Adaptive learning is structure learning in time

Linda Q. Yu, Robert C. Wilson, Matthew R. Nassar

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations


People use information flexibly. They often combine multiple sources of relevant information over time in order to inform decisions with little or no interference from intervening irrelevant sources. They adjust the degree to which they use new information over time rationally in accordance with environmental statistics and their own uncertainty. They can even use information gained in one situation to solve a problem in a very different one. Learning flexibly rests on the ability to infer the context at a given time, and therefore knowing which pieces of information to combine and which to separate. We review the psychological and neural mechanisms behind adaptive learning and structure learning to outline how people pool together relevant information, demarcate contexts, prevent interference between information collected in different contexts, and transfer information from one context to another. By examining all of these processes through the lens of optimal inference we bridge concepts from multiple fields to provide a unified multi-system view of how the brain exploits structure in time to optimize learning.

Original languageEnglish (US)
Pages (from-to)270-281
Number of pages12
JournalNeuroscience and Biobehavioral Reviews
StatePublished - Sep 2021


  • Adaptive learning
  • Bayesian inference
  • Event segmentation
  • Grid code
  • Reversal learning
  • Structure learning

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Cognitive Neuroscience
  • Behavioral Neuroscience


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