU), Service de neurochirurgie [Rouen], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Université Paris Descartes - Paris 5 (UPD5)-Hôpital Sainte-Anne, Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Troubles cognitifs dégénératifs et vasculaires (U1171), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-INSERM, Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut des sciences du cerveau de Toulouse. (ISCT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Institut des Neurosciences Cliniques de Rennes (INCR)-CHU Pontchaillou [Rennes]-Université européenne de Bretagne - European University of Brittany (UEB)-Université de Rennes 1 (UR1)

Subjects
Drug Resistant Epilepsy, medicine.medical_specialty, Drug-resistant epilepsy, Adults, Thermocoagulations, Stereo-electroencephalogram, Invasive exploration, Guidelines, Focal epilepsy, Epilepsy surgery, Children, Guidelines as Topic, Stereoelectroencephalography, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Epileptic discharge, 0302 clinical medicine, Physiology (medical), Electrocoagulation, medicine, Humans, Medical physics, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Focal Epilepsies, Electroencephalography, General Medicine, Electrodes, Implanted, 3. Good health, Clinical Practice, Neurology, Current practice, [SDV.IB]Life Sciences [q-bio]/Bioengineering, France, Neurology (clinical), Psychology, International league against epilepsy, 030217 neurology & neurosurgery
Abstract

International audience; Stereoelectroencephalography (SEEG) was designed and developed in the 1960s in France by J. Talairach and J. Bancaud. It is an invasive method of exploration for drug-resistant focal epilepsies, offering the advantage of a tridimensional and temporally precise study of the epileptic discharge. It allows anatomo-electrical correlations and tailored surgeries. Whereas this method has been used for decades by experts in a limited number of European centers, the last ten years have seen increasing worldwide spread of its use. Moreover in current practice, SEEG is not only a diagnostic tool but also offers a therapeutic option, i.e., thermocoagulation. In order to propose formal guidelines for best clinical practice in SEEG, a working party was formed, composed of experts from every French centre with a large SEEG experience (those performing more than 10 SEEG per year over at least a 5 year period). This group formulated recommendations, which were graded by all participants according to established methodology. The first part of this article summarizes these within the following topics: indications and limits of SEEG; planning and management of SEEG; surgical technique; electrophysiological technical procedures; interpretation of SEEG recordings; and SEEG-guided radio frequency thermocoagulation. In the second part, those different aspects are discussed in more detail by subgroups of experts, based on existing literature and their own experience. The aim of this work is to present a consensual French approach to SEEG, which could be used as a basic document for centers using this method, particularly those who are beginning SEEG practice. These guidelines are supported by the French Clinical Neurophysiology Society and the French chapter of the International League Against Epilepsy.

Published
2018

33. High-frequency oscillations are not better biomarkers of epileptogenic tissues than spikes

Author

Isabelle Lambert, Nicolas Roehri, Anca Nica, Francesca Pizzo, Aileen McGonigal, Stanislas Lagarde, Christian-George Bénar, Fabrice Bartolomei, and Bernard Giusiano

Subjects
0301 basic medicine, medicine.diagnostic_test, Receiver operating characteristic analysis, Seizure onset zone, Biology, Electroencephalography, Brain mapping, Stereoelectroencephalography, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Nuclear magnetic resonance, Neurology, medicine, Biomarker (medicine), Intracerebral EEG, Neurology (clinical), 030217 neurology & neurosurgery
Abstract

Objective: High-frequency oscillations (HFOs) in intracerebral EEG (stereoencephalography, SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well the HFOs and the spikes can predict epileptogenic regions with a large spatial sampling at the patient level. Methods: We analyzed non-REM sleep SEEG recordings sampled at 2048 Hz of thirty patients. Ripples (R, 80-250 Hz), fast ripples (FR, 250-500 Hz) and spikes were automatically detected. Rates of these markers and several combinations – spikes co-occurring with HFOs or FRs and cross rate (Spk ⊗ HFO) – were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon sign rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ. Results: A total of 2930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate was better than all the other markers. Moreover, fast ripples, even though very specific, did not delineate all epileptogenic tissues. Interpretation: At the patient level, the performance of the HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure –the cross rate– is a better strategy than using only one marker.

Published
2018

34. Stereoelectroencephalography and surgical outcome in polymicrogyria-related epilepsy: A multicentric study

Author

Petr Marusic, François Dubeau, Hélène Catenoix, Anca Nica, Ioana Mindruta, Fabrice Bartolomei, Louis Maillard, William Szurhaj, Francine Chassoux, Philippe Kahane, Laura Tassi, and Georgia Ramantani

Subjects
0301 basic medicine, medicine.medical_specialty, business.industry, Concordance, Cortical dysplasia, Drug Resistant Epilepsy, medicine.disease, Stereoelectroencephalography, Surgery, 03 medical and health sciences, Epilepsy, 030104 developmental biology, 0302 clinical medicine, Neurology, Schizencephaly, Anesthesia, medicine, Polymicrogyria, Epilepsy surgery, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

