Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set.
Julia BuhmannArlo SheridanCaroline Malin-MayorPhilipp SchlegelStephan GerhardTom KazimiersRenate KrauseTri M NguyenLarissa HeinrichWei-Chung Allen LeeRachel I WilsonStephan SaalfeldGregory S X E JefferisDavi D BockSrinivas C TuragaMatthew CookJan FunkePublished in: Nature methods (2021)
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.
Keyphrases
- electron microscopy
- resting state
- white matter
- functional connectivity
- hiv testing
- prefrontal cortex
- deep learning
- machine learning
- neural network
- bioinformatics analysis
- men who have sex with men
- cerebral ischemia
- convolutional neural network
- big data
- loop mediated isothermal amplification
- rna seq
- brain injury
- zika virus
- quantum dots
- data analysis