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.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZRG1-IFCN-E (02))
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Rossi, Andrew
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Massachusetts Institute of Technology
Other Basic Sciences
Schools of Arts and Sciences
United States
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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
Roy, Jefferson E; Buschman, Timothy J; Miller, Earl K (2014) PFC neurons reflect categorical decisions about ambiguous stimuli. J Cogn Neurosci 26:1283-91
Antzoulatos, Evan G; Miller, Earl K (2014) Increases in functional connectivity between prefrontal cortex and striatum during category learning. Neuron 83:216-25
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
Seger, Carol A; Miller, Earl K (2010) Category learning in the brain. Annu Rev Neurosci 33:203-19
Roy, Jefferson E; Riesenhuber, Maximilian; Poggio, Tomaso et al. (2010) Prefrontal cortex activity during flexible categorization. J Neurosci 30:8519-28
Cromer, Jason A; Roy, Jefferson E; Miller, Earl K (2010) Representation of multiple, independent categories in the primate prefrontal cortex. Neuron 66:796-807

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