Objective We aimed to (1) assess the concordance between various polymicrogyria (PMG) types and the associated epileptogenic zone (EZ), as defined by stereoelectroencephalography (SEEG), and (2) determine the postsurgical seizure outcome in PMG-related drug-resistant epilepsy. Methods We retrospectively analyzed 58 cases: 49 had SEEG and 39 corticectomy or hemispherotomy. Results Mean age at SEEG or surgery was 28.3 years (range, 2-50). PMG was bilateral in 9 (16%) patients and unilateral in 49, including 17 (29%) unilobar, 12 (21%) multilobar, 15 (26%) perisylvian, and only 5 (9%) hemispheric. Twenty-eight (48%) patients additionally had schizencephaly, heterotopia, or focal cortical dysplasia. The SEEG-determined EZ was fully concordant with the PMG in only 8 (16%) cases, partially concordant in 74%, and discordant in 10%. The EZ included remote cortical areas in 21 (43%) cases and was primarily localized in those in 5 (10%), all related to the mesial temporal structures. All but 1 PMG patient with corticectomy or hemispherotomy had a unilateral PMG. At last follow-up (mean, 4.6 years; range, 1-16), 28 (72%) patients remained seizure free. Shorter epilepsy duration to surgery was an independent predictor of seizure freedom. Interpretation PMG-related drug-resistant epilepsy warrants a comprehensive presurgical evaluation, including SEEG investigations in most cases, given that the EZ may only partially overlap with the PMG or include solely remote cortical areas. Seizure freedom is feasible in a large proportion of patients. PMG extent should not deter from exploring the possibility of epilepsy surgery. Our data support the early consideration of epilepsy surgery in this patient group. Ann Neurol 2017;82:781-794.

Published
2017

35. Clinical aspects of seizures in the elderly

Author

Lucie, De Clerck, Anca, Nica, and Arnaud, Biraben

Subjects
Aged, 80 and over, Seizures, Humans, France, Aged
Abstract

The population of France and the world is aging with an increase in the population of people aged over 65 years old. Old people are the second largest population affected by seizures. Hence, neurologists and geriatricians have to be able to identify and treat elderly that suffer from seizures. The current epileptic seizure classification is inappropriate for old people. It is difficult to identify seizures in this group of patients for many reasons and some semiological particularities are required to establish a diagnostic. Within the elderly, first generalized seizures are rare except when epilepsy begins in childhood. The most common type of epilepsy in the elderly is partial seizure but in most cases, the beginning of seizure is difficult to analyze. Seizures clinical description depends on functional areas concerned by the spread of the epileptic discharge. Keep in mind that most of functional areas are interconnected and because of the epileptic discharge speed, clinical expression is polymorph.

Published
2019

36. Epilepsy treatment in the elderly

Author

Arnaud, Biraben, Lucie, De Clerck, and Anca, Nica

Subjects
Aged, 80 and over, Male, Epilepsy, Geriatrics, Humans, Patient Compliance, Anticonvulsants, Female, Comorbidity, Precision Medicine, Aged
Abstract

The population is aging in all countries. The incidence of epilepsy increases with age, leading to an increase in the number of elderly epileptic patients. In addition to the diagnostic problems specific to this population, there are particular treatment difficulties for these age groups. Indeed, in addition to the physiological aging that modifies the metabolism of many drugs is added frequent comorbidities and consequently frequent co-medications. These comorbidities can be neurological, psychiatric, degenerative, but also cardiovascular, renal or hepatic... The availability of many new anti-epileptic drugs has not been very effective in comparison to the old ones. Studies show that new molecules are better tolerated and associated with a better compliance. They are also easier to use, some need just a single daily dose, systematic biological control is not necessary, and they have fewer interactions with co-medications than older anti-epileptic drugs. Thus, at present, these advances make the management of epilepsy more complex but also allow a better personalization of the treatment adapted to a particular patient in this fragile population.

Published
2019

37. FLAWS imaging improves depiction of the thalamic subregions for DBS planning in epileptic patients

Author

Elise Bannier, Giulio Gambarota, Jean-Christophe Ferré, Tobias Kober, Anca Nica, Stephan Chabardes, Claire Haegelen, Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de radiologie et imagerie médicale [Rennes] = Radiology [Rennes], Ecole Polytechnique Fédérale de Lausanne (EPFL), Département de neurochirurgie, Université Joseph Fourier - Grenoble 1 (UJF)-CHU Grenoble, Service de neurochirurgie [Rennes] = Neurosurgery [Rennes], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Bannier, Elise

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, [SDV.IB]Life Sciences [q-bio]/Bioengineering, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

