The contributions of the relationship between brain structure and function to modelling of human cognition

Abstract

Brain structure and function share a complex relationship. To some extent, they mirror each other and show mutual influence but they also diverge in their organisation. However, little is known about how these two aspects relate to each other in service of cognitive function. This work first explores how previous research has related brain structure and function in cognitive neuroscience, and it demonstrates that few investigations quantify how much the relationship between brain structure and function contributes to cognitive function. Then the thesis utilises the neuroimaging and cognitive data from Human Connectome Project in predictive modelling of cognition to investigate whether there are any benefits to joint consideration of structural and functional brain connectivity. As presented in Chapter 4, joint consideration of brain structure and function improved prediction accuracy of for specific cognitive domains, particularly those that involve higher-order processing (e.g. Language and Executive Function). The thesis then progresses to explore how predictive models are influenced by characterising connectivity with graph theory measures, and estimating connectivity with a variety of parcellation schemes. In Chapter 6, it was found that graph theory was often able to predict cognitive performance, but there was no consistent benefit to obtaining graph theory measures relative to use of raw connectivity. Then, as demonstrated in Chapter 7, obtaining brain connectivity with different parcellation schemes impacted graph theoretic measures of brain connectivity. However, despite the effect of parcellation schemes on graph theory measures, there was no single parcellation that would consistently produce the most generalisable models of cognition. Overall, this thesis demonstrates that unique aspects of brain structure and function support specific cognitive domains, but joint consideration of them both in predictive models does not necessarily benefit modelling of cognition. Therefore, the thesis demonstrates that unique properties of the brain system are conveyed by modality specific connectivity. Two theoretical models are proposed in the general discussion to account for these findings.

Date of Award	1 Aug 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Anna Woollams (Supervisor), Nelson Trujillo-Barreto (Supervisor) & Nils Muhlert (Supervisor)