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Age-related differences in ventral striatal and default mode network function during reciprocated trust
- Source :
- NeuroImage, Vol 256, Iss , Pp 119267- (2022)
- Publication Year :
- 2022
- Publisher :
- Elsevier, 2022.
-
Abstract
- Social relationships change across the lifespan as social networks narrow and motivational priorities shift to the present. Interestingly, aging is also associated with changes in executive function, including decision-making abilities, but it remains unclear how age-related changes in both domains interact to impact financial decisions involving other people. To study this problem, we recruited 50 human participants (Nyounger = 26, ages 18–34; Nolder = 24, ages 63–80) to play an economic trust game as the investor with three partners (friend, stranger, and computer) who played the role of investee. Investors underwent functional magnetic resonance imaging (fMRI) during the trust game while investees were seated outside of the scanner. Building on our previous work with younger adults showing both enhanced striatal responses and altered default-mode network (DMN) connectivity as a function of social closeness during reciprocated trust, we predicted that these relations would exhibit age-related differences. We found that striatal responses to reciprocated trust from friends relative to strangers and computers were blunted in older adults relative to younger adults, thus supporting our primary pre-registered hypothesis regarding social closeness. We also found that older adults exhibited enhanced DMN connectivity with the temporoparietal junction (TPJ) during reciprocated trust from friends compared to computers while younger adults exhibited the opposite pattern. Taken together, these results advance our understanding of age-related differences in sensitivity to social closeness in the context of trusting others.
Details
- Language :
- English
- ISSN :
- 10959572
- Volume :
- 256
- Issue :
- 119267-
- Database :
- Directory of Open Access Journals
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.fc48babc7bd84b178479abc3885780fa
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2022.119267