BookR: School of Health Core Facilities Booking
PubMed Publications| Keyword search (4,163 papers available) |  |
"Frauscher B" Authored Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG | Wei X; Afnan J; Avigdor T; von Ellenrieder N; Delaire É; Royer J; Ho A; Minato E; Schiller K; Jaber K; Wang YL; Moye M; Bernhardt BC; Lina JM; Grova C; Frauscher B; | 41687693 SOH |
| 2 | Personalized biomarkers of multiscale functional alterations in temporal lobe epilepsy | Xie K; Sahlas E; Ngo A; Chen J; Arafat T; Royer J; Zhou Y; Rodríguez-Cruces R; Dascal A; Caldairou B; Fadaie F; Barnett A; Audrain S; Larivière S; Caciagli L; Pana R; Weil AG; Grova C; Frauscher B; Schrader DV; Zhang Z; Concha L; Bernasconi A; Bernasconi N; Bernhardt BC; | 41258102 SOH |
| 3 | Visual Features in Stereo-Electroencephalography to Predict Surgical Outcome: A Multicenter Study | Abdallah C; Thomas J; Aron O; Avigdor T; Jaber K; Doležalová I; Mansilla D; Nevalainen P; Parikh P; Singh J; Beniczky S; Kahane P; Minotti L; Chabardes S; Colnat-Coulbois S; Maillard L; Hall J; Dubeau F; Gotman J; Grova C; Frauscher B; | 40519108 SOH |
| 4 | Spectral and network investigation reveals distinct power and connectivity patterns between phasic and tonic REM sleep | Avigdor T; Peter-Derex L; Ho A; Schiller K; Wang Y; Abdallah C; Delaire E; Jaber K; Travnicek V; Grova C; Frauscher B; | 40394955 SOH |
| 5 | The Awakening Brain is Characterized by a Widespread and Spatiotemporally Heterogeneous Increase in High Frequencies | Avigdor T; Ren G; Abdallah C; Dubeau F; Grova C; Frauscher B; | 40126936 PERFORM |
| 6 | Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology | Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B; | 39608298 SOH |
| 7 | NREM sleep brain networks modulate cognitive recovery from sleep deprivation | Lee K; Wang Y; Cross NE; Jegou A; Razavipour F; Pomares FB; Perrault AA; Nguyen A; Aydin Ü; Uji M; Abdallah C; Anticevic A; Frauscher B; Benali H; Dang-Vu TT; Grova C; | 39005401 PERFORM |
| 8 | EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy | Afnan J; Cai Z; Lina JM; Abdallah C; Delaire E; Avigdor T; Ros V; Hedrich T; von Ellenrieder N; Kobayashi E; Frauscher B; Gotman J; Grova C; | 38994740 SOH |
| 9 | A spatial perturbation framework to validate implantation of the epileptogenic zone | Jaber K; Avigdor T; Mansilla D; Ho A; Thomas J; Abdallah C; Chabardes S; Hall J; Minotti L; Kahane P; Grova C; Gotman J; Frauscher B; | 38897997 SOH |
| 10 | Systematic review of seizure-onset patterns in stereo-electroencephalography: Current state and future directions | Abdallah C; Mansilla D; Minato E; Grova C; Beniczky S; Frauscher B; | 38733701 PERFORM |
| 11 | Consistency of electrical source imaging in presurgical evaluation of epilepsy across different vigilance states | Avigdor T; Abdallah C; Afnan J; Cai Z; Rammal S; Grova C; Frauscher B; | 38217279 PERFORM |
| 12 | Targeted density electrode placement achieves high concordance with traditional high-density EEG for electrical source imaging in epilepsy | Horrillo-Maysonnial A; Avigdor T; Abdallah C; Mansilla D; Thomas J; von Ellenrieder N; Royer J; Bernhardt B; Grova C; Gotman J; Frauscher B; | 37704552 PERFORM |
| 13 | Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas | Afnan J; von Ellenrieder N; Lina JM; Pellegrino G; Arcara G; Cai Z; Hedrich T; Abdallah C; Khajehpour H; Frauscher B; Gotman J; Grova C; | 37149236 PERFORM |
| 14 | Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy | Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; | 37119580 PERFORM |
| 15 | Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data | Abdallah C; Hedrich T; Koupparis A; Afnan J; Hall JA; Gotman J; Dubeau F; von Ellenrieder N; Frauscher B; Kobayashi E; Grova C; | 35473762 PERFORM |
| 16 | Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. | Avigdor T, Abdallah C, von Ellenrieder N, Hedrich T, Rubino A, Lo Russo G, Bernhardt B, Nobili L, Grova C, Frauscher B | 33450578 PERFORM |
