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A Probability Distribution over Latent Causes, in the Orbitofrontal Cortex

Author(s): Chan, Stephanie C.Y.; Niv, Yael; Norman, Kenneth A.

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Abstract: The orbitofrontal cortex (OFC) has been implicated in both the representation of “state,” in studies of reinforcement learning and decision making, and also in the representation of “schemas,” in studies of episodic memory. Both of these cognitive constructs require a similar inference about the underlying situation or “latent cause” that generates our observations at any given time. The statistically optimal solution to this inference problem is to use Bayes' rule to compute a posterior probability distribution over latent causes. To test whether such a posterior probability distribution is represented in the OFC, we tasked human participants with inferring a probability distribution over four possible latent causes, based on their observations. Using fMRI pattern similarity analyses, we found that BOLD activity in the OFC is best explained as representing the (log-transformed) posterior distribution over latent causes. Furthermore, this pattern explained OFC activity better than other task-relevant alternatives, such as the most probable latent cause, the most recent observation, or the uncertainty over latent causes.
Publication Date: 27-Jul-2016
Electronic Publication Date: 27-Jul-2016
Citation: Chan, Stephanie CY, Niv, Yael, Norman, Kenneth A. (2016). A Probability Distribution over Latent Causes, in the Orbitofrontal Cortex. The Journal of Neuroscience, 36 (30), 7817 - 7828. doi:10.1523/JNEUROSCI.0659-16.2016
DOI: doi:10.1523/JNEUROSCI.0659-16.2016
ISSN: 0270-6474
EISSN: 1529-2401
Pages: 7817 - 7828
Type of Material: Journal Article
Journal/Proceeding Title: The Journal of Neuroscience
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.

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