38. Probabilistic functional tractography of the human cortex revisited

Author

Thomas Blauwblomme, Martin Pail, M. Jedynak, Caroline Saubat, Pierre Deman, Luca De Palma, Sinclair Liu, Elizabeth Landre, Rodrigo Rocamora, Edouard Hirsch, Andreas Schulze-Bonhage, Manik Bhattacharjee, Delphine Taussig, Blandine Chanteloup-Foret, François Dubeau, Agnès Trébuchon, William Szurhaj, Stefano Francione, Viateur Tuyisenge, Luc Valton, Lena Trebaul, Louis Maillard, Gina Catalina Reyes Mejia, Anca Nica, Eeva-Liisa Metsähonkala, Ana Maria Petrescu, Antonio Valentin, Mercedes Garcés, Claude Adam, Olivier David, Haixiang Wang, Ioana Mindruta, Sylvain Rheims, Etienne Hugues, Philippe Kahane, François Tadel, David Rudrauf, Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Center for Brain and Cognition, Universitat Pompeu Fabra [Barcelona] (UPF), Institut National de la Santé et de la Recherche Médicale (INSERM), Equipe NEMESIS - Centre de Recherches de l'Institut du Cerveau et de la Moelle épinière (NEMESIS-CRICM), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Pontchaillou [Rennes], Département de mathématiques [Sherbrooke] (UdeS), Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Institut de Neurobiologie de la Méditerranée [Aix-Marseille Université] (INMED - INSERM U1249), Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), Epilepsies, Lesions Cerebrales et Systemes Neuraux de la Cognition, Université de la Méditerranée - Aix-Marseille 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Computer & Information Sciences Department, Fordham University, Fordham University [New York], INSERM U836, équipe 9, Dynamique des réseaux synchrones épileptiques, Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Neurologie et thérapeutique expérimentale, IFR70-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service d'explorations neurologiques et épileptologie, CHU Toulouse [Toulouse], Epilepsy Centre, University Hospital Freiburg, Centre « Claudio-Munari » pour la chirurgie de l'épilepsie et du Parkinson, Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Service de neurologie [Rennes], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Espaces et Sociétés (ESO), Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université d'Angers (UA)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Le Mans Université (UM), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département Neurologie [CHU Toulouse], Pôle Neurosciences [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Le Mans Université (UM)-Université d'Angers (UA)-AGROCAMPUS OUEST-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN), Maquin, Didier, Doctoral Programme in Clinical Veterinary Medicine, Clinicum, Lastentautien yksikkö, Children's Hospital, and HUS Children and Adolescents

Subjects
Male, MOTOR SYSTEM, Connectome/methods, Databases, Factual, Computer science, [SDV]Life Sciences [q-bio], [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Connectivity mapping, Intracranial Electroencephalography, 3124 Neurology and psychiatry, Evoked Potentials/physiology, Epilepsy, 0302 clinical medicine, Neural Pathways, TEMPORAL-LOBE EPILEPSY, Focal Epilepsies, Child, Neocortical epilepsy, Evoked Potentials, IN-VIVO, Cerebral Cortex, 05 social sciences, Cerebral Cortex/diagnostic imaging/physiopathology, Human brain, Middle Aged, HUMAN BRAIN, [SDV] Life Sciences [q-bio], medicine.anatomical_structure, Epilepsy/diagnostic imaging/physiopathology, Neurology, Cerebral cortex, Child, Preschool, Female, Cortico-cortical evoked potentials, PULSE ELECTRICAL-STIMULATION, EFFECTIVE CONNECTIVITY, Tractography, Adult, LANGUAGE SYSTEM, Adolescent, Cognitive Neuroscience, NEOCORTICAL EPILEPSY, 050105 experimental psychology, Electrocorticography/methods, Article, 03 medical and health sciences, Databases, Young Adult, Atlases as Topic, Motor system, medicine, Connectome, Humans, Brain atlas, 0501 psychology and cognitive sciences, Preschool, Factual, business.industry, ICTAL ONSET, 3112 Neurosciences, Probabilistic logic, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Pattern recognition, CORTICOCORTICAL EVOKED-POTENTIALS, 3126 Surgery, anesthesiology, intensive care, radiology, medicine.disease, Neural Pathways/diagnostic imaging, Artificial intelligence, Electrocorticography, business, Intracranial electroencephalogram, 030217 neurology & neurosurgery
Abstract

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human. he research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 616268 “F-TRACT”. All the computations presented in this paper were performed using the CIMENT infrastructure (https://ciment.ujf-grenoble.fr), which is supported by the Rhône-Alpes region (GRANT CPER07_13 CIRA: http://www.ci-ra.org). We thank Bruno Bzenik and Romain Cavagna for their help on the CIMENT facility, and Jean-François Mangin and Cyril Poupon from Neurospin, CEA Saclay, for providing us with the ARCHI DTI database.

Published
2018

39. Estimating the dominant frequency of High Frequency Oscillations in depth-EEG signals

Author

Fabrice Wendling, Isabelle Merlet, Anca Nica, Mohamad Khalil, Mohamad Shamas, Pascal Benquet, and Wassim El Faou

Subjects
Signal processing, medicine.diagnostic_test, business.industry, Pattern recognition, Dominant frequency, Electroencephalography, Epileptogenic zone, Scalp eeg, Radio spectrum, Synchronization (alternating current), Research studies, medicine, Artificial intelligence, business
Abstract

Pathological high-frequency oscillations (HFOs, 200–600 Hz) observed in depth-EEG and on scalp EEG recordings are recognized to be potentially valuable biomarkers of the epileptogenic zone responsible for generating seizures. Many research studies have been dedicated to detect, classify, simulate and understand the underlying mechanisms responsible for their generation. However, broadly classifying the HFOs into classes of wide frequency bands may negatively impact the quality of information carried by these electrophysiological biomarkers. In this paper, we perform a comparative study of various signal processing methods for estimating the dominant frequency of HFOs. The novelty is to make use of a physiologically-plausible computational model in which the HFO frequency can be tuned a priori. Results indicate that non-parametric methods best estimate the frequency of the low-amplitude fast oscillations characteristic of HFOs.

