Exploring task-related variability in fMRI data using fluctuations in power spectrum of simultaneously acquired EEG.
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).


METHODS
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.


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.
Department of Biomedical Engineering, Brno University of Technology, Faculty of Electrical Engineering and Communication, Technická 12, Brno, Czech Republic. Electronic address: labounek@phd.feec.vutbr.cz.
René
R
Labounek
Department of Biomedical Engineering, Brno University of Technology, Faculty of Electrical Engineering and Communication, Technická 12, Brno, Czech Republic.
Martin
M
Lamoš
CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
Radek
R
Mareček
CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
Milan
M
Brázdil
Department of Biomedical Engineering, Brno University of Technology, Faculty of Electrical Engineering and Communication, Technická 12, Brno, Czech Republic.
Jiří
J
Jan
D000328:Adult; D001921:Brain / Q000098:blood supply* / Q000502:physiology*; D001931:Brain Mapping; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D010100:Oxygen; D013057:Spectrum Analysis; D055815:Young Adult
D010100:Oxygen
Absolute and relative power; EEG Regressor Builder; General linear model (GLM); Regressor; Simultaneous EEG-fMRI; Task-related variability; Visual oddball paradigm