Citation

Peng XR, Lei X, Xu P, Yu J. Neuroscience 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, International Brain Research Organization, Publisher Elsevier Publishing)

DOI

10.1016/j.neuroscience.2020.05.017

PMID

unavailable

Abstract

Previous studies have shown that aging is associated with changes in decision behavior. However, the neural mechanisms that underpin such age differences are inadequately understood. In this study, we aim to characterize the optimal neural model underlying a dynamic decision making task in both young and older adults, and further examine the age differences from the perspective of effective connectivity. Twenty-five young and 23 older adults performed a dynamic risk taking task, i.e., the balloon analogue risk task, in the functional magnetic resonance imaging scanner. The dynamic causal modeling analysis, with the coupling between the ventromedial prefrontal cortex (VMPFC), dorsolateral prefrontal cortex (DLPFC) and anterior insula (AI) that were identified in our task-related activation and psychophysiological interaction analysis, was performed to address the best fitting neural model and characterize age differences. Although both age groups adopted the same optimal model with bidirectional connection between the VMPFC and DLPFC, older adults exhibited up-regulation in several connections and among which the increased modulatory effect of AI-to-VMPFC subserving their decision quality. Our finding suggests that older adults might utilize different neural strategy via compensation to counteract the impact of advanced age in risk taking process.

Language: en

Keywords

decision making; aging; compensation; dynamic causal modeling; effective connectivity