Propofol selectively modulates functional connectivity signatures of sustained attention during rest and narrative listening. (14th March 2022)

• Record Type: Journal Article
• Authors: Chamberlain, Taylor A; Rosenberg, Monica D
• Is Part Of: Cerebral cortex. Volume 32:Number 23(2022)
• Page Start: 5362
• Page End: 5375
• Publication Date: 2022-03-14
• Subjects: resting-state functional connectivity -- individual differences -- attention networks -- connectome-based predictive modeling -- fMRI -- propofol; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhac020
• Languages: English
• ISSNs: 1047-3211

Abstract

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.