Next-generation AI for connectomics

New approaches in artificial intelligence (AI), such as foundation models and synthetic data, are having a substantial impact on many areas of applied computer science. Here we discuss the potential to apply these developments to the computational challenges associated with producing synapse-resolut...

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Bibliographic Details
Published inNature methods Vol. 21; no. 8; pp. 1398 - 1399
Main Authors Januszewski, Michał, Jain, Viren
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.08.2024
Nature Publishing Group
Subjects
631/114/1564
631/378/116
Animals
Artificial Intelligence
Automation
Bioinformatics
Biological Microscopy
Biological Techniques
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Brain - physiology
Brain research
Comment
Computer science
Connectome - methods
Humans
Life Sciences
Machine learning
Preprints
Proteomics
Synapses
Synthetic data
Online AccessGet full text
ISSN1548-7091
1548-7105
1548-7105
DOI10.1038/s41592-024-02336-0

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Summary:New approaches in artificial intelligence (AI), such as foundation models and synthetic data, are having a substantial impact on many areas of applied computer science. Here we discuss the potential to apply these developments to the computational challenges associated with producing synapse-resolution maps of nervous systems, an area in which major ambitions are currently bottlenecked by AI performance.
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ISSN:1548-7091
1548-7105
1548-7105
DOI:10.1038/s41592-024-02336-0