Changes in global functional network properties predict individual differences in habit formation
Research output: Contribution to journal › Research article › Contributed › peer-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 language | English |
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Pages (from-to) | 1565-1578 |
Number of pages | 14 |
Journal | Human brain mapping |
Volume | 44 |
Issue number | 4 |
Early online date | 22 Nov 2022 |
Publication status | Published - Mar 2023 |
Peer-reviewed | Yes |
External IDs
PubMed | 36413054 |
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WOS | 000888160700001 |
ORCID | /0000-0001-9793-3859/work/142248864 |
Keywords
ASJC Scopus subject areas
Keywords
- fMRI, functional connectivity, goal-directed behavior, habit, multivariate linear regression, sensorimotor network, Functional connectivity, Habit, Sensorimotor network, Goal-directed behavior, Multivariate linear regression