# Cortical Interactions Underlying Sensory Representations

> **NIH NIH R01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $379,500

## Abstract

PROJECT SUMMARY
Sensory perception involves processing incoming sensory input and interpreting that information through rules
generated from prior experience. Stimulus features need to be bound together to form more complex sensory
representations and then associated with a valence or action outcome to give meaning to those representations.
In the mammalian neocortex, the formation of sensory representations is believed to occur through
processing that is distributed across several cortical areas. Beyond this general framework, the exact
circuits and computations involved in transforming sensory information into increasingly abstract
representations remain unknown. To achieve a deeper mechanistic understanding, it is necessary to close
the loop between theoretical models and experimental work and to identify common mechanisms through
comparative approaches across model systems. Many of the leading theoretical models for sensory
processing have been derived from experimental studies performed in humans or non-human primates. It
has been difficult to validate or refine these computational models because of the limited experimental
access to tools for circuit-level dissection in those species. However, novel tools for circuit dissection are
now available for applications in mice. Using newly developed whisker-based mouse behaviors that
recapitulate perceptual tasks in primates, we propose to investigate how stimulus information is encoded
and transformed across primary somatosensory, secondary somatosensory, and perirhinal cortex, three
prominent reciprocally connected areas that function at increasingly complex stages of sensory processing. Our
goal is to achieve a circuit-level understanding for how stimuli are bound to generate higher-order
representations, how such representations are associated with action outcomes, and how they are learned
and recalled as required for behavior. This work will provide critical new insight into how local and long-range
cortical circuits function to build internal representations and evaluate the external environment. By testing and
improving upon models of cortical function across mammalian species, we will seek to derive common principles
of circuit function that explain how increasingly invariant and abstract representations may be encoded and
implemented in the neocortex.

## Key facts

- **NIH application ID:** 9955376
- **Project number:** 5R01NS109965-03
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Jerry L Chen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $379,500
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9955376

## Citation

> US National Institutes of Health, RePORTER application 9955376, Cortical Interactions Underlying Sensory Representations (5R01NS109965-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9955376. Licensed CC0.

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