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Segregation and integration are two general principles of the brain's functional architecture. Therefore, brain network analysis is of significant importance in understanding brain function. Critical to brain network construction and analysis is the identification of reliable, reproducible, and accurate network nodes, or Regions of Interest (ROIs). Task-based fMRI has been widely considered as a reliable approach to identify functionally meaningful ROIs in the brain. However, recent studies have shown that factors such as spatial smoothing could considerably shift the locations of detected activation peaks. As a result, structural and functional connectivity patterns can be significantly altered. Here, we propose a novel framework by which to optimize ROI sizes and locations, ensuring that differences between the structural connectivity profiles among a group of subjects is minimized. This framework is based on functional …