Brain network correlates of adolescent self-control

© 2013 Dr. Dominic B. DwyerThe ability to engage self-control by overcoming automatic habits and impulses is critical to the progression from adolescence to adulthood, and can predict long-term health outcomes. Research into self-control has involved a number of techniques, with the psychology of individual differences and cognitive neuroscience featuring prominently. Despite their diverse perspectives, these two fields have converged recently to suggest that variations in both cognitive and personality-based measures of self-control rely on a common set of functional interactions within and between two canonical large-scale brain systems: The so-called cognitive control (CCN) and default-mode networks (DMN). However, very little is known about how individual differences in self-control during the teenage years relate to the functional activity and connectivity of these networks. This thesis aimed to fill this gap using a series of functional magnetic resonance imaging (fMRI) experiments designed to assess, in detail, the large-scale functional brain networks that support adolescent self-control as defined using both cognitive and questionnaire-based measures. To achieve this, data from the same sample of participants was used in a series of five experiments that progressed in the focus on large-scale brain networks from simple brain mapping, through individual differences analyses of activity and functional connectivity, and then ending with modularity analyses. During each experiment, a specific interest was also to determine the similarities and differences between the task-related versus the resting-state CCN and DMN to determine how self-control networks are engaged during task performance. The main hypothesis was that the task-related activity and functional connectivity of core regions that comprise the CCN and DMN would be most related to individual differences in cognitive and effortful control. Methods: The participants comprised a healthy sample of adolescents (N=73; mean age (SD) =16.5(0.5); 51% female) from a longitudinal study who completed questionnaire measures of effortful control, a temperamental index of self-control capacity in daily life; an fMRI interference control paradigm (the Multi-Source Interference Task; MSIT); and a resting-state fMRI sequence. Using these data, five experiments were then devised to investigate how the task-related activity, task-related functional connectivity, and resting-state functional connectivity of the CCN and DMN support self-control behaviours as measured by self-reported effortful control (ECc), parent-reported effortful control (ECp), MSIT interference effect, and MSIT accuracy. The experiments were designed to build upon each other to comprehensively address the thesis aim. Chapter 6 established the main measures used throughout the thesis related to the sample, and to the behavioural and brain measures related to self-control. The second experimental chapter (Chapter 7) examined how MSIT-related activation and within each region comprising the CCN and DMN correlated with EC and MSIT performance. Chapter 8 then established the functional connectivity parameters for each participant and employed the graph theoretic measure of node strength to investigate correlations between behaviour and the resting-state and task-related functional connectivity of each region. More specific pair-wise functional connectivity relationships between brain regions were then investigated in Chapter 9 in order to identify functional connectivity sub-networks related to each behavioural variable. Finally, Chapter 10 then integrated the results into a broader functional connectivity picture using a data-driven technique to identify how the putative network nodes aggregated into functionally specialized modules. Results: Contrary to the main hypothesis of this thesis, the results indicated that each behavioural measure was related to a different large-scale brain network, which appeared to be specific to the condition under investigation (i.e., task or rest). For example, the MSIT interference effect was associated with a putative visual attention network during task performance but not at rest; MSIT accuracy was mainly associated with the connectivity of default-mode regions; and effortful control was correlated with complex subnetworks where interactions between the CCN and DMN appeared to be most important. The importance of interactions between networks was then emphasised in the modularity analysis, which showed subtle, but behaviourally important, differences in network modular organization between the task and resting-state conditions. Conclusion: Overall, the results of the thesis supported the idea that competitive and cooperative relationships between the cognitive control and default mode networks support adolescent self-control. However, the experiments highlighted the importance of the engagement of different subnetworks for different measurements of self-control, and functional connectivity differences between rest and task conditions that may predict behaviour. Together, these findings emphasise the importance of considering the flexibility of large-scale networks when considering the neural basis of adolescent self-control, rather than a single canonical brain region or circuit