Advancing Machine Learning for Neuroimaging Through Topology-Aware Signal Processing

University of Delaware Research Foundation–Strategic Initiative, Principal Investigator: Austin J. Brockmeier, Mentor: Gonzalo Arce, 11/2019–10/2021.

The proposed work plan is to develop machine learning techniques to work directly with graph signal processing techniques in the context of neuroimaging. The goal is to leverage information in the form of the topology of the signal sensors or measurement locations to refine the neural signal representations in order to improve the statistical power of tests for distinguishing differences between conditions or stimuli. The project’s scope includes the formulation, mathematical and statistical analysis, and initial validation of the proposed methodology.

First 5 harmonics (Fourier transform) of the gray matter graph.