Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency

Kelly M J Diederen, Tom Spencer, Martin D Vestergaard, Paul C Fletcher, Wolfram Schultz

Research output: Contribution to journalArticlepeer-review

64 Citations (Scopus)
177 Downloads (Pure)

Abstract

Effective error-driven learning benefits from scaling of prediction errors to reward variability. Such behavioral adaptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD) of reward distributions. To investigate this hypothesis, we required participants to predict the magnitude of upcoming reward drawn from distributions with different SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. In line with the notion of adaptive coding, BOLD response slopes in the Substantia Nigra/Ventral Tegmental Area (SN/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smaller SDs. SN/VTA adaptation was not instantaneous but developed across trials. Adaptive prediction error coding was paralleled by behavioral adaptation, as reflected by SD-dependent changes in learning rate. Crucially, increased SN/VTA and ventral striatal adaptation was related to improved task performance. These results suggest that adaptive coding facilitates behavioral adaptation and supports efficient learning.

Original languageEnglish
Pages (from-to)1127-38
Number of pages12
JournalNeuron
Volume90
Issue number5
Early online date12 May 2016
DOIs
Publication statusPublished - 1 Jun 2016

Keywords

  • Adaptation, Psychological
  • Corpus Striatum
  • Humans
  • Learning
  • Magnetic Resonance Imaging
  • Models, Psychological
  • Neuroimaging
  • Neurons
  • Psychomotor Performance
  • Reward
  • Substantia Nigra
  • Ventral Tegmental Area
  • Journal Article
  • Research Support, Non-U.S. Gov't

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