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Abstract #0036

Finite Number of Brain Network Configurations Revealed from Time-Varying Connectivity Assessment of Resting State fMRI

Hao Jia1, Xiaoping P. Hu2, Gopikrishna Deshpande1, 3

1AU MRI research center, ECE dept., Auburn University, Auburn, AL, United States; 2Coulter Dept. of Biomedical Engineering, Georgia Institute of Technology & Emory Univeristy, Atlanta, GA, United States; 3Dept. of Psychology, Auburn University, Auburn, AL, United States

We assume connectivity dynamics derived from fMRI have finite, quasi-stable configurations based on previous EEG/fMRI evidence. We tested this using a unified framework involving dynamic estimation of whole brain functional connectivity (FC) and effective connectivity (EC), evolutionary clustering and segmentation into finite number of patterns. Sliding window method was used to determine FC and dynamic granger method was used for EC. Result evidenced above hypothesis and there are 2-3 dominant modes for both FC and EC. Main FC modes feature default mode network, visual, sub-cortical and motor networks, while sensory regions to frontal cortex interaction is revealed by EC modes.