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Author(s): Vaquero L; Ramos-Escobar N; Cucurell D; François C; Putkinen V; Segura E; Huotilainen M; Penhune V; Rodríguez-Fornells A;...
The mismatch negativity (MMN) is an event related brain potential (ERP) elicited by unpredicted sounds presented in a sequence of repeated auditory stimuli. The neural sources of the MMN have been ...
Article GUID: 33454403
Author(s): Cross N; Paquola C; Pomares FB; Perrault AA; Jegou A; Nguyen A; Aydin U; Bernhardt BC; Grova C; Dang-Vu TT;...
Sleep deprivation leads to significant impairments in cognitive performance and changes to the interactions between large scale cortical networks, yet the hierarchical organisation of cortical acti...
Article GUID: 33186718
Author(s): Matthews TE, Witek MAG, Lund T, Vuust P, Penhune VB
Neuroimage. 2020 Mar 23;:116768 Authors: Matthews TE, Witek MAG, Lund T, Vuust P, Penhune VB
Article GUID: 32217163
Author(s): Vaquero L; Rousseau PN; Vozian D; Klein D; Penhune V;
Music and language engage the dorsal auditory pathway, linked by the arcuate fasciculus (AF). Sustained practice in these activities can modify brain structure, depending on length of experience but also age of onset (AoO). To study the impact of early expe...
Article GUID: 32119984
Author(s): Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM
Neuroimage. 2019 Nov 09;:116348 Authors: Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM
Article GUID: 31715254
Author(s): Gauthier CJ, Fan AP
Neuroimage. 2019 02 15;187:116-127 Authors: Gauthier CJ, Fan AP
Article GUID: 29544818
Author(s): Padrão G; Penhune V; de Diego-Balaguer R; Marco-Pallares J; Rodriguez-Fornells A;
The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged dur...
Article GUID: 24956067
Author(s): Vaquero L; Ramos-Escobar N; François C; Penhune V; Rodríguez-Fornells A;
Music learning has received increasing attention in the last decades due to the variety of functions and brain plasticity effects involved during its practice. Most previous reports interpreted the differences between music experts and laymen as the result ...
Article GUID: 29929006
Author(s): Baer LH, Park MT, Bailey JA, Chakravarty MM, Li KZ, Penhune VB
Neuroimage. 2015 Apr 01;109:130-9 Authors: Baer LH, Park MT, Bailey JA, Chakravarty MM, Li KZ, Penhune VB
Article GUID: 25583606
Author(s): Tardif CL, Gauthier CJ, Steele CJ, Bazin PL, Schäfer A, Schaefer A, Turner R, Villringer A
Neuroimage. 2016 05 01;131:55-72 Authors: Tardif CL, Gauthier CJ, Steele CJ, Bazin PL, Schäfer A, Schaefer A, Turner R, Villringer A
Article GUID: 26318050
Author(s): Lee K, Lina JM, Gotman J, Grova C
Neuroimage. 2016 07 01;134:434-449 Authors: Lee K, Lina JM, Gotman J, Grova C
Article GUID: 27046111
Author(s): Kroemer NB, Lee Y, Pooseh S, Eppinger B, Goschke T, Smolka MN
Neuroimage. 2019 02 01;186:113-125 Authors: Kroemer NB, Lee Y, Pooseh S, Eppinger B, Goschke T, Smolka MN
Article GUID: 30381245
Author(s): Elmer S; Hänggi J; Vaquero L; Cadena GO; François C; Rodríguez-Fornells A;
Due to the high linguistic and cognitive demands placed on real-time language translation, professional simultaneous interpreters (SIs) have previously been proposed to serve as a reasonable model for evaluating experience-dependent brain properties. Howeve...
Article GUID: 30831314
Author(s): Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT
Neuroimage. 2019 Jul 15;195:104-112 Authors: Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT
Article GUID: 30928690
Author(s): Chowdhury RA, Merlet I, Birot G, Kobayashi E, Nica A, Biraben A, Wendling F, Lina JM, Albera L, Grova C...
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.
Neuroimage. 2016 De...
Article GUID: 27561712
Author(s): Tardif CL, Steele CJ, Lampe L, Bazin PL, Ragert P, Villringer A, Gauthier CJ
Neuroimage. 2017 04 01;149:233-243 Authors: Tardif CL, Steele CJ, Lampe L, Bazin PL, Ragert P, Villringer A, Gauthier CJ
Article GUID: 28159689
Author(s): Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C
Neuroimage. 2017 08 15;157:531-544 Authors: Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C
Article GUID: 28619655
Title: | 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. |
Authors: | Chowdhury RA, Merlet I, Birot G, Kobayashi E, Nica A, Biraben A, Wendling F, Lina JM, Albera L, Grova C |
Link: | www.ncbi.nlm.nih.gov/pubmed/27561712?dopt=Abstract |
Category: | Neuroimage |
PMID: | 27561712 |
Dept Affiliation: | PERFORM
1 Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University , Montreal, Canada. Electronic address: rasheda.chowdhury@mail.mcgill.ca. 2 INSERM, U1099, 35000 Rennes, France; Université de Rennes 1, Laboratoire de Traitement du Signal et de l'Image, 35000 Rennes, France. 3 Department of Fundamental and Clinical Neurosciences, University of Geneva, Switzerland. 4 Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada. 5 INSERM, U1099, 35000 Rennes, France; Université de Rennes 1, Laboratoire de Traitement du Signal et de l'Image, 35000 Rennes, France; Neurology Department, CHU de Rennes, France. 6 Département de Genie Electrique, Ecole de Technologie Supérieure, Canada. 7 INSERM, U1099, 35000 Rennes, France; Université de Rennes 1, Laboratoire de Traitement du Signal et de l'Image, 35000 Rennes, France; INRIA, Centre Inria Rennes - Bretagne Atlantique, 35042 Rennes Cedex, France. 8 Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University , Montreal, Canada; Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada; Physics Dpt., PERFORM Centre, Concordia University, Canada. |
Description: |
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. Neuroimage. 2016 Dec;143:175-195 Authors: Chowdhury RA, Merlet I, Birot G, Kobayashi E, Nica A, Biraben A, Wendling F, Lina JM, Albera L, Grova C Abstract 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 20cm2 for MEG and 3 to 30cm2 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. PMID: 27561712 [PubMed |