Complementary contributions of basolateral amygdala and orbitofrontal cortex to value learning under uncertainty
Abstract
We make choices based on the values of expected outcomes, informed by previous experience in similar settings. When the outcomes of our decisions consistently violate expectations, new learning is needed to maximize rewards. Yet not every surprising event indicates a meaningful change in the environment. Even when conditions are stable overall, outcomes of a single experience can still be unpredictable due to small fluctuations (i.e., expected uncertainty) in reward or costs. In the present work, we investigate causal contributions of the basolateral amygdala (BLA) and orbitofrontal cortex (OFC) in rats to learning under expected outcome uncertainty in a novel delay-based task that incorporates both predictable fluctuations and directional shifts in outcome values. We demonstrate that OFC is required to accurately represent the distribution of wait times to stabilize choice preferences despite trial-by-trial fluctuations in outcomes, whereas BLA is necessary for the facilitation of learning in response to surprising events.
Article and author information
Author details
Funding
UCLA's Division of Life Sciences Recruitment and Retention fund
- Alicia Izquierdo
Opportunity Fund
- Alicia Izquierdo
Academic Senate Grant
- Alicia Izquierdo
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. Research protocols (#2013-094-13A) were approved by the Chancellor's Animal Research Committee at the University of California, Los Angeles. All surgeries were performed under isoflurane anesthesia, and every effort was made to minimize suffering.
Copyright
© 2017, Stolyarova & Izquierdo
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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