SBIR-STTR Award

Infrastructure automation for connectomic image analysis
Award last edited on: 2/16/2024

Sponsored Program
SBIR
Awarding Agency
NIH : NIMH
Total Award Amount
$497,283
Award Phase
2
Solicitation Topic Code
242
Principal Investigator
Nicholas Turner

Company Information

Zetta AI LLC

109 Broadmead Street
Princeton, NJ 08540
   (215) 917-3267
   ontact@zetta.ai
   www.zetta.ai
Location: Single
Congr. District: 12
County: Mercer

Phase I

Contract Number: 1R43MH131493-01
Start Date: 9/1/2022    Completed: 2/28/2024
Phase I year
2022
Phase I Amount
$334,576
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.

Public Health Relevance Statement:
Zetta AI will further automate its computational pipeline for reconstructing neural circuits from electron microscopy images. Circuit diagrams are a major priority of the BRAIN Initiative, and will aid the discovery of connectopathies and other structural pathologies that have long been hypothesized to be associated with brain disorders.

Project Terms:
Artificial Intelligence; AI system; Computer Reasoning; Machine Intelligence; Automation; Brain; Brain Nervous System; Encephalon; Brain Diseases; Brain Disorders; Encephalon Diseases; Intracranial CNS Disorders; Intracranial Central Nervous System Disorders; Client; Communities; Courtship; Drosophila genus; Drosophila; fruit fly; Engineering; Goals; Gold; Recording of previous events; History; Human; Modern Man; Institutes; Manuals; Maps; Electron Microscopy; Mining; Mission; Nerve; Nervous System; Neurologic Body System; Neurologic Organ System; Nervous system structure; Pathology; Private Sector; Research; Running; medical college; school of medicine; medical schools; Semantics; Synaptic; synapse; Synapses; Testing; Schedule; Data Set; Dataset; Caenorhabditis elegans; C elegans; C. elegans; C.elegans; base; Electron Microscope; Image Analysis; Image Analyses; image evaluation; image interpretation; Encapsulated; Phase; Ingestion; insight; Visual; WWW; web; world wide web; Internet; millimeter; System; success; Speed; Basic Research; Basic Science; Reporting; Coding System; Code; neural circuitry; neurocircuitry; synaptic circuit; synaptic circuitry; neural circuit; Functional RNA; Non-Coding; Non-Coding RNA; Non-translated RNA; Noncoding RNA; Nontranslated RNA; noncoding; Untranslated RNA; 3-D Images; 3-D image; 3D image; 3D images; Three-Dimensional Image; preventing; prevent; Defect; Data; Detection; transmission process; Transmission; Process; Image; imaging; cost; reconstruction; data acquisition; data format; operation; BRAIN initiative; Brain Research through Advancing Innovative Neurotechnologies initiative; microscopic imaging; microscope imaging; microscopy imaging; connectome; petabyte; cloud storage; cloud-based storage; Infrastructure; convolutional neural network; ConvNet; convolutional network; convolutional neural nets; analysis pipeline; computational pipelines

Phase II

Contract Number: 5R43MH131493-02
Start Date: 9/1/2022    Completed: 2/28/2024
Phase II year
2023
Phase II Amount
$162,707
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.

Public Health Relevance Statement:
Zetta AI will further automate its computational pipeline for reconstructing neural circuits from electron microscopy images. Circuit diagrams are a major priority of the BRAIN Initiative, and will aid the discovery of connectopathies and other structural pathologies that have long been hypothesized to be associated with brain disorders.

Project Terms:
Artificial Intelligence; AI system; Computer Reasoning; Machine Intelligence; Automation; Brain; Brain Nervous System; Encephalon; Brain Diseases; Brain Disorders; Encephalon Diseases; Intracranial CNS Disorders; Intracranial Central Nervous System Disorders; Client; Communities; Courtship; Drosophila genus; Drosophila; fruit fly; Engineering; Goals; Recording of previous events; History; histories; Human; Modern Man; Manuals; Maps; Electron Microscopy; Mining; Mission; Nerve; Nervous System; Neurologic Body System; Neurologic Organ System; Pathology; Private Sector; Research; Running; medical schools; medical college; school of medicine; Semantics; Synapses; Synaptic; synapse; Testing; Schedule; Data Set; C elegans; C. elegans; C.elegans; Caenorhabditis elegans; Electron Microscope; Image Analyses; image evaluation; image interpretation; Image Analysis; Encapsulated; Phase; ingest; Ingestion; insight; Visual; WWW; web; world wide web; Internet; millimeter; System; success; Speed; Basic Science; Basic Research; Reporting; Code; Coding System; neural circuit; neural circuitry; neurocircuitry; synaptic circuit; synaptic circuitry; Untranslated RNA; Functional RNA; Non-Coding; Non-Coding RNA; Non-translated RNA; Noncoding RNA; Nontranslated RNA; noncoding; 3-D Images; 3-D image; 3D image; 3D images; Three-Dimensional Image; preventing; prevent; Defect; Data; Detection; Resolution; resolutions; transmission process; Transmission; Process; Image; imaging; cost; reconstruction; data acquisitions; data acquisition; usability; data format; operations; operation; Brain Research through Advancing Innovative Neurotechnologies initiative; BRAIN initiative; microscope imaging; microscopy imaging; microscopic imaging; connectome; petabyte; cloud-based storage; cloud storage; Infrastructure; ConvNet; convolutional network; convolutional neural nets; convolutional neural network; analysis pipeline; computational pipelines