| Title: | Visual Features in Stereo-Electroencephalography to Predict Surgical Outcome: A Multicenter Study | ||||
| Authors: | Abdallah C, Thomas J, Aron O, Avigdor T, Jaber K, Doležalová I, Mansilla D, Nevalainen P, Parikh P, Singh J, Beniczky S, Kahane P, Minotti L, Chabardes S, Colnat-Coulbois S, Maillard L, Hall J, Dubeau F, Gotman J, Grova C, Frauscher B | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/40519108/ | ||||
| DOI: | 10.1002/ana.27278 | ||||
| Publication: | Annals of neurology | ||||
| Keywords: | |||||
| PMID: | 40519108 | Category: | Date Added: | 2025-06-16 | |
| Dept Affiliation: |
SOH
1 Montreal Neurological Institute and Hospital, McGill University, Montréal, Québec, Canada. 2 Department of Neurology, Duke University Medical Center, Durham, North Carolina, USA. 3 Department of Biomedical Engineering, Duke Pratt School of Engineering, Durham, North Carolina, USA. 4 Department of Neurology, University Hospital of Nancy, Lorraine University, Nancy, France. 5 Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR, Nancy, France. 6 Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic. 7 Neurophysiology Unit, Institute of Neurosurgery Dr. Asenjo, Santiago, Chile. 8 Epilepsia Helsinki, Full member of ERN EpiCare, Department of Clinical Neurophysiology, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 9 Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA. 10 Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark. 11 Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark. 12 CHU Grenoble Alpes, Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France. 13 Multimodal Functional Imaging Lab, Department of Physics, Concordia School of Health, Concordia University, Montréal, Québec, Canada. 14 Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada. |
||||
Description: |
Objective: Epilepsy surgery needs predictive features that are easily implemented in clinical practice. Previous studies are limited by small sample sizes, lack of external validation, and complex computational approaches. We aimed to identify and validate visually stereo-electroencephalography (SEEG) features with the highest predictive value for surgical outcome, and assess the reliability of their visual extraction. Methods: We included 177 patients with drug-resistant epilepsy who underwent SEEG-guided surgery at 4 epilepsy centers. We assessed the predictive performance of 10 SEEG features from various SEEG periods for surgical outcome, using the area under the receiver operating characteristic curve, and considering resected channels and surgical outcome as the gold standard. Findings were validated externally using balanced accuracy. Six experts, blinded to outcome, evaluated the visual reliability of the optimal feature using interrater reliability, percentage agreement (standard deviation ± SD) and Gwet's kappa (? ± SD). Results: The derivation cohort comprised 100 consecutive patients, each with at least 1-year of postoperative follow up (40% temporal lobe epilepsy; 42% Engel Ia). Spatial co-occurrence of gamma spikes and preictal spikes emerged as the optimal predictive feature of surgical outcome (area under the receiver operating characteristic curve 0.82). Applying the optimized threshold from the derivation cohort, external validation in 2 datasets showed similar performances (balanced accuracy 69.2% and 73.2%). Expert interrater reliability for gamma spikes (percentage agreement, 96% ± 2%; ?, 0.63 ± 0.16) and preictal spikes (percentage agreement, 92% ± 2%; ?, 0.65 ± 0.18) were substantial. Interpretation: Spatial co-occurrence of gamma spikes and preictal spikes predicts surgical outcome. These visually identifiable features may reduce the burden of SEEG analysis by reducing analysis time, and improve outcome by guiding surgical resection margins. ANN NEUROL 2025. |
