# A 3D multimodal micron-scale human brain atlas bridging single cell data, neuropathology and neuroradiology

> **NIH NIH RF1** · COLD SPRING HARBOR LABORATORY · 2021 · $5,278,129

## Abstract

Digitized reference brains, also referred to as Common Coordinate Frameworks (CCFs), together
with superposed atlas annotations, are of central importance to neuroscience. They bear the
same relation to neuroscience as do reference genomes and genome annotations to cellular and
molecular biology. Strikingly, however, such reference brains for humans lag far behind the
corresponding CCFs for non-human model organisms such as the laboratory mouse. Existing
data sets either have sections spaced relatively far apart or lack in-plane resolution down to the
micron scale. Crucially, existing data sets are not well connected to the major areas in medicine
that deal with the human brain, namely neuroradiology and neuropathology.
We will meet this need by creating an unprecedented micron-scale, 3D atlas that combines
multiple MRI modalities as well as continuous serial section histology. In particular, the reference
atlas will consist of Nissl, Myelin and H&E stains, with 20 micron contiguous serial sections, and
approximately ~8000 sections/brain. We will do so using the tape-transfer method, which
preserves tissue geometry even in the presence of disconnected pieces to the brain being
sectioned, and permits 3D reassembly of the sections into a 3D volume. We will utilize
diffeomorphic mapping methods to co-register the MRI and histological data, and will create a
human brain CCF in which single-cell transcriptomic and epigenomic data can be pinned in order
to create a Human Brain Cell atlas.
We will use machine learning approaches to segment cells and processes in these images and
to algorithmically detect cytoarchitectonic boundaries; such machine learning methods will also
be used to predict histology and cytoarchitecture from MRI data, with our collected data as a
training set. We will make our data freely available to scientists as well as medical professionals
through an online data portal with a multi-resolution viewer for zooming and panning through
terapixel image data, and also deposit the data in a shared data repository to make it easily
accessible to other researchers. We will connect our data to a unique on-line neuropathology
resource containing over a petabyte of neuropathological images, including H&E stained sections
from the coronal plane. We expect that the reference brain data we produce will become the de-
facto standard for a high-resolution reference atlas for the human brain.

## Key facts

- **NIH application ID:** 10370064
- **Project number:** 1RF1MH128875-01
- **Recipient organization:** COLD SPRING HARBOR LABORATORY
- **Principal Investigator:** PARTHA Pratim MITRA
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $5,278,129
- **Award type:** 1
- **Project period:** 2021-09-15 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10370064

## Citation

> US National Institutes of Health, RePORTER application 10370064, A 3D multimodal micron-scale human brain atlas bridging single cell data, neuropathology and neuroradiology (1RF1MH128875-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10370064. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*