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Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques.
Celotto, Marco; De Luca, Chiara; Resta, Paolo Muratore Francesco; Allegra Mascaro, Anna Letizia; Pavone, Francesco Saverio; De Bonis, Giulia; Paolucci, Pier Stanislao.
Afiliación
  • Celotto M; Department of Physics, "Sapienza" University of Rome, 00185 Rome, Italy.
  • De Luca C; IIT-Neural Computation Lab, CNCS@UniTn, 38068 Rovereto, Italy.
  • Resta PMF; Department of Physics, "Sapienza" University of Rome, 00185 Rome, Italy.
  • Allegra Mascaro AL; INFN, 00185 Rome, Italy.
  • Pavone FS; PhD Program in Behavioural Neuroscience,"Sapienza" University of Rome, 00185 Rome, Italy.
  • De Bonis G; Department of Physics, "Sapienza" University of Rome, 00185 Rome, Italy.
  • Paolucci PS; PhD Program in Cognitive Neuroscience, SISSA, 34136 Trieste, Italy.
Methods Protoc ; 3(1)2020 Jan 31.
Article en En | MEDLINE | ID: mdl-32023996
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).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Methods Protoc Año: 2020 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Methods Protoc Año: 2020 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza