Integration and segregation across large-scale intrinsic brain networks as a marker of sustained attention and task-unrelated thought

Abstract

Sustained attention is a fundamental cognitive process that can be decoupled from distinct external events, and instead emerges from ongoing intrinsic large-scale network interdependencies fluctuating over seconds to minutes. Lapses of sustained attention are commonly associated with the subjective experience of mind wandering and task-unrelated thoughts. Little is known about how fluctuations in information processing underpin sustained attention, nor how mind wandering undermines this information processing. To overcome this, we used fMRI to investigate brain activity during subjects’ performance (n=29) of a cognitive task that was optimized to detect and isolate continuous fluctuations in both sustained attention (via motor responses) and task-unrelated thought (via subjective reports). We then investigated sustained attention with respect to global attributes of communication throughout the functional architecture, i.e., by the segregation and integration of information processing across large scale-networks. Further, we determined how task-unrelated thoughts related to these global information processing markers of sustained attention. The results show that optimal states of sustained attention favor both enhanced segregation and reduced integration of information processing in several task-related large-scale cortical systems with concurrent reduced segregation and enhanced integration in the auditory and sensorimotor systems. Higher degree of mind wandering was associated with losses of the favored segregation and integration of specific subsystems in our sustained attention model. Taken together, we demonstrate that intrinsic ongoing neural fluctuations are characterized by two converging communication modes throughout the global functional architecture, which give rise to optimal and suboptimal attention states. We discuss how these results might potentially serve as neural markers for clinically abnormal attention

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