Assessment of Multidimensional Functional Neuroimaging Data Model by Statistical Resampling
نویسندگان
چکیده
Artificially generated functional magnetic resonance imaging (fMRI) data drawn from a block-based visual stimulation paradigm were analyzed by the stochastic neuromorphic extended BS Infomax algorithm [1] implementing spatial independent component analysis (ICA) [2]. Variance estimate based on bootstrap resampling [3] was employed as model selection criterion and reliability assessment of ICA decomposition of neuroimaging data.
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