Through the Looking-Glass: Analytical Flexibility and Interpretive Consensus in Resting-State fMRI

Abstract

Most data analyses underscore an obvious but difficult question: what information do we lose in the process of extracting something we can understand? This question emerges in widespread obstacles in the analysis and interpretation of resting-state fMRI data. In neuroimaging, extensive post-processing of resting-state functional MRI (rfMRI) data is necessary for its application, especially when investigating neural mechanisms of mental illness. However, widespread variability in these post-processing pipelines has hindered both the reproducibility and accumulation of knowledge in this area of the field. A choice of dimension-reduction algorithm is one of the most variable and impactful ones made in an rfMRI post-processing pipeline, and the interpretive implications of this choice will be the primary focus of this defense. We study information consensus between dimension reductions by examining the variability they induce on the topology (or, more precisely, the persistent homology) of the Human Connectome Project. We also probe this example case for general insights into the topological stability of dimension reduction problems (of n D-dimensional points to n d-dimensional points) in the regime D ≫ d ≫ n, which is not mathematically well-characterized despite its practical prevalence and significance.

Committee Chair

Janine Bijsterbosch

Committee Members

Ari Stern; Aristeidis Sotiras; Elizabeth Munch; Joseph O'Sullivan

Degree

Doctor of Philosophy (PhD)

Author's Department

Interdisciplinary Programs

Author's School

McKelvey School of Engineering

Document Type

Dissertation

Date of Award

8-18-2025

Language

English (en)

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