Published
2017

40. A page-hinkley based method for HFOs detection in epileptic depth-EEG

Author

Isabelle Merlet, Nisrine Jrad, Amar Kachenoura, Fabrice Wendling, Anca Nica, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-13-TECS-0013, ANR, Agence Nationale de la Recherche, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), and ANR-13-TECS-0013,FORCE,Utilisation des oscillations neuronales à haute fréquence comme marqueurs fiables des processus cognitifs et de l'épilepsie(2013)

Subjects
Computer science, Page-Hinkley algorithm, 0206 medical engineering, CUSUM, 02 engineering and technology, Electroencephalography, Signal, Interictal High Frequency Oscillations, 03 medical and health sciences, 0302 clinical medicine, Statistics, medicine, Ictal, Sensitivity (control systems), Abrupt change, Signal processing, Epilepsy, medicine.diagnostic_test, business.industry, Pattern recognition, 020601 biomedical engineering, Thresholding, Intracerebral electroencephalo-graphy, Cumulative Sum test, Gabor Transform, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, 030217 neurology & neurosurgery, Energy (signal processing)
Abstract

International audience; Interictal High Frequency Oscillations, (HFOs [30-600 Hz]), recorded from intracerebral electroencephalo-graphy (iEEG) in epileptic brain, showed to be potential biomarkers of epilepsy. Hence, their automatic detection has become a subject of high interest. So far, all detection algorithms consisted of comparing HFOs energy, computed in bands of interest, to a threshold. In this paper, a sequential technique was investigated. Detection was based on a variant of the Cumulative Sum (CUSUM) test, the so-called Page-Hinkley algorithm showing optimal results for detecting abrupt changes in the mean of a normal random signal. Experiments on simulated and real datasets showed the good performance of the method in terms of sensitivity and false detection rate. Compared to the classical thresholding, Page-Hinkley showed better performance.

Published
2017

41. High-frequency oscillations are not better biomarkers of epileptogenic tissues than spikes

Author

Nicolas, Roehri, Francesca, Pizzo, Stanislas, Lagarde, Isabelle, Lambert, Anca, Nica, Aileen, McGonigal, Bernard, Giusiano, Fabrice, Bartolomei, and Christian-George, Bénar

Subjects
Adult, Male, Automation, Brain Mapping, Epilepsy, Predictive Value of Tests, Seizures, Humans, Electroencephalography, Female, Sleep, Slow-Wave, Biomarkers
Abstract

High-frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level.We analyzed non-REM sleep SEEG recordings sampled at 2,048Hz of 30 patients. Ripples (Rs; 80-250Hz), fast ripples (FRs; 250-500Hz), and spikes were automatically detected. Rates of these markers and several combinations-spikes co-occurring with HFOs or FRs and cross-rate (Spk⊗HFO)-were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon signed-rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ.A total of 2,930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate, was better than all the other markers. Moreover, fast ripples, even though very specific, were not delineating all epileptogenic tissues.At the patient level, the performance of HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure-the cross-rate-is a better strategy than using only one marker. Ann Neurol 2018;83:84-97.

Published
2017

42. Stereoelectroencephalography and surgical outcome in polymicrogyria-related epilepsy: A multicentric study

Author

Louis Georges, Maillard, Laura, Tassi, Fabrice, Bartolomei, Hélène, Catenoix, François, Dubeau, William, Szurhaj, Philippe, Kahane, Anca, Nica, Petr, Marusic, Ioana, Mindruta, Francine, Chassoux, and Georgia, Ramantani

Subjects
Adult, Male, Drug Resistant Epilepsy, Adolescent, Brain, Electroencephalography, Middle Aged, Young Adult, Treatment Outcome, Polymicrogyria, Child, Preschool, Humans, Female, Child, Current Literature In Clinical Science, Retrospective Studies
Abstract

We aimed to (1) assess the concordance between various polymicrogyria (PMG) types and the associated epileptogenic zone (EZ), as defined by stereoelectroencephalography (SEEG), and (2) determine the postsurgical seizure outcome in PMG-related drug-resistant epilepsy.We retrospectively analyzed 58 cases: 49 had SEEG and 39 corticectomy or hemispherotomy.Mean age at SEEG or surgery was 28.3 years (range, 2-50). PMG was bilateral in 9 (16%) patients and unilateral in 49, including 17 (29%) unilobar, 12 (21%) multilobar, 15 (26%) perisylvian, and only 5 (9%) hemispheric. Twenty-eight (48%) patients additionally had schizencephaly, heterotopia, or focal cortical dysplasia. The SEEG-determined EZ was fully concordant with the PMG in only 8 (16%) cases, partially concordant in 74%, and discordant in 10%. The EZ included remote cortical areas in 21 (43%) cases and was primarily localized in those in 5 (10%), all related to the mesial temporal structures. All but 1 PMG patient with corticectomy or hemispherotomy had a unilateral PMG. At last follow-up (mean, 4.6 years; range, 1-16), 28 (72%) patients remained seizure free. Shorter epilepsy duration to surgery was an independent predictor of seizure freedom.PMG-related drug-resistant epilepsy warrants a comprehensive presurgical evaluation, including SEEG investigations in most cases, given that the EZ may only partially overlap with the PMG or include solely remote cortical areas. Seizure freedom is feasible in a large proportion of patients. PMG extent should not deter from exploring the possibility of epilepsy surgery. Our data support the early consideration of epilepsy surgery in this patient group. Ann Neurol 2017;82:781-794.

