# EM Core

> **NIH NIH U19** · HARVARD UNIVERSITY · 2021 · $573,771

## Abstract

EM Core - Abstract
While the neural circuits that underlie behavior are of interest to all of the investigators on this grant (and a substantial part
of the entire neuroscience community), there have been very few technical approaches that actually provide this kind of
information across all levels at which circuits function, including the level of synaptic connections. This electron
microscopy core is explicitly designed to provide the “wiring diagrams” of neural circuits in an efficient way. Much of our
effort over the past 5 years has been to transform serial electron microscopy of large volumes (such as the fish nervous
system) from a heroic to a more mundane enterprise. This transformation required innovations in hardware and software
to abbreviate all the time-consuming steps in the connectomic pipeline. In particular we: 1) automated ultra-thin
sectioning (using a tape-based approach), 2) automated image acquisition (using a custom multibeam serial electron
microscope), 3) automated stitching and registration of the image data on high performance computing clusters, 4)
automated segmentation of neurons and synapses on a GPU cluster, and 5) semi-automated proofreading and rendering of
the neural circuits with custom software. Because of these developments, we can routinely collect tens of thousands of
sections losslessly at 30 nm thickness and acquire images of them at lateral resolutions of 4 x 4 nanometers. This voxel
size (480 nm3​ ​) provides enough detail for human or machine vision methods to trace out the finest aspects of neural
connectivity. Obtaining this information about neural circuits is relevant inasmuch as it provides insight into circuit
function. Hence the tremendous benefit of doing electron microscopy on functionally imaged samples - a main goal of this
proposal.
Acquiring these circuits is also relevant if neuronal connectivity can be associated with cells of particular types, hence the
significant benefit of doing analysis of cell types that have been defined in the fish atlas associated with this proposal.
Finally, these circuit diagrams provide ground truth for testing and refining computational theories of brain function,
another important prong of this proposal. Because of the speed of the EM Core approaches, we have the ability to acquire
datasets of many different fish that each have been used in particular experimental or live-cell imaging contexts. The
overarching goal being to provide synaptic level structural information for all research questions where such detailed data
can enhance our comprehension of the way fish behavior is instantiated in its nervous system.

## Key facts

- **NIH application ID:** 10241481
- **Project number:** 5U19NS104653-05
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Jeff W Lichtman
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $573,771
- **Award type:** 5
- **Project period:** 2017-09-25 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10241481

## Citation

> US National Institutes of Health, RePORTER application 10241481, EM Core (5U19NS104653-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10241481. Licensed CC0.

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