Characterizing Spatiotemporal Resting-State fMRI Using Dynamic High-Angular-Resolution Correlation Functions

Motivation: Traditional functional connectivity methods often overlook spatiotemporal dynamics in resting-state fMRI, limiting our understanding of brain activity patterns over time. Goal(s): Our aim is to characterize these dynamics via high-angular-resolution correlation functions and demonstrate potential applications of this enhanced characterization. Approach: We processed resting-state fMRI images using a modified preprocessing pipeline, and applied a novel method to measure BOLD signal propagation. This measurement enables us to identify sources and sinks of activity and track dynamic functional patterns. Results: We demonstrated two main applications of our method: identifying dynamic sources and sinks in the BOLD signal and performing tractography to map its propagation pathways. Impact: Our characterization method introduces a novel approach for analyzing resting-state fMRI, offering valuable insights for both research and clinical applications.