PERFORM Publications

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Title		Authors	PubMed ID
1	MATES: A tool for appraising the completeness with which a meta-analysis has been reported	Morrison K; Pottier P; Pollo P; Ricolfi L; Williams C; Yang Y; Beillouin D; Cardoso SJ; Ferreira V; Gallagher B; Gan JL; Hao G; Keikha M; Kozlowsky-Suzuki B; Kiran Kumara TM; Latterini F; Leverkus AB; Macartney EL; Manrique SM; Martinig AR; Mizuno A; Nanayakkara S; Ntzani E; Ouédraogo DY; Pursell E; Simpson Z; Sleight H; Woon KS; Xia Z; Ghannad M; Grames E; Hennessy EA; IntHout J; Moher D; O' Dea RE; Page MJ; Whaley P; Lagisz M; Nakagawa S;	41411971 BIOLOGY
2	Open-source platforms to investigate analytical flexibility in neuroimaging	Sanz-Robinson J; Wang M; McPherson B; Chatelain Y; Kennedy D; Glatard T; Poline JB;	40800896 ENCS
3	Infants' Social Evaluation of Helpers and Hinderers: A Large-Scale, Multi-Lab, Coordinated Replication Study	Lucca K; Yuen F; Wang Y; Alessandroni N; Allison O; Alvarez M; Axelsson EL; Baumer J; Baumgartner HA; Bertels J; Bhavsar M; Byers-Heinlein K; Capelier-Mourguy A; Chijiiwa H; Chin CS; Christner N; Cirelli LK; Corbit J; Daum MM; Doan T; Dresel M; Exner A; Fei W; Forbes SH; Franchin L; Frank MC; Geraci A; Giraud M; Gornik ME; Wiesmann CG; Grossmann T; Hadley IM; Havron N; Henderson AME; Matzner EH; Immel BA; Jankiewicz G; Jedryczka W; Kanakogi Y; Kominsky JF; Lew-Williams C; Liberman Z; Liu L; Liu Y; Loeffler MT; Martin A; Mayor J; Meng X; Misiak M; Moreau D; Nencheva ML; Oña LS; Otálora Y; Paulus M; Pepe B; Pickron CB; Powell LJ; Proft M; Quinn AA; Rakoczy H; Reschke PJ; Roth-Hanania R; Rothmaler K; Schlegelmilch K; Schlingloff-Nemecz L; Schmuckler MA; Schuwerk T; Seehagen S; Sen HH; Shainy MR; Silvestri V; Soderstrom M; Sommerville J; Song HJ; Sorokowski P; Stutz SE; Su Y; Taborda-Osorio H; Tan AWM; Tatone D; Taylor-Partridge T; Tsang CKA; Urbanek A; Uzefovsky F; Visser I; Wertz AE; Williams M; Wolsey K; Wong TT; Woodward AM; Wu Y; Zeng Z; Zimmer L; Hamlin JK;	39600132 PSYCHOLOGY
4	Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics	Mosley JD; Schock TB; Beecher CW; Dunn WB; Kuligowski J; Lewis MR; Theodoridis G; Ulmer Holland CZ; Vuckovic D; Wilson ID; Zanetti KA;	38345679 CHEMBIOCHEM
5	Functional Synthetic Biology	Aldulijan I; Beal J; Billerbeck S; Bouffard J; Chambonnier G; Ntelkis N; Guerreiro I; Holub M; Ross P; Selvarajah V; Sprent N; Vidal G; Vignoni A;	37073284 BIOLOGY
6	File-based localization of numerical perturbations in data analysis pipelines.	Salari A, Kiar G, Lewis L, Evans AC, Glatard T	33269388 ENCS
7	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

Title:	Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.
Authors:	Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C
Link:	https://www.ncbi.nlm.nih.gov/pubmed/29164737?dopt=Abstract
DOI:	10.1002/hbm.23889
Publication:	Human brain mapping
Keywords:	coherent maximum entropy on the mean; fusion of EEG and MEG; interictal epileptic spikes; presurgical evaluation of epilepsy; reproducibility; single trial localization;
PMID:	29164737	Category:	Hum Brain Mapp	Date Added:	2019-06-04
Dept Affiliation:	PERFORM 1 Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada. 2 San Camillo Hospital IRCCS, 80 Via Alberoni, Venice, 30126, Italy. 3 Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada. 4 Ecole de Technologie Supérieure, Montréal, Québec, Canada. 5 Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada. 6 Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.

Description:

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.

Hum Brain Mapp. 2018 02;39(2):880-901

Authors: Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C

Abstract

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG?=?55%, MEG?=?71%, fusion?=?90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.

PMID: 29164737 [PubMed - indexed for MEDLINE]

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