2015
Exploring task-related variability in fMRI data using fluctuations in power spectrum of simultaneously acquired EEG
LABOUNEK, René; Martin LAMOŠ; Radek MAREČEK; Milan BRÁZDIL; Jiří JAN et al.Základní údaje
Originální název
Exploring task-related variability in fMRI data using fluctuations in power spectrum of simultaneously acquired EEG
Autoři
Vydání
Journal of Neuroscience Methods, Amsterdam, Elsevier Science Ltd, 2015, 0165-0270
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
30000 3. Medical and Health Sciences
Stát vydavatele
Nizozemské království
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 2.053
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14740/15:00080754
Organizační jednotka
Středoevropský technologický institut
UT WoS
EID Scopus
Klíčová slova anglicky
Simultaneous EEG-fMRI; Visual oddball paradigm; Absolute and relative power; Regressor; General linear model (GLM); Task-related variability; EEG Regressor Builder
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 23. 3. 2016 09:36, Mgr. Eva Špillingová
Anotace
V originále
Background: The paper deals with joint analysis of fMRI and scalp EEG data, simultaneously acquired during event-related oddball experiment. The analysis is based on deriving temporal sequences of EEG powers in individual frequency bands for the selected EEG electrodes and using them as regressors in the general linear model (GLM). New method: Given the infrequent use of EEG spectral changes to explore task-related variability, we focused on the aspects of parameter setting during EEG regressor calculation and searched for such parameters that can detect task-related variability in EEG-fMRI data. We proposed a novel method that uses relative EEG power in GLM. Results: Parameter, the type of power value, has a direct impact as to whether task-related variability is detected or not. For relative power, the final results are sensitive to the choice of frequency band of interest. The electrode selection also has certain impact; however, the impact is not crucial. It is insensitive to the choice of EEG power series temporal weighting step. Relative EEG power characterizes the experimental task activity better than the absolute power. Absolute EEG power contains broad spectrum component. Task-related relative power spectral formulas were derived. Comparison with existing methods: For particular set of parameters, our results are consistent with previously published papers. Our work expands current knowledge by new findings in spectral patterns of different brain processes related to the experimental task. Conclusions: To make analysis to be sensitive to task-related variability, the parameters type of power value and frequency band should be set properly. © 2015 Elsevier B.V.
Návaznosti
| GAP304/11/1318, projekt VaV |
|