# A Tool for Synapse-level Circuit Analysis of Human Cerebral Cortex Specimens.

> **NIH NIH UG3** · HARVARD UNIVERSITY · 2021 · $1,169,015

## Abstract

Project Summary/Abstract
The goal of this work is to facilitate synaptic level analysis of neurons and their interconnecting microcircuits in
neurosurgical cerebral cortex biopsies from human patients. These full-thickness human cerebral cortex biopsies
will be provided by neurosurgical colleagues from patients undergoing resective surgery or surgical implantation
of leads for deep brain stimulation (DBS). Once we have demonstrated that the techniques and tools are
sufficiently reliable, we will analyze neural circuits in samples from medical centers that study psychiatric and
neurological disorders. In the initial phase we will: 1) optimize the removal of undamaged brain biopsies during
neurosurgical procedures and transfer new techniques for immersion fixation and osmium staining to large (>5
cubic millimeter) fresh brain biopsies from human patients.; 2) we will optimize, with hardware and software
changes, the speed and reliability of multibeam scanning electron microscopy image acquisition to automatically
acquire synapse-level neural circuitry at petabyte scale in brain volumes that connect tens of thousands of
neurons via hundreds of millions of synapses; 3) we will transfer methods to co-register molecular labels (for cell
-types) with serial electron microscopy of the same human samples using very small novel immuno-probes that
do not require permeabilization and hence, do not negatively impact the quality of the brain’s ultrastructure in
order to identify ultrastructural correlates for each cell type; and 4) we will work with computer scientists at
Argonne National Laboratory to develop a robust computational connectomics pipeline for stitching, alignment,
segmentation, and storage of human brain circuits. This public platform will augment the efforts of a team at
Google that is already begun working on our human samples. In the second phase, we will run many human
biopsies through the image acquisition and analysis connectomic pipelines. We will use new software to compare
circuit variability within and between individuals. We contend that detailed neural circuit analysis in human brain
tissue that bridges scales from nanometers to millimeters is a prerequisite for understanding how the normal
brain functions and discovering the pathological underpinnings of cognitive and developmental disorders. Our
goal is that the methods we develop will be disseminated, becoming part of the toolbox for both neuropathology
and fundamental human neuroscience.

## Key facts

- **NIH application ID:** 10271724
- **Project number:** 1UG3MH123386-01A1
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Jeff W Lichtman
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,169,015
- **Award type:** 1
- **Project period:** 2021-09-13 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10271724

## Citation

> US National Institutes of Health, RePORTER application 10271724, A Tool for Synapse-level Circuit Analysis of Human Cerebral Cortex Specimens. (1UG3MH123386-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10271724. Licensed CC0.

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