# Towards integrated 3D reconstruction of whole human brains at subcellular resolution

> **NIH NIH U01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2021 · $1,691,053

## Abstract

Project Summary
A detailed understanding of the anatomical and molecular architectures of brain cells and their brain-wide
organization is essential for interrogating human brain function and dysfunction. Extensive efforts have been
made toward mapping brain cells through various lenses, which have established invaluable databases
yielding new insights. However, integrative extraction of the multimodal properties of various cell-types
brain-wide within the same brain, crucial to elucidating complex intercellular relationships, remains nearly
impossible. We have developed high-throughput, cost-effective technology platforms to create a fully
integrated three-dimensional (3D) human brain cell atlas by simultaneously mapping high-dimensional
features (e.g., spatial, molecular, morphological, and microenvironment information) of all cells acquired
from the same whole brain. The proposed work will establish the most comprehensive 3D human brain map
to date, with unprecedented resolution and completeness. We envision that this atlas will facilitate the
integration of a broad range of studies and allow the research community to interrogate human brain
structure and function at multiple levels.
In Aim 1, we will apply a novel technology to transform whole human brain tissue into indestructible
hydrogel–tissue hybrids that allow highly multiplexed molecular labeling and subcellular-resolution volume
imaging. In Aim 2, we will apply scalable labeling and imaging technologies to map the brain-wide 3D
distribution of various cell-type and structural markers at subcellular resolution within the same brain. Our
chemical engineering–based approach to this aim will enable cost-effective, lossless 3D labeling of the
entire human brain at lower cost as traditional subsampling approaches. True volume labeling and
subcellular-resolution imaging will allow us to extract fine morphological and connectivity information from
labeled cells and reconstruct the microenvironment of all cells.
In Aim 3, we will use a host of rapid and highly automated algorithms to perform unbiased, integrative high-
dimensional phenotyping of all cells based on their spatial location, molecular expression, morphology, and
microenvironment. In Aim 4, we will perform super-resolution phenotyping of cells in a selected brain region
from the same sample used in Aim 3 to map inter-areal axonal connectivity at single-fiber resolution and to
characterize chemical synapses. This integrative approach will likely unveil unique cell-types and brain
regions, a crucial step toward a better understanding of brain function. The complete 3D dataset will be
linked to magnetic resonance and diffusion spectrum images and existing reference atlases to facilitate the
integration of a wide breadth of study at multiple levels and to make the data publicly accessible for mining
and analysis.

## Key facts

- **NIH application ID:** 10168641
- **Project number:** 5U01MH117072-04
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Kwanghun Chung
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,691,053
- **Award type:** 5
- **Project period:** 2018-08-22 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10168641

## Citation

> US National Institutes of Health, RePORTER application 10168641, Towards integrated 3D reconstruction of whole human brains at subcellular resolution (5U01MH117072-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10168641. Licensed CC0.

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