Date of Award

Fall 2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Interdepartmental Neuroscience Program

First Advisor

Constable, R. Todd

Abstract

Studying individual differences in functional connectomes provides a powerful framework to tackle questions in developmental human neuroscience. In this work, I use such a framework to study a multitude of factors, ranging from data quality control issues to building predictive models of clinically relevant phenotypes in neurodiverse youth. The first empirical chapter explores how factors related to the reliability of functional connections, namely the amount of scan data, in-scanner head motion, and the spatiotemporal resolution of data acquisition affect the detection of individual differences. In the second empirical chapter, I demonstrate that individual differences in connectomes are stable in developing populations. That is, connectivity signatures specific to an individual are retained across years, even in periods of rapid brain development. In the third empirical chapter, I describe the successful implementation of a desensitization protocol that allowed the collection of high-quality, low-motion data necessary to detect and leverage individual differences in a neurodiverse sample. In the fourth empirical chapter, I use the data obtained through the work of chapter three to demonstrate that robust connectome-based signatures of sustained attention can be generated in neurodiverse youth. I go on to show such a signature generalizes to predict attention in neurotypical young adults, of special interest given developmental differences in the youth and adult samples. In sum, this body of work suggests the power of focusing on individual differences in functional connectivity research and provides a foundation for linking such differences to clinically-actionable behaviors in developing populations.

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