Perceptual Classification in a Rapidly Changing Environment

Humans and monkeys can learn to classify perceptual information in a statistically optimal fashion if the functional groupings remain stable over many hundreds of trials, but little is known about categorization when the environment changes rapidly. Here, we used a combination of computational model...

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Bibliographic Details
Published in:Neuron (Cambridge, Mass.) Mass.), 2011-08, Vol.71 (4), p.725-736
Main Authors: Summerfield, Christopher, Behrens, Timothy E., Koechlin, Etienne
Format: Article
Language:English
Subjects:
Adolescent
Adult
Animals
Bayes Theorem
Brain - anatomy & histology
Brain - physiology
Brain Mapping
Brain research
Choice Behavior - physiology
Computer Simulation
Decision making
Environment
Expected values
Haplorhini
Humans
Judgment - physiology
Magnetic Resonance Imaging
Memory, Short-Term - physiology
Models, Neurological
Perception - physiology
Photic Stimulation - methods
Reaction Time
Volatility
Young Adult
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Summary:Humans and monkeys can learn to classify perceptual information in a statistically optimal fashion if the functional groupings remain stable over many hundreds of trials, but little is known about categorization when the environment changes rapidly. Here, we used a combination of computational modeling and functional neuroimaging to understand how humans classify visual stimuli drawn from categories whose mean and variance jumped unpredictably. Models based on optimal learning (Bayesian model) and a cognitive strategy (working memory model) both explained unique variance in choice, reaction time, and brain activity. However, the working memory model was the best predictor of performance in volatile environments, whereas statistically optimal performance emerged in periods of relative stability. Bayesian and working memory models predicted decision-related activity in distinct regions of the prefrontal cortex and midbrain. These findings suggest that perceptual category judgments, like value-guided choices, may be guided by multiple controllers. ► Human categorization judgments are guided by both Bayesian and cognitive strategies ► Decision strategy varies with environmental volatility ► Distinct prefrontal and midbrain regions are activated by different strategies
ISSN:0896-6273
1097-4199
DOI:10.1016/j.neuron.2011.06.022