Keyword search (4,163 papers available)

"EEG" Keyword-tagged 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 Biotuner: A python toolbox integrating music theory and signal processing for harmonic analysis of physiological and natural time series Bellemare-Pepin A; Jerbi K; 41269470
PSYCHOLOGY
3 Assessment of cognitive load in the context of neurosurgery Di Giovanni DA; Kersten-Oertel M; Drouin S; Collins DL; 40650801
PERFORM
4 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
5 Correlations of pilot trainees brainwave dynamics with subjective performance evaluations: insights from EEG microstate analysis Zhao M; Law A; Su C; Jennings S; Bourgon A; Jia W; Larose MH; Bowness D; Zeng Y; 40109507
ENCS
6 A protocol for trustworthy EEG decoding with neural networks Borra D; Magosso E; Ravanelli M; 39549492
ENCS
7 Monitoring pilot trainees' cognitive control under a simulator-based training process with EEG microstate analysis Zhao M; Jia W; Jennings S; Law A; Bourgon A; Su C; Larose MH; Grenier H; Bowness D; Zeng Y; 39428425
ENCS
8 EEG-based study of design creativity: a review on research design, experiments, and analysis Zangeneh Soroush M; Zeng Y; 39148896
ENCS
9 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
10 Sleep spindles predict stress-related increases in sleep disturbances Dang-Vu TT; Salimi A; Boucetta S; Wenzel K; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; 25713529
PERFORM
11 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
12 A Pilot Randomized Trial of Combined Cognitive-Behavioral Therapy and Exercise Training Versus Exercise Training Alone for the Management of Chronic Insomnia in Obstructive Sleep Apnea Cammalleri A; Perrault AA; Hillcoat A; Carrese-Chacra E; Tarelli L; Patel R; Baltzan M; Chouchou F; Dang-Vu TT; Gouin JP; Pepin V; 38663849
PERFORM
13 Loosely controlled experimental EEG datasets for higher-order cognitions in design and creativity tasks Zangeneh Soroush M; Zhao M; Jia W; Zeng Y; 38152489
ENCS
14 The effects of acute exercise and a nap on heart rate variability and memory in young sedentary adults Mograss M; Frimpong E; Vilcourt F; Chouchou F; Zvionow T; Dang-Vu TT; 37855092
PERFORM
15 The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; 37675803
CONCORDIA
16 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
17 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
18 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
19 EEG complexity during mind wandering: A multiscale entropy investigation Cnudde K; Kim G; Murch WS; Handy TC; Protzner AB; Kam JWY; 36621593
CONCORDIA
20 Neural evidence for age-related deficits in the representation of state spaces Ruel A; Bolenz F; Li SC; Fischer A; Eppinger B; 35510942
PERFORM
21 DF-SSmVEP: Dual Frequency Aggregated Steady-State Motion Visual Evoked Potential Design with Bifold Canonical Correlation Analysis Karimi R; Mohammadi A; Asif A; Benali H; 35408182
ENCS
22 Data-driven beamforming technique to attenuate ballistocardiogram artefacts in electroencephalography-functional magnetic resonance imaging without detecting cardiac pulses in electrocardiography recordings Uji M; Cross N; Pomares FB; Perrault AA; Jegou A; Nguyen A; Aydin U; Lina JM; Dang-Vu TT; Grova C; 34101939
PERFORM
23 Arcuate fasciculus architecture is associated with individual differences in pre-attentive detection of unpredicted music changes Vaquero L; Ramos-Escobar N; Cucurell D; François C; Putkinen V; Segura E; Huotilainen M; Penhune V; Rodríguez-Fornells A; 33454403
MLNP
24 PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research Parent M; Albuquerque I; Tiwari A; Cassani R; Gagnon JF; Lafond D; Tremblay S; Falk TH; 33363449
PERFORM
25 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
26 Brain Rhythms During Sleep and Memory Consolidation: Neurobiological Insights. Marshall L, Cross N, Binder S, Dang-Vu TT 31799908
PERFORM
27 Speech perception in tinnitus is related to individual distress level - A neurophysiological study. Jagoda L, Giroud N, Neff P, Kegel A, Kleinjung T, Meyer M 30031353
PSYCHOLOGY
28 Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study. Bénar CG, Grova C, Jirsa VK, Lina JM 31292816
PERFORM
29 Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Vorwerk J, Aydin Ü, Wolters CH, Butson CR 31231178
PERFORM
30 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
31 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
32 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
33 Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study. Aydin Ü, Rampp S, Wollbrink A, Kugel H, Cho J-, Knösche TR, Grova C, Wellmer J, Wolters CH 28510905
PERFORM
34 Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy. Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C 29164737
PERFORM
35 Cortical reactivations during sleep spindles following declarative learning. Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT 30928690
PERFORM
36 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:EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy
Authors:Afnan JCai ZLina JMAbdallah CDelaire EAvigdor TRos VHedrich Tvon Ellenrieder NKobayashi EFrauscher BGotman JGrova C
Link:https://pubmed.ncbi.nlm.nih.gov/38994740/
DOI:10.1002/hbm.26720
Publication:Human brain mapping
Keywords:HD-EEGMEGdeep brain activityepilepsysource imaging
PMID:38994740 Category: Date Added:2024-07-12
Dept Affiliation: SOH
1 Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada.
2 Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada.
3 Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada.
4 Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada.
5 Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec, Canada.
6 Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada.
7 Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
8 Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada.

Description:

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.





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