# Cortical Mechanisms of Visual Category Recognition and Learning

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2023 · $600,895

## Abstract

Summary and Relevance of Proposed Research
Humans have an impressive capacity to recognize the category membership of sensory stimuli. This ability,
which is disrupted by a brain-based diseases and conditions such as Alzheimer’s disease, schizophrenia,
stroke, and attention deficit disorder, is critical because it allows us to respond appropriately to the stimuli and
events that we encounter in the environment. We are not born with an innate library of categories, such as
“tables” and “chairs”, which we are preprogrammed to recognize. Instead, we learn to recognize familiar
categories through experience. Our recent work has shown that both the posterior parietal cortex (PPC) and
prefrontal cortex (PFC) are involved in categorical decisions. We recorded from neurons in PPC and PFC
during performance of visual motion categorization tasks. These recordings revealed that neurons in both
areas robustly encoded stimuli according to their learned category membership, suggesting that both regions
are involved in computing and representing abstract categorical information about visual stimuli. We also
showed that activity in PPC is causally related to categorical decisions, using reversible inactivation. This
project uses novel brain recording techniques to monitor the activity of large neuronal populations of neurons in
the lateral intraparietal area, frontal eye field, and superior colliculus during visual categorical decisions. This
will allow us to gain a mechanistic understanding of how interactions between neurons in these three regions
enable computations which transform visual feature encoding into categorical decisions. This work will also
determine how multiple behavioral functions are mediated by this brain network, including eye movements and
spatial attention, as well assess the causal significance of each brain area to categorical decisions.
While much is known about how the brain processes visual features (such as color, orientation, and direction
of motion), less is known about how the brain learns and represents the meaning, or category, of stimuli. A
greater understanding of visual categorization is critical for addressing a number of brain diseases and
conditions (e.g. stroke, Alzheimer’s disease, attention deficit disorder, schizophrenia, and stroke) that leave
patients impaired in everyday tasks that require visual learning, recognition and/or evaluating and responding
appropriately to sensory information. The long-term goal of this project is to guide the next generation of
treatments for these brain-based diseases and disorders by helping to develop a detailed understanding of the
brain mechanisms that underlie learning, memory and recognition. These studies also have relevance for
understanding and addressing learning disabilities, such as attention deficit disorder and dyslexia, which affect
a substantial fraction of school age children and young adults. Thus, a detailed understanding of the basic
brain mechanisms of categorical d...

## Key facts

- **NIH application ID:** 10680147
- **Project number:** 2R01EY019041-15
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** David J Freedman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $600,895
- **Award type:** 2
- **Project period:** 2009-09-01 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10680147

## Citation

> US National Institutes of Health, RePORTER application 10680147, Cortical Mechanisms of Visual Category Recognition and Learning (2R01EY019041-15). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10680147. Licensed CC0.

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