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Open AccessArticle

Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques

1
Department of Physics, “Sapienza” University of Rome, 00185 Rome, Italy
2
IIT—Neural Computation Lab, [email protected], 38068 Rovereto, Italy
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INFN, 00185 Rome, Italy
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PhD Program in Behavioural Neuroscience,“Sapienza” University of Rome, 00185 Rome, Italy
5
PhD Program in Cognitive Neuroscience, SISSA, 34136 Trieste, Italy
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LENS, University of Florence, 50019 Florence, Italy
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Istituto di Neuroscienze, CNR, 56124 Pisa, Italy
8
Department of Physics, University of Florence, 50019 Florence, Italy
*
Author to whom correspondence should be addressed.
Methods Protoc. 2020, 3(1), 14; https://doi.org/10.3390/mps3010014
Received: 12 November 2019 / Revised: 10 January 2020 / Accepted: 22 January 2020 / Published: 31 January 2020
Slow waves (SWs) are spatio-temporal patterns of cortical activity that occur both during natural sleep and anesthesia and are preserved across species. Even though electrophysiological recordings have been largely used to characterize brain states, they are limited in the spatial resolution and cannot target specific neuronal population. Recently, large-scale optical imaging techniques coupled with functional indicators overcame these restrictions, and new pipelines of analysis and novel approaches of SWs modelling are needed to extract relevant features of the spatio-temporal dynamics of SWs from these highly spatially resolved data-sets. Here we combined wide-field fluorescence microscopy and a transgenic mouse model expressing a calcium indicator (GCaMP6f) in excitatory neurons to study SW propagation over the meso-scale under ketamine anesthesia. We developed a versatile analysis pipeline to identify and quantify the spatio-temporal propagation of the SWs. Moreover, we designed a computational simulator based on a simple theoretical model, which takes into account the statistics of neuronal activity, the response of fluorescence proteins and the slow waves dynamics. The simulator was capable of synthesizing artificial signals that could reliably reproduce several features of the SWs observed in vivo, thus enabling a calibration tool for the analysis pipeline. Comparison of experimental and simulated data shows the robustness of the analysis tools and its potential to uncover mechanistic insights of the Slow Wave Activity (SWA). View Full-Text
Keywords: slow wave activity; GCamP6f; wide-field microscopy; spatio-temporal dynamics; in vivo Imaging; data analysis methods; toy-model simulation slow wave activity; GCamP6f; wide-field microscopy; spatio-temporal dynamics; in vivo Imaging; data analysis methods; toy-model simulation
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Celotto, M.; De Luca, C.; Muratore, P.; Resta, F.; Allegra Mascaro, A.L.; Pavone, F.S.; De Bonis, G.; Paolucci, P.S. Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques. Methods Protoc. 2020, 3, 14.

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