LABOUNEK, R., D.A. BRIDWELL, Radek MAREČEK, Martin LAMOŠ, Michal MIKL, Milan BRÁZDIL, J. JAN and P. HLUSTIK. Stable EEG Spatiospectral Sources Using Relative Power as Group-ICA Input. Online. In Lhotska, L Sukupova, L Lackovic, I Ibbott, GS. WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 2. NEW YORK: SPRINGER, 2019, p. 125-128. ISSN 1680-0737. Available from: https://dx.doi.org/10.1007/978-981-10-9038-7_22.
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Basic information
Original name Stable EEG Spatiospectral Sources Using Relative Power as Group-ICA Input
Authors LABOUNEK, R., D.A. BRIDWELL, 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), Milan BRÁZDIL (203 Czech Republic, guarantor, belonging to the institution), J. JAN and P. HLUSTIK.
Edition NEW YORK, WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 2, p. 125-128, 4 pp. 2019.
Publisher SPRINGER
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20601 Medical engineering
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14740/19:00113467
Organization unit Central European Institute of Technology
ISSN 1680-0737
Doi http://dx.doi.org/10.1007/978-981-10-9038-7_22
UT WoS 000449742700022
Keywords in English EEG; Spatiospectral ICA; Multisubject blind source separation
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Pavla Foltynová, Ph.D., učo 106624. Changed: 1/4/2020 15:46.
Abstract
Within the last decade, various blind source separation algorithms (BSS) isolating distinct EEG oscillations were derived and implemented. Group Independent Component Analysis (group-ICA) is a promising tool for decomposing spatiospectral EEG maps across multiple subjects. However, researchers are faced with many preprocessing options prior to performing group-ICA, which potentially influences the results. To examine the influence of preprocessing steps, within this article we compare results derived from group-ICA using the absolute power of spatiospectral maps and the relative power of spatiospectral maps. Within a previous study, we used K-means clustering to demonstrate group-ICA of absolute power spatiospectral maps generates sources which are stable across different paradigms (i.e. resting-state, semantic decision, visual oddball) Within the current study, we compare these maps with those obtained using relative power of spatiospectral maps as input to group-ICA. We find that relative EEG power contains 10 stable spatiospectral patterns which were similar to those observed using absolute power as inputs. Interestingly, relative power revealed two c-band (20-40 Hz) patterns which were present across 3 paradigms, but not present using absolute power. This finding suggests that relative power potentially emphasizes low energy signals which are obscured by the high energy low frequency which dominates absolute power measures.
Links
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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