Published
2017

43. Automatic Detection and Classification of High-Frequency Oscillations in Depth-EEG Signals

Author

Anca Nica, Isabelle Merlet, Amar Kachenoura, Nisrine Jrad, Fabrice Bartolomei, Arnaud Biraben, Fabrice Wendling, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Neurosciences des Systèmes (INS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), ANR-13-TECS-0013, ANR, Agence Nationale de la Recherche, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and ANR-13-TECS-0013,FORCE,Utilisation des oscillations neuronales à haute fréquence comme marqueurs fiables des processus cognitifs et de l'épilepsie(2013)

Subjects
Support Vector Machine, Gabor filters, 0206 medical engineering, Feature extraction, Biomedical Engineering, 02 engineering and technology, Gabor transform, Electroencephalography, Sensitivity and Specificity, Pattern Recognition, Automated, 03 medical and health sciences, 0302 clinical medicine, intracerebral electroencephalography (iEEG), signal detection, Biological Clocks, Oscillometry, medicine, Humans, Mathematics, Ground truth, interictal high-frequency oscillations (HFOs), signal classification, Epilepsy, medicine.diagnostic_test, business.industry, Detector, Brain, Reproducibility of Results, Pattern recognition, 020601 biomedical engineering, Brain Waves, Support vector machine, support vector machines (SVM), Pattern recognition (psychology), [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, Energy (signal processing), Algorithms
Abstract

International audience; Goal: Interictal high-frequency oscillations (HFOs [30-600 Hz]) have proven to be relevant biomarkers in epilepsy. In this paper, four categories of HFOs are considered: Gamma ([30-80 Hz]), high-gamma ([80-120 Hz]), ripples ([120-250 Hz]), and fast-ripples ([250-600 Hz]). A universal detector of the four types of HFOs is proposed. It has the advantages of 1) classifying HFOs, and thus, being robust to inter and intrasubject variability; 2) rejecting artefacts, thus being specific. Methods : Gabor atoms are tuned to cover the physiological bands. Gabor transform is then used to detect HFOs in intracerebral electroencephalography (iEEG) signals recorded in patients candidate to epilepsy surgery. To extract relevant features, energy ratios, along with event duration, are investigated. Discriminant ratios are optimized so as to maximize among the four types of HFOs and artefacts. A multiclass support vector machine (SVM) is used to classify detected events. Pseudoreal signals are simulated to measure the performance of the method when the ground truth is known. Results: Experiments are conducted on simulated and on human iEEG signals. The proposed method shows high performance in terms of sensitivity and false discovery rate. Conclusion: The methods have the advantages of detecting and discriminating all types of HFOs as well as avoiding false detections caused by artefacts. Significance: Experimental results show the feasibility of a robust and universal detector. © 1964-2012 IEEE.

Published
2017

44. Identification of interictal epileptic networks from dense-EEG

Author

Aya Kabbara, Anca Nica, Ahmad Mheich, Mahmoud Hassan, Isabelle Merlet, Fabrice Wendling, Arnaud Biraben, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre AZM pour la Recherche en Biotechnologie et ses Applications, Université Libanaise, Service de neurologie [Rennes], Université de Rennes (UR), CHU Pontchaillou [Rennes], 10-LABX-07-01, ANR, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), and Université de Rennes 1 (UR1)

Subjects
Matching (graph theory), Computer science, Context (language use), Electroencephalography, Machine learning, computer.software_genre, 050105 experimental psychology, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Similarity (network science), medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Ictal, Epileptic networks, Dense-EEG source connectivity, Brain Mapping, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, 05 social sciences, Brain, Pattern recognition, Mutual information, medicine.disease, Phase synchronization, Neurology, Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Neurons and Cognition (q-bio.NC), Neurology (clinical), Artificial intelligence, Anatomy, Nerve Net, business, computer, 030217 neurology & neurosurgery, Algorithms
Abstract

Epilepsy is a network disease. The epileptic network usually involves spatially distributed brain regions. In this context, noninvasive M/EEG source connectivity is an emerging technique to identify functional brain networks at cortical level from noninvasive recordings. In this paper, we analyze the effect of the two key factors involved in EEG source connectivity processing: i) the algorithm used in the solution of the EEG inverse problem and ii) the method used in the estimation of the functional connectivity. We evaluate four inverse solutions algorithms and four connectivity measures on data simulated from a combined biophysical/physiological model to generate realistic interictal epileptic spikes reflected in scalp EEG. We use a new network-based similarity index (SI) to compare between the network identified by each of the inverse/connectivity combination and the original network generated in the model. The method will be also applied on real data recorded from one epileptic patient who underwent a full presurgical evaluation for drug-resistant focal epilepsy. In simulated data, results revealed that the selection of the inverse/connectivity combination has a significant impact on the identified networks. Results suggested that nonlinear methods for measuring the connectivity are more efficient than the linear one. The wMNE inverse solution showed higher performance than dSPM, cMEM and sLORETA. In real data, the combination (wMNE/PLV) led to a very good matching between the interictal epileptic network identified from noninvasive EEG recordings and the network obtained from connectivity analysis of intracerebral EEG recordings. These results suggest that source connectivity method, when appropriately configured, is able to extract highly relevant diagnostic information about networks involved in interictal epileptic spikes from non-invasive dense-EEG data., Comment: 30 pages, 5 figures

