Keyword search (4,163 papers available)

"Source imaging" Keyword-tagged Publications:

Title Authors PubMed ID
1 Sleep magnetoencephalography enhances detection and source imaging of seizures and fast oscillations in focal cortical dysplasia Heers M; Afnan J; Braun C; Grova C; Altenmüller DM; Steinhoff BJ; Dümpelmann M; Demerath T; Urbach H; Ethofer S; Siegel M; Schulze-Bonhage A; Lerche H; Li Hegner Y; 41804684
PERFORM
2 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
3 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
4 Dynamic networks differentiate the language ability of children with cochlear implants Koirala N; Deroche MLD; Wolfe J; Neumann S; Bien AG; Doan D; Goldbeck M; Muthuraman M; Gracco VL; 37409105
PSYCHOLOGY
5 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
6 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
7 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
8 Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter Hamid L; Habboush N; Stern P; Japaridze N; Aydin Ü; Wolters CH; Claussen JC; Heute U; Stephani U; Galka A; Siniatchkin M; 33250282
PERFORM
9 Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients Pellegrino G, Xu M, Alkuwaiti A, Porras-Bettancourt M, Abbas G, Lina JM, Grova C, Kobayashi E, 32582009
PERFORM
10 Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients. Pellegrino G, Hedrich T, Porras-Bettancourt M, Lina JM, Aydin Ü, Hall J, Grova C, Kobayashi E 32386115
PERFORM
11 Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Heers M, Chowdhury RA, Hedrich T, Dubeau F, Hall JA, Lina JM, Grova C, Kobayashi E 25609211
PERFORM
12 Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy. Grova C, Aiguabella M, Zelmann R, Lina JM, Hall JA, Kobayashi E 26931511
PERFORM
13 Source localization of the seizure onset zone from ictal EEG/MEG data. Pellegrino G, Hedrich T, Chowdhury R, Hall JA, Lina JM, Dubeau F, Kobayashi E, Grova C 27059157
PERFORM
14 Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method. Pellegrino G, Hedrich T, Chowdhury RA, Hall JA, Dubeau F, Lina JM, Kobayashi E, Grova C 29024165
PERFORM
15 Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C 28619655
PERFORM

 

Title:How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG
Authors:Wei XAfnan JAvigdor Tvon Ellenrieder NDelaire ÉRoyer JHo AMinato ESchiller KJaber KWang YLMoye MBernhardt BCLina JMGrova CFrauscher B
Link:https://pubmed.ncbi.nlm.nih.gov/41687693/
DOI:10.1016/j.neuroimage.2026.121803
Publication:NeuroImage
Keywords:Cortical oscillation analysisHigh-density EEGNormative intracranial EEGSleep/Wake PhysiologySource imagingVigilance states
PMID:41687693 Category: Date Added:2026-02-14
Dept Affiliation: SOH
1 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
2 Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada; Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.
3 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
4 Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.
5 Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada.
6 Multimodal Imaging and Connectome Analysis (MICA) Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
7 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA.
8 Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
9 Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
10 Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada; Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec H3C 1K3, Canada; Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada.
11 Multimodal Functional Imaging Lab, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada; Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada; Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada.
12 Analytical Neurophysiological Lab, Department of Neurology, Duke University, Durham, North Carolina, USA; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Analytical Neurophysiological Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. Electronic address: birgit.frauscher@duke.edu.

Description:

Cortical oscillations across sleep-wake cycles are essential for coordinating functional brain dynamics. High-density electroencephalography (HDEEG) combined with electrical source imaging (ESI) provides a noninvasive approach to map cortical dynamics; however, its ability to capture spatial ongoing oscillations across different vigilance states remains uncertain. Here, we directly compared HDEEG source imaging by comparing it to a normative intracranial EEG (iEEG) atlas from 110 epilepsy patients with electrodes in healthy brain regions (https://mni-open-ieegatlas.research.mcgill.ca/). Wavelet-based Maximum Entropy on the Mean (wMEM) was applied to localize oscillatory patterns using overnight HDEEG recordings from 35 healthy adults (16 females, mean age 31.1±6.3 years). Virtual iEEG (ViEEG) signals were estimated by applying an iEEG forward model to wMEM sources to examine oscillatory patterns across 5 frequency bands, 38 regions, and 4 vigilance states. We found that HDEEG source imaging exhibited comparable spectral patterns of iEEG in low frequencies but overestimated oscillatory activities at high frequencies. Lateral cortical regions exhibited more accurate source estimation than medial regions (p<0.05). After removing the aperiodic components, the spectral alignment between ViEEG and iEEG significantly improved except for N3 sleep (p<0.05). Oscillatory peak patterns in ViEEG reflect state-dependent dynamics that are broadly consistent with iEEG peaks (p<0.05). HDEEG-derived ViEEG and magnetoencephalography-derived ViEEG approximated iEEG spectral features, showing complementary correspondence. These findings reveal that vigilance states significantly shape cortical oscillations by altering their spectral and spatial profiles. Our results establish high-density EEG as a powerful tool for large-scale, noninvasive investigations of human sleep neurophysiology and brain network dynamics.





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University