PT  - JOURNAL ARTICLE
AU  - Rosenberg, Monica D.
AU  - Scheinost, Dustin
AU  - Greene, Abigail S.
AU  - Avery, Emily W.
AU  - Kwon, Young Hye
AU  - Finn, Emily S.
AU  - Ramani, Ramachandran
AU  - Qiu, Maolin
AU  - Constable, R. Todd
AU  - Chun, Marvin M.
TI  - Functional connectivity predicts changes in attention over minutes, days, and months
AID  - 10.1101/700476
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 700476
4099  - http://biorxiv.org/content/early/2019/07/14/700476.short
4100  - http://biorxiv.org/content/early/2019/07/14/700476.full
AB  - The ability to sustain attention differs across people and changes within a single person over time. Although recent work has demonstrated that patterns of functional brain connectivity predict individual differences in sustained attention, whether these same patterns capture fluctuations in attention in single individuals remains unclear. Here, across five independent studies, we demonstrate that the sustained attention connectome-based predictive model (CPM), a validated model of sustained attention function, generalizes to predict attention changes across minutes, days, weeks, and months. Furthermore, the sustained attention CPM is sensitive to within-subject state changes induced by propofol as well as sevoflurane, such that individuals show functional connectivity signatures of stronger attentional states when awake than when under deep sedation and light anesthesia. Together these results demonstrate that fluctuations in attentional state reflect variability in the same functional connectivity patterns that predict individual differences in sustained attention.