Categories are a foundation of cognition. Imagine if we could not abstract the "essence" of experiences and had to learn anew about every unique object and situation. We would probably have dysfunctions like those seen in neuropsychiatric disorders like autism and schizophrenia, which are marked by an impaired ability to generalize and extract meaning from experience. While a great deal is known about the cortical organization of the processing of bottom-up sensory information, virtually nothing is known about the respective roles of different cortical areas in top-down processing, particularly categorization. This is because few neurophysiological investigations have directly compared neural correlates of categories across brain areas and, importantly, no neurophysiological study has manipulated the attributes that determine the level of categorization. We will do so while directly comparing neural activity in the prefrontal cortex (PFC) and lateral intraparietal area (LIP), two cortical areas that human and monkey studies indicate are engaged during visual categorization. We will test the hypothesis that the PFC plays the central role in extracting learned categories or that either the PFC or LIP will play the leading role in categorization depending on the level of category demand. We will record simultaneously two brain regions known to have neural correlates of categories the PFC and LIP in a task known to activate both areas in humans (dot pattern categorization). Monkeys will classify category exemplars formed by distorting prototypes of arbitrary dot patterns. Because dot patterns can be parametrically varied, we can manipulate fundamental category properties (abstractness, complexity, and number of alternative category decisions). Because virtually nothing is known about the how these manipulations affect the neural correlates of categories, any pattern of results will be informative and provide insight into the fundamental mechanisms by which the brain adds meaning to the world.

Public Health Relevance

This project addresses the neural basis of categorization, a fundamental cognitive ability that is disrupted in neuropsychiatric disorders like autism. Virtuall nothing is known on the neuron level about the cortical organization and respective contributions of different cortical areas because no neurophysiological study has ever manipulated category properties (abstractness, complexity, uncertainty) let alone compared them across brain areas. By doing so, we will answer fundamental and critical questions about the neural mechanisms the brain uses to make sense of the world.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
2R01MH065252-11
Application #
8369354
Study Section
Special Emphasis Panel (SPC)
Program Officer
Rossi, Andrew
Project Start
2002-04-01
Project End
2017-06-30
Budget Start
2012-08-10
Budget End
2013-06-30
Support Year
11
Fiscal Year
2012
Total Cost
$401,250
Indirect Cost
$151,250
Name
Massachusetts Institute of Technology
Department
Miscellaneous
Type
Schools of Arts and Sciences
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
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
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
Histed, Mark H; Pasupathy, Anitha; Miller, Earl K (2009) Learning substrates in the primate prefrontal cortex and striatum: sustained activity related to successful actions. Neuron 63:244-53
Nieder, Andreas; Miller, Earl K (2004) Analog numerical representations in rhesus monkeys: evidence for parallel processing. J Cogn Neurosci 16:889-901
Nieder, Andreas; Miller, Earl K (2004) A parieto-frontal network for visual numerical information in the monkey. Proc Natl Acad Sci U S A 101:7457-62
Nieder, Andreas; Miller, Earl K (2003) Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex. Neuron 37:149-57