Flexibility in valenced reinforcement learning computations across development

Abstract

Optimal integration of positive and negative outcomes during learning varies depending on an environment's reward statistics. The present study investigated the extent to which children, adolescents, and adults (N = 142 8–25 year‐olds, 55% female, 42% White, 31% Asian, 17% mixed race, and 8% Black; data collected in 2021) adapt their weighting of better‐than‐expected and worse‐than‐expected outcomes when learning from reinforcement. Participants made choices across two contexts: one in which weighting positive outcomes more heavily than negative outcomes led to better performance, and one in which the reverse was true. Reinforcement learning modeling revealed that across age, participants shifted their valence biases in accordance with environmental structure. Exploratory analyses revealed strengthening of context‐dependent flexibility with increasing age.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 21, 2022
Source ID
10.1111/cdev.13791

Entities

People

  • Bradli T. Washington
  • Catherine A. Hartley
  • Hannah E. Hamling
  • Juan A. Velez
  • Kate Nussenbaum

Organizations

  • Jacobs Foundation
  • National Institute of Mental Health
  • National Science Foundation of Sri Lanka
  • New York University
  • United States Department of Defense

Tags

Fields of Study

  • Psychology

Readers

  • Mathematical Modeling and Probability Theory.
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.
  • Systems Analysis and Design

Technology Areas

  • AI & ML