III: Small: Modeling Multi-Level Connectivity of Brain Dynamics

Principal Investigator: Ruogu Fang

Sponsor: National Science Foundation

Start Date: October 1, 2019

End Date: September 30, 2022

Amount: $500,000

Abstract

The temporal dynamics of blood flows through the network of cerebral arteries and veins provides a window into the health of the human brain. Since the brain is vulnerable to disrupted blood supply, brain dynamics serves as a crucial indicator for many kinds of neurological diseases such as stroke, brain cancer, and Alzheimer’s disease. Existing efforts at characterizing brain dynamics have predominantly centered on ‘isolated’ models in which data from single-voxel, single-modality, and single-subject are characterized. However, the brain is a vast network, naturally connected on structural and functional levels, and multimodal imaging provides complementary information on this natural connectivity. Thus, the current isolated models are deemed not capable of offering the platform necessary to enable many of the potential advancements in understanding, diagnosing, and treating neurological and cognitive diseases, leaving a critical gap between the current computational modeling capabilities and the needs in brain dynamics analysis. This project aims to bridge this gap by exploiting multi-scale structural (voxel, vasculature, tissue) connectivity and multi-modal (anatomical, angiography, perfusion) connectivity to develop an integrated connective computational paradigm for characterizing and understanding brain dynamics.

The approach consists of three thrusts: (1) multi-scale structural connectivity modeling to quantify brain dynamics beyond a single voxel; (2) multimodal dynamic dictionary learning for mining hidden complementary information; and (3) multicenter evaluation to assess the efficacy of the proposed models at three nationally renowned healthcare systems. Successful project completion would potentially transform the rapidly evolving field of brain dynamics modeling, facilitate basic neuroscience discovery and enable comprehensive identification of neurovascular diseases. Aiming to broaden its impact this project will also implement educational initiatives to expose students, middle school teachers, and medical professionals to ‘CS for All,’ to foster interests in STEM and cross-disciplinary careers, and to promote research on the convergence of computer science and computational thinking for brain health and neuromedicine.