Spike detection for calcium activity

Biermé Hermine (), Constant Camille (), Duittoz Anne () and Georgelin Christine ()
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Biermé Hermine: LMA UMR CNRS 7348, Université de Poitiers Bât. H3 - Site du Futuroscope, TSA 61125, 11 bd Marie et Pierre Curie, 86073 Poitiers Cedex 9, France
Constant Camille: LMA UMR CNRS 7348, Université de Poitiers Bât. H3 - Site du Futuroscope, TSA 61125, 11 bd Marie et Pierre Curie, 86073 Poitiers Cedex 9, France
Duittoz Anne: CNRS, IFCE, INRAE, Université de Tours, PRC, F-37380, Nouzilly, France
Georgelin Christine: IDP UMR CNRS 7013, Université de Tours, Université d’Orléans, Parc de Grandmont 37200 Tours, France

The International Journal of Biostatistics, 2022, vol. 18, issue 2, 627-675

Abstract: We present in this paper a global methodology for the spike detection in a biological context of fluorescence recording of GnRH-neurons calcium activity. For this purpose we first propose a simple stochastic model that could mimic experimental time series by considering an autoregressive AR(1) process with a linear trend and specific innovations involving spiking times. Estimators of parameters with asymptotic normality are established and used to set up a statistical test on estimated innovations in order to detect spikes. We compare several procedures and illustrate on biological data the performance of our procedure.

Keywords: autoregressive process; neuronal activity; peaks detection; time series; 62M10; 62F12; 62F03; Secondary: 92B25 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/ijb-2020-0043

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