ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2024
Dissociable Contributions of Basolateral Amygdala and Ventrolateral Orbitofrontal Cortex to Flexible Learning Under Uncertainty.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Adaptive reorganization of history encoding in the retrosplenial cortex supports flexible decision-making strategies.Neuron · 2026Article
- Persistent representation of a prior schema in the orbitofrontal cortex facilitates learning of a conflicting schema.Nature communications · 2026Article
- Uncertainty and reward histories have distinct effects on decisions after wins and losses.Scientific reports · 2026Article
- Sex differences in task engagement and lapse rate during reward learning.Oxford open neuroscience · 2026Article
- Contribution of amygdala to dynamic model arbitration under uncertainty.Nature communications · 2025Article
- Neural coding of choice and outcome are modulated by uncertainty in orbitofrontal but not secondary motor cortex.Nature communications · 2025Article
- Adaptive reward representations integrate expected uncertainty signals in orbitofrontal cortex.Science advances · 2025Article
- A special role for anterior cingulate cortex, but not orbitofrontal cortex or basolateral amygdala, in choices involving information.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Comparative basolateral amygdala connectomics reveals dissociable single-neuron projection patterns to frontal cortex in macaques and mice.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
- Erratum issued
- Update of
Authors and funding
17 authors at 2 institutions in 2 countries.
Funding
Abstract
Reversal learning measures the ability to form flexible associations between choice outcomes with stimuli and actions that precede them. This type of learning is thought to rely on several cortical and subcortical areas, including the highly interconnected orbitofrontal cortex (OFC) and basolateral amygdala (BLA), and is often impaired in various neuropsychiatric and substance use disorders. However, the unique contributions of these regions to stimulus- and action-based reversal learning have not been systematically compared using a chemogenetic approach particularly before and after the first reversal that introduces new uncertainty. Here, we examined the roles of ventrolateral OFC (vlOFC) and BLA during reversal learning. Male and female rats were prepared with inhibitory designer receptors exclusively activated by designer drugs targeting projection neurons in these regions and tested on a series of deterministic and probabilistic reversals during which they learned about stimulus identity or side (left or right) associated with different reward probabilities. Using a counterbalanced within-subject design, we inhibited these regions prior to reversal sessions. We assessed initial and pre-/post-reversal changes in performance to measure learning and adjustments to reversals, respectively. We found that inhibition of the ventrolateral orbitofrontal cortex (vlOFC), but not BLA, eliminated adjustments to stimulus-based reversals. Inhibition of BLA, but not vlOFC, selectively impaired action-based probabilistic reversal learning, leaving deterministic reversal learning intact. vlOFC exhibited a sex-dependent role in early adjustment to action-based reversals, but not in overall learning. These results reveal dissociable roles for BLA and vlOFC in flexible learning and highlight a more crucial role for BLA in learning meaningful changes in the reward environment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.