# Fluorescence-based methods for microconnectivity analysis in neocortex

> **NIH NIH RF1** · CARNEGIE-MELLON UNIVERSITY · 2022 · $1,597,011

## Abstract

ABSTRACT
A comprehensive census of neural cell types in the brain, together with molecular-genetic
resources for cell-type specific labeling, is revolutionizing our ability to detect and monitor age,
disease, and experience-dependent changes in neural connectivity. Fluorescence-based
methods for quantitative synapse analysis would be easily adopted by the scientific community
and have been widely used in neuronal cultures, but have not been well-developed for analysis
of connectivity in brain networks, due to concerns about resolution and accuracy of detected
contacts and difficulty of reagent use. Here we will use recently-developed tools for fluorescent
synaptic labeling to develop a workflow to evaluate and mitigate concerns about fluorescence-
based measurements in brain tissue using state-of-the-art Expansion Microscopy methods. We
will then test the ability of these reagents to drive new insights about input-specific plasticity
during learning, using a well-characterized training paradigm where electrophysiological
changes in thalamocortical synaptic strength have been demonstrated.

## Key facts

- **NIH application ID:** 10413555
- **Project number:** 1RF1MH129267-01
- **Recipient organization:** CARNEGIE-MELLON UNIVERSITY
- **Principal Investigator:** ALISON L BARTH
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,597,011
- **Award type:** 1
- **Project period:** 2022-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10413555

## Citation

> US National Institutes of Health, RePORTER application 10413555, Fluorescence-based methods for microconnectivity analysis in neocortex (1RF1MH129267-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10413555. Licensed CC0.

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