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Main Menu - Block
- Overview
 - Anatomy and Histology
 - Cryo-Electron Microscopy
 - Electron Microscopy
 - Flow Cytometry
 - Gene Targeting and Transgenics
 - High Performance Computing
 - Immortalized Cell Line Culture
 - Integrative Imaging
 - Invertebrate Shared Resource
 - Janelia Experimental Technology
 - Mass Spectrometry
 - Media Prep
 - Molecular Genomics
 - Primary & iPS Cell Culture
 - Project Pipeline Support
 - Project Technical Resources
 - Quantitative Genomics
 - Scientific Computing
 - Viral Tools
 - Vivarium
 
Abstract
Automated reconstruction of neural connectivity graphs from electron microscopy image stacks is an essential step towards large-scale neural circuit mapping. While significant progress has recently been made in automated segmentation of neurons and detection of synapses, the problem of synaptic partner assignment for polyadic (one-to-many) synapses, prevalent in the Drosophila brain, remains unsolved. In this contribution, we propose a method which automatically assigns pre- and postsynaptic roles to neurites adjacent to a synaptic site. The method constructs a probabilistic graphical model over potential synaptic partner pairs which includes factors to account for a high rate of one-to-many connections, as well as the possibility of the same neuron to be pre-synaptic in one synapse and post-synaptic in another. The algorithm has been validated on a publicly available stack of ssTEM images of Drosophila neural tissue and has been shown to reconstruct most of the synaptic relations correctly.

