LABOUNEK, René, D.A. BRIDWELL, Radek MAREČEK, Martin LAMOŠ, Michal MIKL, Tomáš SLAVÍČEK, Petr BEDNAŘÍK, J. BASTINEC, P. HLUSTIK, Milan BRÁZDIL and J. JAN. Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA (Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA). BRAIN TOPOGRAPHY. DORDRECHT: SPRINGER, 2018, vol. 31, No 1, p. 76-89. ISSN 0896-0267. Available from: https://dx.doi.org/10.1007/s10548-017-0585-8.
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Basic information
Original name Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA
Authors LABOUNEK, René (203 Czech Republic, belonging to the institution), D.A. BRIDWELL (840 United States of America), Radek MAREČEK (203 Czech Republic, belonging to the institution), Martin LAMOŠ (203 Czech Republic, belonging to the institution), Michal MIKL (203 Czech Republic, belonging to the institution), Tomáš SLAVÍČEK (203 Czech Republic, belonging to the institution), Petr BEDNAŘÍK (203 Czech Republic, belonging to the institution), J. BASTINEC (203 Czech Republic), P. HLUSTIK (203 Czech Republic), Milan BRÁZDIL (203 Czech Republic, guarantor, belonging to the institution) and J. JAN (203 Czech Republic).
Edition BRAIN TOPOGRAPHY, DORDRECHT, SPRINGER, 2018, 0896-0267.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30103 Neurosciences
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 3.104
RIV identification code RIV/00216224:14740/18:00100718
Organization unit Central European Institute of Technology
Doi http://dx.doi.org/10.1007/s10548-017-0585-8
UT WoS 000422889300007
Keywords in English EEG; ICA; Spatiospectral patterns; Multi-subject blind source separation; Resting-state; Semantic decision; Visual oddball
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Pavla Foltynová, Ph.D., učo 106624. Changed: 13/3/2019 16:59.
Abstract
Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.
Links
ED1.1.00/02.0068, research and development projectName: CEITEC - central european institute of technology
ED3.2.00/08.0144, research and development projectName: CERIT Scientific Cloud
GAP304/11/1318, research and development projectName: Optimalizace metodiky analýzy a hodnocení simultánního EEG-fMRI u pacientů s farmakorezistentní epilepsií
Investor: Czech Science Foundation
LM2010005, research and development projectName: Velká infrastruktura CESNET (Acronym: VI CESNET)
Investor: Ministry of Education, Youth and Sports of the CR
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