Influencia de la frecuencia respiratoria inducida en los valores HRV

Abstract

The study of Place Cells, hippocampal neurons tuned to spatial locations in the environment, is central to elucidate how the brain encodes and retrieves spatial information. Advances in genetic and imaging technologies have allowed keeping track of the dynamics of large ensembles of Place Cells across multiple days in mice. As the brain processes information at the neuronal population level, novel recording techniques such as in-vivo calcium imaging have the potential to unveil the mechanisms underlying the dynamics of place coding. However, with new recording paradigms comes the need to standardize and optimize the processing and first analysis stages of the data. In this work, we present our efforts in building a pipeline to process, extract, filter, track and analyze Place Cells from mice calcium imaging recordings in a linear-track experiment. To validate the pipeline, we show accurate prediction of the animal actions from the processed neural recordings. Finally, building on the previous steps, we present some tentative results on Place Cell turnover and the relation between predictive-accuracy and noise correlations.