Published
2016
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45. Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data

Author

Gwénaël Birot, Laurent Albera, Arnaud Biraben, Rasheda Arman Chowdhury, Eliane Kobayashi, Fabrice Wendling, Jean-Marc Lina, Christophe Grova, Isabelle Merlet, Anca Nica, Department of Biomedical Engineering [Montréal] (BME), McGill University = Université McGill [Montréal, Canada], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Genève = University of Geneva (UNIGE), McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Service de Neurologie [Rennes] = Neurology [Rennes], CHU Pontchaillou [Rennes], Ecole de Technologie Supérieure [Montréal] (ETS), Concordia University [Montreal], SAVOY FOUNDATION, MOP-133619, CIHR, NSERC Discovery grant, Centres of Excellence for Commercialization of Research (CECR), American Epilepsy Society award, HR-EEG system, French Foundation for Research on Epilepsy (FFRE), Jonchère, Laurent, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Université de Genève (UNIGE)

Subjects
Computer science, Interictal epileptic discharges, Cognitive Neuroscience, Speech recognition, Context (language use), Higher-order statistics, Electroencephalography, 050105 experimental psychology, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, medicine, Humans, 0501 psychology and cognitive sciences, Ictal, Sensitivity (control systems), [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Cerebral Cortex, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Receiver operating characteristic, medicine.diagnostic_test, Higher order statistics, business.industry, Principle of maximum entropy, 05 social sciences, Magnetoencephalography, Pattern recognition, medicine.disease, EEG/MEG source localization, Neurology, 4-ExSo-MUSIC, Neural mass model, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, Maximum entropy on the mean
Abstract

International audience; Electric Source Imaging (ESI) and Magnetic Source Imaging (MSI) of EEG and MEG signals are widely used to determine the origin of interictal epileptic discharges during the pre-surgical evaluation of patients with epilepsy. Epileptic discharges are detectable on EEG/MEG scalp recordings only when associated with a spatially extended cortical generator of several square centimeters, therefore it is essential to assess the ability of source localization methods to recover such spatial extent. In this study we evaluated two source localization methods that have been developed for localizing spatially extended sources using EEG/MEG data: coherent Maximum Entropy on the Mean (cMEM) and 4th order Extended Source Multiple Signal Classification (4-ExSo-MUSIC). In order to propose a fair comparison of the performances of the two methods in MEG versus EEG, this study considered realistic simulations of simultaneous EEG/MEG acquisitions taking into account an equivalent number of channels in EEG (257 electrodes) and MEG (275 sensors), involving a biophysical computational neural mass model of neuronal discharges and realistically shaped head models. cMEM and 4-ExSo-MUSIC were evaluated for their sensitivity to localize complex patterns of epileptic discharges which includes (a) different locations and spatial extents of multiple synchronous sources, and (b) propagation patterns exhibited by epileptic discharges. Performance of the source localization methods was assessed using a detection accuracy index (Area Under receiver operating characteristic Curve, AUC) and a Spatial Dispersion (SD) metric. Finally, we also presented two examples illustrating the performance of cMEM and 4-ExSo-MUSIC on clinical data recorded using high resolution EEG and MEG. When simulating single sources at different locations, both 4-ExSo-MUSIC and cMEM exhibited excellent performance (median AUC significantly larger than 0.8 for EEG and MEG), whereas, only for EEG, 4-ExSo-MUSIC showed significantly larger AUC values than cMEM. On the other hand, cMEM showed significantly lower SD values than 4-ExSo-MUSIC for both EEG and MEG. When assessing the impact of the source spatial extent, both methods provided consistent and reliable detection accuracy for a wide range of source spatial extents (source sizes ranging from 3 to 20 cm2 for MEG and 3 to 30 cm2 for EEG). For both EEG and MEG, 4-ExSo-MUSIC localized single source of large signal-to-noise ratio better than cMEM. In the presence of two synchronous sources, cMEM was able to distinguish well the two sources (their location and spatial extent), while 4-ExSo-MUSIC only retrieved one of them. cMEM was able to detect the spatio-temporal propagation patterns of two synchronous activities while 4-ExSo-MUSIC favored the strongest source activity. Overall, in the context of localizing sources of epileptic discharges from EEG and MEG data, 4-ExSo-MUSIC and cMEM were found accurately sensitive to the location and spatial extent of the sources, with some complementarities. Therefore, they are both eligible for application on clinical data. © 2016 Elsevier Inc.

Published
2016

46. Brain (Hyper)Excitability Revealed by Optimal Electrical Stimulation of GABAergic Interneurons

Author

F.H. Lopes da Silva, Anca Nica, Stiliyan Kalitzin, Olivier Raineteau, D. Cosandier-Rimele, Fabrice Wendling, J. De Montigny, Urs Gerber, Pascal Benquet, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Neurologie [Rennes] = Neurology [Rennes], CHU Pontchaillou [Rennes], Region Bretagne ('EPIGONE' project, CREATE Competitive Call), Swiss National Science Foundation [31-45547.95], and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
0301 basic medicine, Male, [SDV]Life Sciences [q-bio], Neuronal network, cortical-neurons, Local field potential, Hippocampal formation, Electroencephalography, Mice, 0302 clinical medicine, Postsynaptic potential, GABAergic Neurons, slice cultures, medicine.diagnostic_test, Chemistry, General Neuroscience, Pyramidal Cells, Brain, GABAergic interneuron, ictal transition, GABAergic, Female, Adult, mouse model, rat hippocampus, Biophysics, Inhibitory postsynaptic potential, lcsh:RC321-571, 03 medical and health sciences, Young Adult, Extracellular bipolar direct stimulation, Interneurons, Biological neural network, medicine, Animals, Humans, Neurostimulation, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Electrical, Excitability, temporal-lobe epilepsy, Neural Inhibition, Electric Stimulation, Rats, Mice, Inbred C57BL, Electrophysiology, synaptic connections, 030104 developmental biology, computational models, Neurology (clinical), basket cells, Neuroscience, 030217 neurology & neurosurgery
Abstract

