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Robust single neuron tracking of calcium imaging in behaving Hydra

View ORCID ProfileThibault Lagache, View ORCID ProfileAlison Hanson, View ORCID ProfileAdrienne Fairhall, View ORCID ProfileRafael Yuste
doi: https://doi.org/10.1101/2020.06.22.165696
Thibault Lagache
1Department of Biological Sciences, Columbia University, New York, NY 10027
2Neurotechnology Center, Columbia University, New York, NY 10027
3Kavli Institute of Brain Science, Columbia University, New York, NY 10027
4Marine Biological Laboratory in Woods Hole, MA 02543
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  • For correspondence: thibault.lagache@pasteur.fr
Alison Hanson
1Department of Biological Sciences, Columbia University, New York, NY 10027
2Neurotechnology Center, Columbia University, New York, NY 10027
3Kavli Institute of Brain Science, Columbia University, New York, NY 10027
4Marine Biological Laboratory in Woods Hole, MA 02543
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Adrienne Fairhall
4Marine Biological Laboratory in Woods Hole, MA 02543
5Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195
6UW Computational Neuroscience Center, University of Washington, Seattle, WA 98195
7WRF UW Institute for Neuroengineering, University of Washington, Seattle, WA 98195
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Rafael Yuste
1Department of Biological Sciences, Columbia University, New York, NY 10027
2Neurotechnology Center, Columbia University, New York, NY 10027
3Kavli Institute of Brain Science, Columbia University, New York, NY 10027
4Marine Biological Laboratory in Woods Hole, MA 02543
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Abstract

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic long-term monitoring of the activity of individual neurons and the subsequent statistical characterization of neuronal functional organization. We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC2) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from behaving Hydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth manual tracking of neurons, along with synthetic time-lapse sequences, covering a large range of particle motions and detectability parameters. Combining automatic monitoring of single neuron activity over long time-lapse sequences in behaving animals with statistical clustering, we characterize and map neuronal ensembles in behaving Hydra. We document the existence three major non-overlapping ensembles of neurons (CB, RP1 and RP2) whose activity correlates with contractions and elongations. Our results prove that the EMC2 algorithm can be used as a robust platform for neuronal tracking in behaving animals.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 23, 2020.
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Robust single neuron tracking of calcium imaging in behaving Hydra
Thibault Lagache, Alison Hanson, Adrienne Fairhall, Rafael Yuste
bioRxiv 2020.06.22.165696; doi: https://doi.org/10.1101/2020.06.22.165696
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Robust single neuron tracking of calcium imaging in behaving Hydra
Thibault Lagache, Alison Hanson, Adrienne Fairhall, Rafael Yuste
bioRxiv 2020.06.22.165696; doi: https://doi.org/10.1101/2020.06.22.165696

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