The ability to extract meaning from experience by abstracting categories and other generalized principles is a foundation of cognition. It is disrupted in neuropsychiatric diseases like autism and schizophrenia. During the last funding period, we used novel behavioral paradigms to identify neural correlates of categories in the prefrontal cortex (PFC), the brain area most central to cognition and implicated in neuropsychiatric disorders. We now aim to use our lab's expertise in category learning and multiple electrode recording in behaving monkeys to address a basic question of neural representation: are PFC neurons cognitive generalists or specialists? This critical question is unresolved because virtually all neurophysiologists train monkeys on a single cognitive problem. We will train monkeys on multiple categorical distinctions and extensively survey neuron activity in three PFC subdivisions (lateral, dorsal, and orbital) using 48 microelectrodes. Two major classes of theories of PFC function make different predictions. Generalist/adaptive theories predict many neurons that each represent multiple category distinctions. Specialist/localist theories predict single neurons dedicated to each distinction. Reality may lie somewhere between. Answering such fundamental questions about neural specificity and localization is how we arrived at our current understanding of sensory and motor processing. Our goal is to provide such an understanding for cognition and the brain area most central to normal cognition. Because categorization is a foundation of cognition, data from this project has the potential to impact on a wide range of behavior and human disorders. Our long-term goal is to provide understanding of this critical cognitive function and by doing so open a path to drug and behavioral therapies that will alleviate neuropsychiatric disorders. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH065252-07
Application #
7340489
Study Section
Special Emphasis Panel (ZRG1-IFCN-E (02))
Program Officer
Rossi, Andrew
Project Start
2002-04-01
Project End
2012-01-31
Budget Start
2008-03-01
Budget End
2009-01-31
Support Year
7
Fiscal Year
2008
Total Cost
$348,230
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Other Basic Sciences
Type
Schools of Arts and Sciences
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
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Villagrasa, Francesc; Baladron, Javier; Vitay, Julien et al. (2018) On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach. J Neurosci 38:9551-9562
Wutz, Andreas; Loonis, Roman; Roy, Jefferson E et al. (2018) Different Levels of Category Abstraction by Different Dynamics in Different Prefrontal Areas. Neuron 97:716-726.e8
Loonis, Roman F; Brincat, Scott L; Antzoulatos, Evan G et al. (2017) A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning. Neuron 96:521-534.e7
Antzoulatos, Evan G; Miller, Earl K (2016) Synchronous beta rhythms of frontoparietal networks support only behaviorally relevant representations. Elife 5:
McKee, Jillian L; Riesenhuber, Maximilian; Miller, Earl K et al. (2014) Task dependence of visual and category representations in prefrontal and inferior temporal cortices. J Neurosci 34:16065-75
Antzoulatos, Evan G; Miller, Earl K (2014) Increases in functional connectivity between prefrontal cortex and striatum during category learning. Neuron 83:216-25
Roy, Jefferson E; Buschman, Timothy J; Miller, Earl K (2014) PFC neurons reflect categorical decisions about ambiguous stimuli. J Cogn Neurosci 26:1283-91
Cromer, Jason A; Roy, Jefferson E; Buschman, Timothy J et al. (2011) Comparison of primate prefrontal and premotor cortex neuronal activity during visual categorization. J Cogn Neurosci 23:3355-65
Antzoulatos, Evan G; Miller, Earl K (2011) Differences between neural activity in prefrontal cortex and striatum during learning of novel abstract categories. Neuron 71:243-9

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