Subjective value representations during effort, probability and time discounting across adulthood.

Journal Article (Journal Article)

Every day, humans make countless decisions that require the integration of information about potential benefits (i.e. rewards) with other decision features (i.e. effort required, probability of an outcome or time delays). Here, we examine the overlap and dissociation of behavioral preferences and neural representations of subjective value in the context of three different decision features (physical effort, probability and time delays) in a healthy adult life span sample. While undergoing functional neuroimaging, participants (N = 75) made incentive compatible choices between a smaller monetary reward with lower physical effort, higher probability, or a shorter time delay versus a larger monetary reward with higher physical effort, lower probability, or a longer time delay. Behavioral preferences were estimated from observed choices, and subjective values were computed using individual hyperbolic discount functions. We found that discount rates were uncorrelated across tasks. Despite this apparent behavioral dissociation between preferences, we found overlapping subjective value-related activity in the medial prefrontal cortex across all three tasks. We found no consistent evidence for age differences in either preferences or the neural representations of subjective value across adulthood. These results suggest that while the tolerance of decision features is behaviorally dissociable, subjective value signals share a common representation across adulthood.

Full Text

Duke Authors

Cited Authors

  • Seaman, KL; Brooks, N; Karrer, TM; Castrellon, JJ; Perkins, SF; Dang, LC; Hsu, M; Zald, DH; Samanez-Larkin, GR

Published Date

  • May 2018

Published In

Volume / Issue

  • 13 / 5

Start / End Page

  • 449 - 459

PubMed ID

  • 29618082

Pubmed Central ID

  • PMC6007391

Electronic International Standard Serial Number (EISSN)

  • 1749-5024

International Standard Serial Number (ISSN)

  • 1749-5016

Digital Object Identifier (DOI)

  • 10.1093/scan/nsy021

Language

  • eng