Differential representations of prior and likelihood uncertainty in the human brain

Iris Vilares*, James D. Howard, Hugo L. Fernandes, Jay A. Gottfried, Konrad P. Kording

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

74 Scopus citations

Abstract

Background: Uncertainty shapes our perception of the world and the decisions we make. Two aspects of uncertainty are commonly distinguished: uncertainty in previously acquired knowledge (prior) and uncertainty in current sensory information (likelihood). Previous studies have established that humans can take both types of uncertainty into account, often in a way predicted by Bayesian statistics. However, the neural representations underlying these parameters remain poorly understood. Results: By varying prior and likelihood uncertainty in a decision-making task while performing neuroimaging in humans, we found that prior and likelihood uncertainty had quite distinct representations. Whereas likelihood uncertainty activated brain regions along the early stages of the visuomotor pathway, representations of prior uncertainty were identified in specialized brain areas outside this pathway, including putamen, amygdala, insula, and orbitofrontal cortex. Furthermore, the magnitude of brain activity in the putamen predicted individuals' personal tendencies to rely more on either prior or current information. Conclusions: Our results suggest different pathways by which prior and likelihood uncertainty map onto the human brain and provide a potential neural correlate for higher reliance on current or prior knowledge. Overall, these findings offer insights into the neural pathways that may allow humans to make decisions close to the optimal defined by a Bayesian statistical framework.

Original languageEnglish (US)
Pages (from-to)1641-1648
Number of pages8
JournalCurrent Biology
Volume22
Issue number18
DOIs
StatePublished - Sep 25 2012

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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