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Nat Commun. 2015 Mar 11;6:6454. doi: 10.1038/ncomms7454.

Choice-correlated activity fluctuations underlie learning of neuronal category representation.

Author information

1
1] Department of Neurobiology, Yale University School of Medicine, Kavli Institute for Neuroscience, 333 Cedar Street, New Haven, Connecticut 06510, USA [2] Department of Bioengineering, Stanford University, 318 Campus Drive, Stanford, California 94305, USA.
2
Department of Neurobiology, Yale University School of Medicine, Kavli Institute for Neuroscience, 333 Cedar Street, New Haven, Connecticut 06510, USA.
3
Department of Neurobiology, The University of Chicago, 5812 S. Ellis Ave., Chicago, Illinois 60637, USA.
4
1] Department of Neurobiology, Yale University School of Medicine, Kavli Institute for Neuroscience, 333 Cedar Street, New Haven, Connecticut 06510, USA [2] Center for Neural Science, New York University, 4 Washington Place, New York, New York 10003, USA [3] NYU-ECNU Joint Institute of Brain and Cognitive Science, NYU-Shanghai, Shanghai 200122, China.

Abstract

The ability to categorize stimuli into discrete behaviourally relevant groups is an essential cognitive function. To elucidate the neural mechanisms underlying categorization, we constructed a cortical circuit model that is capable of learning a motion categorization task through reward-dependent plasticity. Here we show that stable category representations develop in neurons intermediate to sensory and decision layers if they exhibit choice-correlated activity fluctuations (choice probability). In the model, choice probability and task-specific interneuronal correlations emerge from plasticity of top-down projections from decision neurons. Specific model predictions are confirmed by analysis of single-neuron activity from the monkey parietal cortex, which reveals a mixture of directional and categorical tuning, and a positive correlation between category selectivity and choice probability. Beyond demonstrating a circuit mechanism for categorization, the present work suggests a key role of plastic top-down feedback in simultaneously shaping both neural tuning and correlated neural variability.

PMID:
25759251
PMCID:
PMC4382677
DOI:
10.1038/ncomms7454
[Indexed for MEDLINE]
Free PMC Article

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