# Infrastructure automation for connectomic image analysis

> **NIH NIH R43** · ZETTA AI, LLC · 2022 · $334,576

## Abstract

The BRAIN 2025 report states that a major goal of the US BRAIN Initiative is "Generate circuit diagrams," and
identifies electron microscopy (EM) as "the gold standard for circuit mapping." So far EM is the only approach
that has ever delivered a connectome, a map of all synaptic connections in a nervous system or brain. After
the C. elegans connectome in the 1980s, the labor of manual image analysis prevented the EM approach from
generalizing to larger nervous systems. Since then, labor has been dramatically reduced by progress in
artificial intelligence. Humans need only correct the errors that remain in an automated reconstruction. Zetta AI
was founded to make connectomic image analysis accessible to any neuroscientist. In 2021, Zetta completed
an automated reconstruction of a cubic millimeter cortical volume for the Allen Institute. This is one of only
three existing petascale reconstructions in the world. For the Harvard Medical School, Zetta also completed an
automated reconstruction of the Drosophila ventral nerve cord. These successes establish Zetta as a leading
organization in connectomics. Zetta’s image analysis pipeline requires significant engineering labor to operate.
Based on our operations over the past two years, we have identified several opportunities for engineering labor
reduction by process automation, including EM image ingestion, image alignment, and hard example mining.
Such process automation will help make connectomics accessible to all neuroscientists. Availability of neural
circuit diagrams will aid the discovery of connectopathies and other structural pathologies that have long been
hypothesized to be associated with brain disorders.

## Key facts

- **NIH application ID:** 10547607
- **Project number:** 1R43MH131493-01
- **Recipient organization:** ZETTA AI, LLC
- **Principal Investigator:** Thomas Macrina
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $334,576
- **Award type:** 1
- **Project period:** 2022-09-01 → 2024-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547607

## Citation

> US National Institutes of Health, RePORTER application 10547607, Infrastructure automation for connectomic image analysis (1R43MH131493-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10547607. Licensed CC0.

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