Granger causality analysis for calcium transients in neuronal networks, challenges and improvements
Abstract
One challenge in neuroscience is to understand how information flows between neurons in vivo to trigger specific behaviors. Granger causality (GC) has been proposed as a simple and effective measure for identifying dynamical interactions. At single-cell resolution however, GC analysis is rarely used compared to directionless correlation analysis. Here, we study the applicability of GC analysis for calcium imaging data in diverse contexts. We first show that despite underlying linearity assumptions, GC analysis successfully retrieves non-linear interactions in a synthetic network simulating intracellular calcium fluctuations of spiking neurons. We highlight the potential pitfalls of applying GC analysis on real in vivo calcium signals, and offer solutions regarding the choice of GC analysis parameters. We took advantage of calcium imaging datasets from motoneurons in embryonic zebrafish to show how the improved GC can retrieve true underlying information flow. Applied to the network of brainstem neurons of larval zebrafish, our pipeline reveals strong driver neurons in the locus of the mesencephalic locomotor region (MLR), driving target neurons matching expectations from anatomical and physiological studies. Altogether, this practical toolbox can be applied on in vivo population calcium signals to increase the selectivity of GC to infer flow of information across neurons.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. All data used in our manuscript have been pre- viously published (references [32, 33] in the manuscript). Modelling code is available on the github: https://github.com/statbiophys/zebrafishGCData files are available: https://zenodo.org/record/6774389#.Yr1Rm5PMKEs
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larval motoneuron datahttps://zenodo.org/record/6774389#.Yr1Rm5PMKEs.
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hinbrain locomotion datahttps://zenodo.org/record/6774389#.Yr1Rm5PMKEs.
Article and author information
Author details
Funding
European Research Council (COG 724208)
- Aleksandra M Walczak
European Research Council (COG 101002870)
- Claire Wyart
New York Stem Cell Foundation (NYSCF-R-NI39)
- Claire Wyart
Human Frontier Science Program (RGP0063/2018)
- Claire Wyart
Fondation pour la Recherche Médicale (FRM- EQU202003010612)
- Claire Wyart
Fondation Bettencourt-Schueller (FBS-don-0031)
- Claire Wyart
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Chen et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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