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Patterns of whole-brain fMRI functional connectivity, or connectomes, are unique to individuals. Previous work has identified subsets of functional connections within these patterns whose strength predicts aspects of attention and cognition. However, overall features of these connectomes, such as how stable they are over time and how similar they are to a group-average (typical) or high-performance (optimal) connectivity pattern, may also reflect cognitive and attentional abilities. Here, we test whether individuals who express more stable, typical, optimal, and distinctive patterns of functional connectivity perform better on cognitive tasks using data from three independent samples. We find that individuals with more stable task-based functional connectivity patterns perform better on attention and working memory tasks, even when controlling for behavioral performance stability. Additionally, we find initial evidence that individuals with more typical and optimal patterns of functional connectivity also perform better on these tasks. These results demonstrate that functional connectome stability within individuals and similarity across individuals predicts individual differences in cognition.

 

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children—and captured individual differences in later recognition memory—but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA. 

Abstract Sustained attention is a critical cognitive function reflected in an individual’s whole-brain pattern of functional magnetic resonance imaging functional connectivity. However, sustained attention is not a purely static trait. Rather, attention waxes and wanes over time. Do functional brain networks that underlie individual differences in sustained attention also underlie changes in attentional state? To investigate, we replicate the finding that a validated connectome-based model of individual differences in sustained attention tracks pharmacologically induced changes in attentional state. Specifically, preregistered analyses revealed that participants exhibited functional connectivity signatures of stronger attention when awake than when under deep sedation with the anesthetic agent propofol. Furthermore, this effect was relatively selective to the predefined sustained attention networks: propofol administration modulated strength of the sustained attention networks more than it modulated strength of canonical resting-state networks and a network defined to predict fluid intelligence, and the functional connections most affected by propofol sedation overlapped with the sustained attention networks. Thus, propofol modulates functional connectivity signatures of sustained attention within individuals. More broadly, these findings underscore the utility of pharmacological intervention in testing both the generalizability and specificity of network-based models of cognitive function. 

As we comprehend narratives, our attentional engagement fluctuates over time. Despite theoretical conceptions of narrative engagement as emotion-laden attention, little empirical work has characterized the cognitive and neural processes that comprise subjective engagement in naturalistic contexts or its consequences for memory. Here, we relate fluctuations in narrative engagement to patterns of brain coactivation and test whether neural signatures of engagement predict subsequent memory. In behavioral studies, participants continuously rated how engaged they were as they watched a television episode or listened to a story. Self-reported engagement was synchronized across individuals and driven by the emotional content of the narratives. In functional MRI datasets collected as different individuals watched the same show or listened to the same story, engagement drove neural synchrony, such that default mode network activity was more synchronized across individuals during more engaging moments of the narratives. Furthermore, models based on time-varying functional brain connectivity predicted evolving states of engagement across participants and independent datasets. The functional connections that predicted engagement overlapped with a validated neuromarker of sustained attention and predicted recall of narrative events. Together, our findings characterize the neural signatures of attentional engagement in naturalistic contexts and elucidate relationships among narrative engagement, sustained attention, and event memory.