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Abstract #3717

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

Soroush Arabshahi1, Dmitry S. Novikov2, Andrew F. Laine1, and Yvonne W. Lui2
1Biomedical Engineering, Columbia University, New York, NY, United States, 2Department of Radiology, New York University, New York, NY, United States

Synopsis

Keywords: Functional Connectivity, fMRI (resting state)

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.

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Keywords