2021/02/18 by Laura A. M. D’Angelo, Antonio Canale, D'Angelo, Laura +5 · 3 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · #Advanced Chemical Sensor Technologies #Advanced Fluorescence Microscopy Techniques #Applications (stat.AP) #FOS: Computer and information sciences #Neural dynamics and brain function
paper · pdf · doi:10.48550/arxiv.2102.09403
openalex publication_date 2021/02/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent advancements in miniaturized fluorescence microscopy have made it possible to investigate neuronal responses to external stimuli in awake behaving animals through the analysis of intra-cellular calcium signals. An on-going challenge is deconvolving the temporal signals to extract the spike trains from the noisy calcium signals' time-series. In this manuscript, we propose a nested Bayesian finite mixture specification that allows the estimation of spiking activity and, simultaneously, reconstructing the distributions of the calcium transient spikes' amplitudes under different experimental conditions. The proposed model leverages two nested layers of random discrete mixture priors to borrow information between experiments and discover similarities in the distributional patterns of neuronal responses to different stimuli. Furthermore, the spikes' intensity values are also clustered within and between experimental conditions to determine the existence of common (recurring) response amplitudes. Simulation studies and the analysis of a data set from the Allen Brain Observatory show the effectiveness of the method in clustering and detecting neuronal activities.