Comparing fMRI data processing methods with respect to possible inaccuracy

We present the comparison of several methods to analyze functional magnetic resonance imaging data with respect to some inaccuracy in subject's response (e.g. missing response to stimuli). Approaches based on general linear model, independent component analysis, and combined methods were used t...

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Bibliographic Details
Published in2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP) pp. 496 - 499
Main Authors Mikl, M., Marecek, R., Prikryl, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2012
Subjects
Brain modeling
Data models
Educational institutions
fMRI
GLM
ICA
inaccuracy
Magnetic resonance imaging
Mathematical model
modelling
Noise
Sensitivity
simulations
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Summary:We present the comparison of several methods to analyze functional magnetic resonance imaging data with respect to some inaccuracy in subject's response (e.g. missing response to stimuli). Approaches based on general linear model, independent component analysis, and combined methods were used to analyze both simulated and real data with unknown (real data) and known (simulated data) levels of inaccuracy. Our results suggest combined approaches as the best choice for single subject analyses. No significant differences between the methods were observed for group results.
ISBN:1457721910
9781457721915
ISSN:2157-8672