Keyword search (4,163 papers available)

"Aydin Ü" Authored Publications:

Title Authors PubMed ID
1 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
2 An altered balance of integrated and segregated brain activity is a marker of cognitive deficits following sleep deprivation Cross NE; Pomares FB; Nguyen A; Perrault AA; Jegou A; Uji M; Lee K; Razavipour F; Ali OBK; Aydin U; Benali H; Grova C; Dang-Vu TT; 34735431
PERFORM
3 Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean Cai Z; Uji M; Aydin Ü; Pellegrino G; Spilkin A; Delaire É; Abdallah C; Lina JM; Grova C; 34342073
PERFORM
4 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
5 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
6 Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation. Cross N; Paquola C; Pomares FB; Perrault AA; Jegou A; Nguyen A; Aydin U; Bernhardt BC; Grova C; Dang-Vu TT; 33186718
PERFORM
7 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
8 Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients. Aydin Ü, Pellegrino G, Bin Ka'b Ali O, Abdallah C, Dubeau F, Lina JM, Kobayashi E, Grova C 32191632
PERFORM
9 Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Vorwerk J, Aydin Ü, Wolters CH, Butson CR 31231178
PERFORM
10 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
11 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 RAPellegrino GAydin ÜLina JMDubeau FKobayashi EGrova 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 meanfusion of EEG and MEGinterictal epileptic spikespresurgical evaluation of epilepsyreproducibilitysingle 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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