The cognitive relevance of resting-state brain activity

Human cognitive ability has been strongly linked to neural functioning using both experimenter-controlled task activations and correlations between individual differences in behavior and resting state functional connectivity (RSFC). Furthermore, there is evidence supporting a close relationship between RSFC and task co-activations (independent of behavior). Despite this, it remains unclear what neural mechanisms underlie resting-state brain activity and how it relates to task-state activity and behavior. In the work presented in this thesis, I investigated the complex relationship between these three constructs (task state, rest state, and behavior). First, I investigated the relationship between task-state and resting-state by identifying spontaneous cognitive states occurring during resting state. Comparisons with previously identified task activation patterns in task-based studies revealed unique functions for each of the cognitive states. Second, I explored the relationship between RSFC, task activations, and behavior by testing the associations between task activations and RSFC in context of individual variability in behavior. This revealed the relevance of RSFC network architecture, despite the majority of behavioral variance being related to task activations. Finally, I developed a novel task-training paradigm to determine the neural basis of automaticity, assessing the functional relevance of RSFC in the development of automatic behavior. The results indicate the recruitment of task-based FC over RSFC in encoding automatic behavior. Taken together, these findings add to pre-existing research investigating resting-state neural activity, providing an integrated perspective of the relevance of resting-state activity in relation to task-evoked activity and human behavior.Ph.D.Includes bibliographical reference