fMRI resting state analysis using empirical mode decomposition

Abstract

© 2016 IEEE. The paper studies connectivity pattern between two functionally specialized brain areas: the primary motor area and the occipital (visual) cortex in the resting state fMRI using empirical mode decomposition (EMD). EMD enables identification of low frequency oscillatory modes in the resting state range [0, 01-0, 1 Hz]. Three frequency modes were determined in the resting state band in 13 subjects with the mean frequencies 0,07Hz, 0,034Hz and 0,016Hz. The temporal correlations among the oscillatory modes were strongest within homologous (corresponding) sources in left and right hemisphere, and weakest between the motor-occipital fMRI signal pairs. The functional connectivity - spatial distribution of temporal correlations in the resting state - has been identified and refined by the oscillatory modes. Connectivity graph obtained across all subjects and all IMFs showed high connectivity rate between homologous areas in the left and right hemisphere and among the visual cortex areas. Combining EMD with the Hilbert transformation may provide an additional tool for exploring correlations between frequency and amplitude ridges in task related problems.