title: Choice-correlated activity fluctuations underlie learning of neuronal category representation.
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.
authors.affiliation: 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.
authors.forename: Tatiana A
authors.initials: TA
authors.lastname: Engel
authors.affiliation: Department of Neurobiology, Yale University School of Medicine, Kavli Institute for Neuroscience, 333 Cedar Street, New Haven, Connecticut 06510, USA.
authors.forename: Warasinee
authors.initials: W
authors.lastname: Chaisangmongkon
authors.affiliation: Department of Neurobiology, The University of Chicago, 5812 S. Ellis Ave., Chicago, Illinois 60637, USA.
authors.forename: David J
authors.initials: DJ
authors.lastname: Freedman
authors.affiliation: 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.
authors.forename: Xiao-Jing
authors.initials: XJ
authors.lastname: Wang
mesh_terms: D000818:Animals; D002755:Choice Behavior / Q000502:physiology; D003071:Cognition / Q000502:physiology*; D004193:Discrimination Learning / Q000502:physiology*; D004567:Electrodes, Implanted; D056228:Feedback, Sensory / Q000502:physiology; D008253:Macaca mulatta / Q000502:physiology; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D010296:Parietal Lobe / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D012201:Reward