ArticleNature methods2022
SyConn2: dense synaptic connectivity inference for volume electron microscopy.
Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- vEMINR: Ultra-Fast Isotropic Reconstruction for Volume Electron Microscopy With Implicit Neural Representation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The songbird basal ganglia connectome.bioRxiv : the preprint server for biology · 2025Article
- An anatomical substrate of credit assignment in reinforcement learning.bioRxiv : the preprint server for biology · 2025Article
- CAVE: Connectome Annotation Versioning Engine.Nature methods · 2025Article
- WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.IEEE transactions on medical imaging · 2024Article
- Multi-layered maps of neuropil with segmentation-guided contrastive learning.Nature methods · 2023Article
- CAVE: Connectome Annotation Versioning Engine.bioRxiv : the preprint server for biology · 2023Article
- Jasmine and Iris: population-scale structural variant comparison and analysis.Nature methods · 2023Article
- Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain.Nature methods · 2022Article
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10 authors.
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Abstract
The ability to acquire ever larger datasets of brain tissue using volume electron microscopy leads to an increasing demand for the automated extraction of connectomic information. We introduce SyConn2, an open-source connectome analysis toolkit, which works with both on-site high-performance compute environments and rentable cloud computing clusters. SyConn2 was tested on connectomic datasets with more than 10 million synapses, provides a web-based visualization interface and makes these data amenable to complex anatomical and neuronal connectivity queries.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.