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Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set
- Source :
- Nature Methods. 18:771-774
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- We develop an automatic method for synaptic partner identification in insect brains and use it to predict synaptic partners in a whole-brain electron microscopy dataset of the fruit fly. The predictions can be used to infer a connectivity graph with high accuracy, thus allowing fast identification of neural pathways. To facilitate circuit reconstruction using our results, we develop CIRCUITMAP, a user interface add-on for the circuit annotation tool CATMAID. A deep-learning-based approach enables automatic identification of synaptically connected neurons in electron microscopy datasets of the fly brain.
- Subjects :
- 0303 health sciences
Computer science
business.industry
fungi
Connectivity graph
Pattern recognition
Cell Biology
Biochemistry
law.invention
Data set
03 medical and health sciences
Identification (information)
law
Artificial intelligence
User interface
Electron microscope
business
Molecular Biology
030304 developmental biology
Biotechnology
Subjects
Details
- ISSN :
- 15487105 and 15487091
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Nature Methods
- Accession number :
- edsair.doi...........0b7b1012ae8d1ba36bf9711a7cfdc41e
- Full Text :
- https://doi.org/10.1038/s41592-021-01183-7