A Graph Matching Approach to Tracking Neurons in Freely-MovingC. elegans

Author:

Jones CorinneORCID,Barzegar-Keshteli Mahsa,Gross Alice,Obozinski GuillaumeORCID,Rahi Sahand JamalORCID

Abstract

AbstractMotivationRecent advances in 3D microscopy allow for recording the neurons in freely-movingC. elegansat high frame rates. In order to read out calcium activity, it is necessary to track individual neurons from frame to frame. However, doing this by hand for tens of neurons in a single ten-minute recording requires more than a hundred hours. Moreover, most methods proposed in the literature for tracking neurons focus on immobilized or partially-immobilized worms and fail with freely-behaving worms.ResultsIn this paper we present an approach based on graph matching for tracking fluorescently-marked neurons in freely-movingC. elegans. Neurites (and sometimes neurons) can be oversegmented into pieces at the preprocessing phase; our algorithm allows several segments to match the same reference neuron or neurite. We demon-strate our method on three recordings. We find that with five labeled frames we can typically track the neurons and pieces of neurites with over 75% accuracy, with more reliable annotations for the most distinctive neurons.Availability and ImplementationThe code and preprocessed data will be made available upon publication.Contactcorinne.jones@epfl.ch

Publisher

Cold Spring Harbor Laboratory

Reference48 articles.

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