Journal article
Automatic monitoring of neural activity with single-cell resolution in behaving Hydra
Scientific reports, Vol.14(1), pp.5083-5083
03/01/2024
DOI: 10.1038/s41598-024-55608-2
PMCID: PMC10907378
PMID: 38429381
Abstract
The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris . We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron’s calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra , and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.
Details
- Title: Subtitle
- Automatic monitoring of neural activity with single-cell resolution in behaving Hydra
- Creators
- Alison Hanson - Columbia UniversityRaphael Reme - Analyse d'images biologiques - Biological Image AnalysisNoah Telerman - Columbia UniversityWataru Yamamoto - Columbia UniversityJean-Christophe Olivo-Marin - Analyse d'images biologiques - Biological Image AnalysisThibault Lagache - Analyse d'images biologiques - Biological Image AnalysisRafael Yuste - Columbia University
- Resource Type
- Journal article
- Publication Details
- Scientific reports, Vol.14(1), pp.5083-5083
- DOI
- 10.1038/s41598-024-55608-2
- PMID
- 38429381
- PMCID
- PMC10907378
- NLM abbreviation
- Sci Rep
- ISSN
- 2045-2322
- eISSN
- 2045-2322
- Publisher
- Nature Publishing Group
- Language
- English
- Date published
- 03/01/2024
- Academic Unit
- Psychiatry
- Record Identifier
- 9984823119902771
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