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Abstract #1141

ROI Atlas Generated from Whole Brain Parcellation of Resting State FMRI Data

Richard Cameron Craddock1,2, George Andrew James3, Paul Edgar Holtzheimer2, Xiaoping P. Hu3, Helen S. Mayberg2

1Electrical and Computer Engineering, Georiga Institute of Technology, Atlanta, GA, United States; 2Psychiatry, Emory University, Atlanta, GA, United States; 3Biomedical Imaging Technology Center, Emory University/Georgia Institute of Technology, Atlanta, GA, United States

Network analysis of resting state fMRI data requires the specification of ROIs. This is a difficult process fraught with error. We propose a method for developing an ROI atlas by whole brain parcellation of resting state data in functinally homogenous, contiguous regions.