Biostatistics Weekly Seminar

Heterogeneity Analysis on Multi-state Brain Functional Connectivity and Adolescent Neurocognition

Yize Zhao, PhD
Associate Professor
Department of Biostatistics
Yale University

Brain functional connectivity or connectome, a unique measure for brain functional organization, provides a great potential to explain the neurobiological underpinning of behavioral profiles. Existing connectome-based analyses highly concentrate on brain activities under a single cognitive state, and fail to consider heterogeneity when attempting to characterize brain-to-behavior relationships. In this work, we study the complex impact of multi-state functional connectivity on behaviors by analyzing the data from a recent landmark brain development and child health study. We propose a nonparametric, Bayesian supervised heterogeneity analysis to uncover neurodevelopmental subtypes with distinct predictive mechanisms. We impose stochastic block structures to identify network-based functional phenotypes and develop a variational expectation–maximization algorithm to facilitate an efficient posterior computation. Through integrating resting-state and task-related functional connectomes, we dissect heterogeneous predictive mechanisms on children’s fluid intelligence from the functional network phenotypes including Fronto-parietal Network and Default Mode Network under different cognitive states. Meanwhile, our method improves the prediction of children’s fluid intelligence compared with existing alternatives and single state analyses. Based on extensive simulations, we further confirm the superior performance of our method on uncovering and predicting brain-to-behavior relationships.

Hybrid: Meeting Room and Zoom Link to Follow
22 February 2023

Speaker Itinerary

Topic revision: r1 - 13 Feb 2023, CierraStreeter

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