Changes in global functional network properties predict individual differences in habit formation

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

Prior evidence suggests that sensorimotor regions play a crucial role in habit formation. Yet, whether and how their global functional network properties might contribute to a more comprehensive characterization of habit formation still remains unclear. Capitalizing on advances in Elastic Net regression and predictive modeling, we examined whether learning-related functional connectivity alterations distributed across the whole brain could predict individual habit strength. Using the leave-one-subject-out cross-validation strategy, we found that the habit strength score of the novel unseen subjects could be successfully predicted. We further characterized the contribution of both, individual large-scale networks and individual brain regions by calculating their predictive weights. This highlighted the pivotal role of functional connectivity changes involving the sensorimotor network and the cingulo–opercular network in subject-specific habit strength prediction. These results contribute to the understanding the neural basis of human habit formation by demonstrating the importance of global functional network properties especially also for predicting the observable behavioral expression of habits.

Details

Original languageEnglish
Number of pages14
JournalHuman brain mapping
Publication statusPublished - 22 Nov 2022
Peer-reviewedYes

External IDs

PubMed 36413054
WOS 000888160700001

Keywords

Keywords

  • fMRI, functional connectivity, goal-directed behavior, habit, multivariate linear regression, sensorimotor network, Functional connectivity, Habit, Sensorimotor network, Goal-directed behavior, Multivariate linear regression