International audience; Background: Neurological disorders are often characterized by an excessive and prolonged imbalance between neural excitatory and inhibitory processes. An ubiquitous finding among these disorders is the disrupted function of inhibitory GABAergic interneurons. Objective: The objective is to propose a novel stimulation procedure able to evaluate the efficacy of inhibition imposed by GABAergic interneurons onto pyramidal cells from evoked responses observed in local field potentials (LFPs). Methods: Using a computational modeling approach combined with in vivo and in vitro electrophysiological recordings, we analyzed the impact of electrical extracellular, local, bipolar stimulation (ELBS) on brain tissue. We implemented the ELBS effects in a neuronal population model in which we can tune the excitation-inhibition ratio and we investigated stimulation-related parameters. Computer simulations led to sharp predictions regarding: i) the shape of evoked responses as observed in local field potentials, ii) the type of cells (pyramidal neurons and interneurons) contributing to these field responses and iii) the optimal tuning of stimulation parameters (intensity and frequency) to evoke meaningful responses. These predictions were tested in vivo (mouse). Neurobiological mechanisms were assessed in vitro (hippocampal slices). Results: Appropriately-tuned ELBS allows for preferential activation of GABAergic interneurons. A quantitative neural network excitability index (NNEI) is proposed. It is computed from stimulation-induced responses as reflected in local field potentials. NNEI was used in four patients with focal epilepsy. Results show that it can readily reveal hyperexcitable brain regions. Conclusion: Well-tuned ELBS and NNEI can be used to locally probe brain regions and quantify the (hyper)excitability of the underlying brain tissue. (C) 2016 Elsevier Inc. All rights reserved.

Published
2015

47. Risk factors of postictal generalized EEG suppression in generalized convulsive seizures

Author

Edouard Hirsch, Anca Nica, Fabrice Bartolomei, Louis Maillard, William Szurhaj, Jacques Jonas, Arielle Crespel, Pierre Thomas, Luc Valton, Philippe Kahane, S.D. Rosenberg, Philippe Ryvlin, J Petit, Vincent Navarro, Cécile Marchal, Francine Chassoux, Bertrand de Toffol, Blanca Mercedes, Sylvain Rheims, Veriano Alexandre, Marie Denuelle, Brain Dynamics and Cognition (DYCOG), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Service de Neurophysiologie Clinique, Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Service de neurophysiologie clinique (CHRU Lille), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de Neurologie [Strasbourg], CHU Strasbourg-Hopital Civil, CHU Bordeaux [Bordeaux], Epilepsies de l'Enfant et Plasticité Cérébrale (U1129), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Neuropathologie [Sainte-Anne], Hôpital Sainte-Anne, Mondes Iranien et Indien - UMR 7528, Université Sorbonne Nouvelle - Paris 3-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National des Langues et Civilisations Orientales (Inalco)-Centre National de la Recherche Scientifique (CNRS), Bibliothèque nationale de France, Département des Manuscrits (BnF_MSS), Bibliothèque nationale de France (BnF), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), CHU Pontchaillou [Rennes], Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), [GIN] Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Neurologie [CHU Clermont-Ferrand], CHU Gabriel Montpied [Clermont-Ferrand], CHU Clermont-Ferrand-CHU Clermont-Ferrand-CHU Estaing [Clermont-Ferrand], CHU Clermont-Ferrand, Institut Pascal (IP), SIGMA Clermont (SIGMA Clermont)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Université Catholique de Louvain = Catholic University of Louvain (UCL), Institut Des Épilepsies de l'Enfant et de l'adolescent (CTRS-IDEE), Hospices Civils de Lyon (HCL), Brain Dynamics and Cognition Team (U1028 Inserm - UMR5292 CNRS), Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Toulouse [Toulouse], Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Sorbonne Nouvelle - Paris 3-École pratique des hautes études (EPHE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Grenoble Institut des Neurosciences (GIN), CHU Estaing [Clermont-Ferrand], CHU Clermont-Ferrand-CHU Clermont-Ferrand-CHU Gabriel Montpied [Clermont-Ferrand], Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de neurologie 1 [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), SIGMA Clermont (SIGMA Clermont)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut des sciences du cerveau de Toulouse. (ISCT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), École pratique des hautes études (EPHE)-Institut National des Langues et Civilisations Orientales (Inalco)-Université Sorbonne Nouvelle - Paris 3-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Grenoble-Université Joseph Fourier - Grenoble 1 (UJF), Institut Pascal - Clermont Auvergne (IP), Sigma CLERMONT (Sigma CLERMONT)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), and Université Catholique de Louvain (UCL)

