Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory

George Cantwell, Matthew J. Crossley, F. Gregory Ashby*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Virtually all current theories of category learning assume that humans learn new categories by gradually forming associations directly between stimuli and responses. In information-integration category-learning tasks, this purported process is thought to depend on procedural learning implemented via dopamine-dependent cortical-striatal synaptic plasticity. This article proposes a new, neurobiologically detailed model of procedural category learning that, unlike previous models, does not assume associations are made directly from stimulus to response. Rather, the traditional stimulus-response (S-R) models are replaced with a two-stage learning process. Multiple streams of evidence (behavioral, as well as anatomical and fMRI) are used as inspiration for the new model, which synthesizes evidence of multiple distinct cortical-striatal loops into a neurocomputational theory. An experiment is reported to test a priori predictions of the new model that: (1) recovery from a full reversal should be easier than learning new categories equated for difficulty, and (2) reversal learning in procedural tasks is mediated within the striatum via dopamine-dependent synaptic plasticity. The results confirm the predictions of the new two-stage model and are incompatible with existing S-R models.

Original languageEnglish
Pages (from-to)1598-1613
Number of pages16
JournalPsychonomic Bulletin and Review
Issue number6
Publication statusPublished - Dec 2015
Externally publishedYes


  • categorization
  • procedural learning
  • striatum


Dive into the research topics of 'Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory'. Together they form a unique fingerprint.

Cite this