# A robust, low-cost platform for EM connectomics

> **NIH NIH RF1** · ALLEN INSTITUTE · 2021 · $2,811,375

## Abstract

Project Summary/Abstract
Over the past decade, serial-section electron microscopy has come into its own as a method to study the
connectivity of neural circuits, from local circuits in mammals to entire invertebrate brains. Recently, the emphasis
in the field has been to create increasingly large data sets, while comparatively little effort has been spent on
making the tools of EM connectomics available to a large number of circuit neuroscientists. Obstacles exist at
multiple levels. Manual approaches to serial sectioning are prohibitively difficult, while automated approaches
require complex, expensive equipment that is difficult to deploy. High throughput scanning EM is limited to multi-
beam approaches that are extremely expensive. Transmission EM is far less expensive, but automated
approaches to sectioning remain challenging and require expensive substrates that are hard to manufacture and
difficult to use.
We propose to develop a new approach, already prototyped by our group and our industry partner, to establish
a robust platform optimized to achieve the widest possible adoption. The system will center on an open source
serial sectioning robot implementing a novel collection approach. The goal is to create a system that can be used
at a variety of scales, from the current state of the art (1 mm3 or greater), to small volumes that can be sectioned
and imaged routinely. Up to now, each published EM volume for connectomics has required a multi-year effort.
Instead, our goal is to use volume reconstruction as an assay, rather than an end unto itself, in the context of
other experiments. In the final year, we will create data sets that test the flexibility and robustness of the approach
by creating EM volumes ranging from 50µm on a side to very large volumes encompassing >1 mm3.

## Key facts

- **NIH application ID:** 10273540
- **Project number:** 1RF1MH123398-01A1
- **Recipient organization:** ALLEN INSTITUTE
- **Principal Investigator:** STEVEN JAY COOK
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $2,811,375
- **Award type:** 1
- **Project period:** 2021-07-15 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10273540

## Citation

> US National Institutes of Health, RePORTER application 10273540, A robust, low-cost platform for EM connectomics (1RF1MH123398-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10273540. Licensed CC0.

---

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