Neurocomputational mechanisms of young children's observational learning of delayed gratification

  • Hui Zhao
  • , Tengfei Zhang
  • , Tong Cheng
  • , Chuansheng Chen
  • , Yu Zhai
  • , Xi Liang
  • , Nanhua Cheng
  • , Yuhang Long
  • , Ying Li
  • , Zhengyan Wang*
  • , Chunming Lu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The ability to delay gratification is crucial for a successful and healthy life. An effective way for young children to learn this ability is to observe the action of adult models. However, the underlying neurocomputational mechanism remains unknown. Here, we tested the hypotheses that children employed either the simple imitation strategy or the goal-inference strategy when learning from adult models in a high-uncertainty context. Results of computational modeling indicated that children used the goal-inference strategy regardless of whether the adult model was their mother or a stranger. At the neural level, results showed that successful learning of delayed gratification was associated with enhanced interpersonal neural synchronization (INS) between children and the adult models in the dorsal lateral prefrontal cortex but was not associated with children's own single-brain activity. Moreover, the discounting of future reward's value obtained from computational modeling of the goal-inference strategy was positively correlated with the strength of INS. These findings from our exploratory study suggest that, even for 3-year-olds, the goal-inference strategy is used to learn delayed gratification from adult models, and the learning strategy is associated with neural interaction between the brains of children and adult models.

Original languageEnglish
Pages (from-to)6063-6076
Number of pages14
JournalCerebral Cortex
Volume33
Issue number10
DOIs
Publication statusPublished - 15 May 2023
Externally publishedYes

Keywords

  • computational modeling
  • delayed gratification
  • fNIRS
  • hyperscanning
  • observational learning

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