Date of Award

Fall 1-1-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Physics

First Advisor

Murray, John

Abstract

Individuality is a defining feature of human existence. Yet the neural mechanisms underlying such individual variation are not fully understood. Prior research has suggested that variation in the balance between excitation and inhibition within the brain may contribute to these differences. To investigate this hypothesis, we employed a large-scale, biophysically-based model of the human cortex. This model is governed by a small set of biologically interpretable parameters, allowing for a focused analysis of how shifts in excitation and inhibition shape individual brain function. Using this modelling framework, this thesis examined patterns of variation across both healthy individuals and clinical populations. We developed and applied new methods to analyze the structure of across-subject differences, aiming to identify how excitation and inhibition relate to differences in functional connections in the brain. We explored extensions incorporating subcortex, allowing for a more comprehensive representation of neural dynamics. The model's biological grounding enables meaningful interpretation of parameter differences, making it a valuable tool for probing the physiological basis of brain diversity. This work highlights the potential of computational neuroscience to bridge the gap between neural mechanisms and individual variation. By leveraging biophysically realistic models of cortical function, we provide new insights into how fundamental neural processes may give rise to the wide spectrum of human individualization. This approach offers a promising path toward a more mechanistic understanding of individual differences in both typical and atypical populations.

Download

Share

COinS