Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia

Carlos Diuk, Karin Tsai, Jonathan Wallis, Matthew Botvinick, Yael Niv

Research output: Contribution to journalArticle

47 Scopus citations

Abstract

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

Original languageEnglish (US)
Pages (from-to)5797-5805
Number of pages9
JournalJournal of Neuroscience
Volume33
Issue number13
DOIs
StatePublished - Mar 27 2013

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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