# Development of a scalable strategy for reconstructing cell-type determined connectome of the mammalian brain

> **NIH NIH RF1** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $3,918,397

## Abstract

Abstract
In order to fully understand the structural substrates underlying the brain function, it is central to curate
multiple attributes of the same neurons. The important attributes include, but limited to morphology,
connection properties and molecular patterns, such as the expression of functional genes and the
distribution of synaptic densities. Light microscopy-based neuronal tracing has contributed our
fundamental understanding of the heterogeneity of neuronal morphology. Aligning morphology
reconstructions of extremely sparsely labeled neurons from multiple brain samples onto a common
coordinate system permitted systematic comparison of the receptive dendritic fields and the projective
axonal arbors of distinct neuronal subtypes. However, connection partners of neurons cannot be
identified from the light microscopy-based reconstructions due to the nature of sparse sampling and
limited resolution. On the other hand, electron microscopy-based reconstructions label all the cell
nondifferential but permit recognition of ultra-fine structures, including synaptic contacts, which in theory
permits mapping the complete connectome between all neurons. However, it is technically and
economically challenging to scale lossless electron microscopy to a large sample, such as the mouse
brain. In addition, molecular information is often lost in sample processing. In this project, we propose
to develop a scalable strategy that combines several novel technologies to permit reconstructing a
molecular connectome of the mammalian brain by light microscopy. Being able to simultaneous profile
neuronal morphology, connectivity and molecular properties throughout the whole mouse brain will
clarify our understanding of the heterogeneity of brain cells and advance our knowledge about the
overall architecture of the mammalian brain with unprecedented resolution and scale.

## Key facts

- **NIH application ID:** 10088842
- **Project number:** 1RF1MH124611-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Dawen Cai
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $3,918,397
- **Award type:** 1
- **Project period:** 2020-09-14 → 2024-09-13

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10088842

## Citation

> US National Institutes of Health, RePORTER application 10088842, Development of a scalable strategy for reconstructing cell-type determined connectome of the mammalian brain (1RF1MH124611-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10088842. Licensed CC0.

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