Functionally dissociable influences on learning rate in a dynamic environment
Open accessAbstract
Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics, and fMRI to show that adaptive learning is not a unitary phenomenon in the brain. Rather, it can be decomposed into three computationally and neuroanatomically distinct factors that were evident in human subjects performing a spatial-prediction task: (1) surprise-driven belief updating, related to BOLD activity in visual cortex; (2) uncertainty-driven belief updating, related to anterior prefrontal and parietal activity; and (3) reward-driven belief updating, a context-inappropriate behavioral tendency related to activity in ventral striatum. These distinct factors converged in a core system governing adaptive learning. This system, which included dorsomedial frontal cortex, responded to all three factors and predicted belief updating both across trials and across individuals.
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When some amount of uncertainty is expected, learning rates should decrease.
“When some amount of uncertainty is expected (also referred to as outcome variance or risk), learning rates should decrease.10–14”
From Serotonin neurons modulate learning rate through uncertainty (2022) · cites this paper as [13]
Deviations from expected uncertainty should increase learning rates.
“Here, deviations from expected uncertainty (“unexpected uncertainty”) should increase learning rates.8,12,13,15–18”
From Serotonin neurons modulate learning rate through uncertainty (2022) · cites this paper as [13]
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References 48 · Cited by 299
- Authors
- McGuire, J. T., Nassar, M. R., Gold, J. I., & Kable, J. W.
- Affiliations
- University of Pennsylvania (US)
- Brown University (US)
- Corresponding author
- Kable, Joseph W.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2014-11
- Volume
- 84
- Issue
- 4
- Pages
- 870-881
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4437663
- OpenAlex
- W2133512499
- Cited by
- 299
- References
- 48
- Citations by year
- 2026: 19 · 2025: 36 · 2024: 40 · 2023: 18 · 2022: 22 · 2021: 25 · 2020: 31 · 2019: 24 · 2018: 34 · 2017: 24 · 2016: 21 · 2015: 4 · 2014: 1
- FWCI
- 9.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- ScholarlyCommons (University of Pennsylvania) (submittedVersion, cc-by-nc-nd)
- ScholarlyCommons (University of Pennsylvania) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (F31MH093099, R01MH098899)
- National Institute on Drug Abuse (F32DA030870)
- National Institute of Neurological Disorders and Stroke (P30NS045839)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- adaptive learning, learning rate, belief updating, surprise, uncertainty, reward, spatial prediction, visual cortex, dorsomedial frontal cortex, ventral striatum, anterior prefrontal cortex, parietal cortex, dynamic environments, individual differences
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Environment, Female, Humans, Image Processing, Computer-Assisted, Learning, Magnetic Resonance Imaging, Male, Reward, Uncertainty, Young Adult, Functional Neuroimaging
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