# PRINCIPLES OF PRESYNAPTIC NETWORKS FOR SINGLE LAYER 2/3 NEURONS IN FERRET VISUAL CORTEX

> **NIH NIH R00** · UNIVERSITY OF PENNSYLVANIA · 2022 · $128,614

## Abstract

Principles of presynaptic networks for single layer 2/3 neurons in ferret visual cortex
Single neurons in neocortical circuits are driven by presynaptic networks composed of excitatory and inhibitory
neurons. Each neuron's population of presynaptic partners determines how incoming information is processed.
A longstanding view of cortical circuits is that a majority of synaptic inputs originate from local networks through
horizontal (recurrent) connections. However, the mechanisms by which recurrent networks shape the activity of
cortical neurons is largely unknown. Additionally, synaptic and cellular mechanisms proposed by theoretical
models rely on studies of the rodent visual cortex, which is increasingly shown to differ from that of carnivores
and primates in organization and function. This proposal aims to address these problems by mapping
presynaptic excitatory and inhibitory cells of single layer 2/3 neurons and dissect how they act to selectively
modulate neural activity in ferret V1 in vivo. This proposal uses a novel combination of advanced optical
techniques and electrophysiology, building off the candidates
optical
create
has a deep background in in vivo physiology and
 imaging in a wide variety of mammalian species and training during the K99 phase. This proposal will
 the foundation for an innovative, multidisciplinary, and independent research program to establish
fundamental principles of cortical circuits, ultimately providing a scaffold for understanding disorders, such as
schizophrenia and autism, which show profound impairments in the processing of sensory signals.

## Key facts

- **NIH application ID:** 10675228
- **Project number:** 3R00EY031137-04S1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Benjamin Kyle Scholl
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $128,614
- **Award type:** 3
- **Project period:** 2021-09-30 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10675228

## Citation

> US National Institutes of Health, RePORTER application 10675228, PRINCIPLES OF PRESYNAPTIC NETWORKS FOR SINGLE LAYER 2/3 NEURONS IN FERRET VISUAL CORTEX (3R00EY031137-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10675228. Licensed CC0.

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