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Who Is Talking to Whom: Synaptic Partner Detection in Anisotropic Volumes of Insect Brain


Kreshuk, Anna; Funke, Jan; Cardona, Albert; Hamprecht, Fred (2015). Who Is Talking to Whom: Synaptic Partner Detection in Anisotropic Volumes of Insect Brain. In: Navab, Nassir; et al. Lecture Notes in Computer Science. Cham: Springer, 661-668.

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.

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.

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Additional indexing

Item Type:Book Section, not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2015
Deposited On:09 Feb 2016 16:06
Last Modified:05 Apr 2016 20:04
Publisher:Springer
Additional Information:Chapter Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015
Publisher DOI:https://doi.org/10.1007/978-3-319-24553-9_81

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