Genetic effects on the temporal organization of connectome dynamics and associated cognitive functions

Jun, Suhnyoung

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https://hdl.handle.net/2142/124196 Copy

Description

Title

Genetic effects on the temporal organization of connectome dynamics and associated cognitive functions

Author(s)

Jun, Suhnyoung

Issue Date

2024-03-01

Director of Research (if dissertation) or Advisor (if thesis)

Sadaghiani, Sepideh

Doctoral Committee Chair(s)

Sadaghiani, Sepideh

Committee Member(s)

• Gratton, Gabriele
• Fabiani, Monica
• Barbey, Aron
• Altmann, Andre

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• dynamic functional connectivity
• fMIR
• electrophysiology
• hidden Markov modeling
• cognition
• individual differences
• canonical correlation analysis
• heritability
• molecular genetics

Abstract

The brain is inherently dynamic and capable of flexibly reorganizing its functional architecture (“connectome”) even in the absence of an explicit task. Such dynamic reconfigurations of the connectome play a role in shaping cognitive abilities and complex brain functions. Specifically, time-varying characteristics of the brain's functional connectome are specific to the individual and predictive of individual cognitive abilities. However, there is a critical gap in understanding which dynamic characteristics are heritable phenotypes and how inter-individual variability in such connectome dynamics could contribute to differences in cognitive abilities across people. Further, specific genetic polymorphisms that influence the heritable aspects of connectome dynamics have remained largely unknown. Therefore, the upcoming chapters are designed to achieve several objectives. Firstly, Chapter 1 explores the genetic influences on features of fMRI-derived connectome dynamics using a twin study design. Secondly, Chapter 2 identified specific genetic polymorphisms that impact fMRI-derived connectome dynamics, employing a molecular genetics study approach. Thirdly, Chapter 3 aims to delve into the genetic effects on connectome dynamics at faster timescales, utilizing source-localized EEG in conjunction with the twin study design. Lastly, Chapter 4 extends to examining the behavioral significance of heritable rapid connectome dynamics phenotypes. Collectively, our findings aim to provide a comprehensive understanding of how genetic effects impact both slow and rapid connectome dynamics, and how such dynamics in turn affect behavior. In Chapter 1, we investigated the heritability of temporal and spatial features of the functional connectome using Human Connectome Project’s resting-state fMRI data. We found strong and robust evidence for heritability and cognitive association of temporal dynamic features, i.e., Fractional Occupancy (FO; the proportion of time spent in each connectome state) and Transition Probability (TP; the probability to transition between state pairs). Specifically, genetic effects explained a substantial proportion of phenotypic variance of these features (narrow-sense heritability (h2) =0.39, 95% CI= [.24,.54] for FO; h2=0.43, 95% CI= [.29,.57] for TP). Moreover, these temporal phenotypes were associated with cognitive performance. Spatial features, however, showed no robust evidence of heritability. Our findings indicate that genetic effects primarily impact how the connectome transitions across states rather than the precise spatial instantiation of the states. Building upon the findings of Chapter 1, Chapter 2 aimed to identify the specific genetic polymorphisms that shape connectome dynamics and the associated cognitive abilities. Given the widespread regulatory impact of modulatory neurotransmitters on functional connectivity, we comprehensively investigated a large set of single nucleotide polymorphisms (SNPs) of their receptors, metabolic enzymes, and transporters. We found that specific subsets of these SNPs jointly explain individual differences in temporal phenotypes of fMRI-derived connectome dynamics for which we previously established heritability in Chapter 1. Specifically, a set of cholinergic SNPs predicted Fractional Occupancy and a set of serotonergic SNPs explained Transition Probability. Together, our findings provide evidence for specific genetic effects on connectome dynamics via the regulatory impact of modulatory neurotransmitter systems. While we have established the substantial genetic effects and behavioral significance of fMRI-derived connectome dynamics throughout Chapters 1 and 2, the fMRI-derived connectome dynamics predominantly captures infra-slow (< 0.1 Hz) processes. Therefore, in Chapters 3 and 4, we studied connectome dynamics at faster timescales that are highly relevant for cognition. Specifically, in Chapter 3, we investigated the genetic effects on rapid connectome dynamics features in each canonical frequency band derived using source-space resting-state EEG. We found that temporal features were heritable, particularly, Fractional Occupancy (in theta, alpha, beta, and gamma bands) and Transition Probability (in theta, alpha, and gamma bands). Further, genetic effects explained a substantial proportion of phenotypic variance of these features: Fractional Occupancy in beta (44.3%) and gamma (39.8%) bands and Transition Probability in theta (38.4%), alpha (63.3%), beta (22.6%), and gamma (40%) bands. Consistent with the findings of Chapter 1, we did not find support for the heritability of spatial features of connectome dynamics, specifically states’ Modularity and connectivity pattern. While electrophysiological connectome dynamics may be highly relevant to cognition due to their rapid (sub-second) timescale, empirical evidence for such relevance is largely lacking. In Chapter 4, we investigated the behavioral significance of rapid electrophysiological connectome dynamics using canonical correlation analysis. We found a significant relationship between the heritable features of sub-second connectome dynamics, identified in Chapter 3, and factorized cognitive performance measures. Specifically, principal components of alpha (followed by theta and gamma components) and a cognitive factor representing visuospatial processing (followed by verbal and auditory working memory) showed the most notable contribution to the relationship. Together, these chapters provide a comprehensive perspective on the genetic influences and behavioral significance of connectome dynamics across various timescales and modalities, advancing our understanding of the intricate relationship between connectome dynamics and cognition.

Graduation Semester

2024-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2024 Suhnyoung Jun

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