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Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set.

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.

SUBMITTER: Buhmann J

PROVIDER: S-EPMC7611460 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set.

Buhmann Julia J Sheridan Arlo A Malin-Mayor Caroline C Schlegel Philipp P Gerhard Stephan S Kazimiers Tom T Krause Renate R Nguyen Tri M TM Heinrich Larissa L Lee Wei-Chung Allen WA Wilson Rachel R Saalfeld Stephan S Jefferis Gregory S X E GSXE Bock Davi D DD Turaga Srinivas C SC Cook Matthew M Funke Jan J

Nature methods 20210624 7

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. ...[more]

PMID: 34168373

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