Subjects
endocrine system, Electroencephalography, Tonic (physiology), [SPI.AUTO]Engineering Sciences [physics]/Automatic, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Ictal semiology, health services administration, polycyclic compounds, medicine, Prospective cohort study, 030304 developmental biology, 0303 health sciences, medicine.diagnostic_test, [SCCO.NEUR]Cognitive science/Neuroscience, Odds ratio, medicine.disease, Convulsive Seizures, Anesthesia, Neurology (clinical), sense organs, Psychology, 030217 neurology & neurosurgery, hormones, hormone substitutes, and hormone antagonists, Cohort study
Abstract

International audience; Objective: To identify the clinical determinants of occurrence of postictal generalized EEG suppression (PGES) after generalized convulsive seizures (GCS).Methods: We reviewed the video-EEG recordings of 417 patients included in the REPO2MSE study, a multicenter prospective cohort study of patients with drug-resistant focal epilepsy. According to ictal semiology, we classified GCS into 3 types: tonic-clonic GCS with bilateral and symmetric tonic arm extension (type 1), clonic GCS without tonic arm extension or flexion (type 2), and GCS with unilateral or asymmetric tonic arm extension or flexion (type 3). Association between PGES and person-specific or seizure-specific variables was analyzed after correction for individual effects and the varying number of seizures.Results: A total of 99 GCS in 69 patients were included. Occurrence of PGES was independently associated with GCS type (p < 0.001) and lack of early administration of oxygen (p < 0.001). Odds ratio (OR) for GCS type 1 in comparison with GCS type 2 was 66.0 (95% confidence interval [CI 5.4–801.6]). In GCS type 1, risk of PGES was significantly increased when the seizure occurred during sleep (OR 5.0, 95% CI 1.2–20.9) and when oxygen was not administered early (OR 13.4, 95% CI 3.2–55.9).Conclusion: The risk of PGES dramatically varied as a function of GCS semiologic characteristics. Whatever the type of GCS, occurrence of PGES was prevented by early administration of oxygen.

Published
2015

48. Reconstruction of Depth-EEG Signals: a spatiotemporal model to simulate realistic epileptic activities

Author

Mohamad Khalil, Arnaud Biraben, Isabelle Merlet, Fabrice Wendling, Anca Nica, Mohamad Shamas, Wassim El Faou, Mahmoud Hassan, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre AZM pour la Recherche en Biotechnologie et ses Applications, Université Libanaise, CHU Pontchaillou [Rennes], Service de Neurologie [Rennes] = Neurology [Rennes], Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Jonchère, Laurent

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, medicine.diagnostic_test, Computer science, business.industry, Pattern recognition, 010103 numerical & computational mathematics, Electroencephalography, Machine learning, computer.software_genre, 01 natural sciences, Stereoelectroencephalography, 03 medical and health sciences, 0302 clinical medicine, medicine, In patient, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, 0101 mathematics, business, computer, Source model, 030217 neurology & neurosurgery
Abstract

International audience; The aim of this work is to interpret the signals recorded by depth-EEG electrodes in epileptic patients. In particular we focused on understanding the relationship that links between recorded SEEG signals and the underlying epileptic neural populations. For this purpose, we used an extended spatiotemporal source model and solved the forward problem to calculate the contribution of the source activity on each contact of the inserted electrodes. As a result we could infer from different configurations of the sources the effect of some parameters on the collected signals. The results of our study show that relying on realistic simulations can help to better understand electrophysiological signals collected in patients with epilepsy.

Published
2015

49. Classification of High Frequency Oscillations in Epileptic Intracerebral EEG

Author

Christian G. Bénar, Amar Kachenoura, Isabelle Merlet, Fabrice Wendling, Anca Nica, Nisrine Jrad, Jonchère, Laurent, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU)

Subjects
Computer science, Speech recognition, 0206 medical engineering, Wavelet Analysis, 02 engineering and technology, Electroencephalography, Sensitivity and Specificity, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Wavelet, medicine, Humans, neocortical epilepsy, Epilepsy surgery, Sensitivity (control systems), [SDV.IB] Life Sciences [q-bio]/Bioengineering, 80-500 hz, medicine.diagnostic_test, Brain, medicine.disease, Linear discriminant analysis, 020601 biomedical engineering, Intracerebral EEG, [SDV.IB]Life Sciences [q-bio]/Bioengineering, 030217 neurology & neurosurgery, Energy (signal processing)
Abstract

International audience; High Frequency Oscillations (HFOs 40-500 Hz), recorded from intracerebral electroencephalography (iEEG) in epileptic patients, are categorized into four distinct sub-bands (Gamma, High-Gamma, Ripples and Fast Ripples). They have recently been used as a reliable biomarker of epileptogenic zones. The objective of this paper is to investigate the possibility of discriminating between the different classes of HFOs which physiological/pathological value is critical for diagnostic but remains to be clarified. The proposed method is based on the definition of a relevant feature vector built from energy ratios (computed using Wavelet Transform-WT) in a-priori- defined frequency bands. It makes use of a multiclass Linear Discriminant Analysis (LDA) and is applied to iEEG signals recorded in patients candidate to epilepsy surgery. Results obtained from bootstrap on training/test datasets indicate high performances in terms of sensitivity and specificity

Published
2015

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