Logo image
Back
Individual-level Functional Connectivity Predicts Cognitive Control Efficiency
Other   Open access

Individual-level Functional Connectivity Predicts Cognitive Control Efficiency

Benjamin Deck, Apoorva Kelkar, Brian Erickson, Fareshte Erani, Eric Mcconathey, Daniela Sacchetti, Olu Faseyitan, Roy Hamilton and John Medaglia
bioRxiv
16 Jul 2022
DOI: https://doi.org/10.1101/2022.07.14.500048
url
https://doi.org/10.1101/2022.07.14.500048View
SubmittedCC BY-ND V4.0,  Open

Abstract

Cognitive ability Neural networks Problem solving Regression analysis
Cognitive control (CC) is a vital component of cognition associated with problem-solving in everyday life. Many neurological and neuropsychiatric conditions have deficits associated with CC. CC is composed of multiple behaviors including switching, inhibiting, and updating. The fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON) and the dorsal default-mode network (dorsal-DMN) have been associated with switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about CC behaviors is still unclear. In the current study, participants performed two in-scanner tasks that required switching and inhibiting. We then used a series of support vector regression (SVR) models containing individually-estimated functional connectivity between the networks of interest derived during tasks and at rest to predict inhibition and switching behaviors in individual subjects. We observed that the combination of between-network connectivity from these individually estimated functional networks predicted accurate and timely inhibition and switching behaviors in individuals. We also observed that the relationships between canonical task-positive and task-negative networks predicted inhibiting and switching behaviors. Finally, we observed a functional dissociation between the FPCN-A and FPCN-B during rest, and task performance predicted inhibiting and switching behaviors. These results suggest that individually estimated networks can predict individual CC behaviors, that between-network functional connectivity estimated within individuals is vital to understanding how CC arises, and that the fractionation of the FPCN and the DMN may be associated with different behaviors than their canonically accepted behaviors. Competing Interest Statement The authors have declared no competing interest.

Metrics

26 Record Views

Details

Logo image