D 2019

Stable EEG Spatiospectral Sources Using Relative Power as Group-ICA Input

LABOUNEK, R., D.A. BRIDWELL, Radek MAREČEK, Martin LAMOŠ, Michal MIKL et. al.

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

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20601 Medical engineering

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14740/19:00113467

Organization unit

Central European Institute of Technology

ISSN

UT WoS

000449742700022

Keywords in English

EEG; Spatiospectral ICA; Multisubject blind source separation

Tags

Tags

International impact, Reviewed
Změněno: 1/4/2020 15:46, Mgr. Pavla Foltynová, Ph.D.

Abstract

V originále

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 project
Name: Velká infrastruktura CESNET (Acronym: VI CESNET)
Investor: Ministry of Education, Youth and Sports of the CR