Deconvolution of calcium imaging data using marked point processes.

Ryohei Shibue,Fumiyasu Komaki,Blake A. Richards

doi:10.1371/journal.pcbi.1007650

Ryohei Shibue, Fumiyasu Komaki + Show 1 more

Open Access

https://doi.org/10.1371/journal.pcbi.1007650

Copy DOI

Abstract

Calcium imaging has been widely used for measuring spiking activities of neurons. When using calcium imaging, we need to extract summarized information from the raw movie beforehand. Recent studies have used matrix deconvolution for this preprocessing. However, such an approach can neither directly estimate the generative mechanism of spike trains nor use stimulus information that has a strong influence on neural activities. Here, we propose a new deconvolution method for calcium imaging using marked point processes. We consider that the observed movie is generated from a probabilistic model with marked point processes as hidden variables, and we calculate the posterior of these variables using a variational inference approach. Our method can simultaneously estimate various kinds of information, such as cell shape, spike occurrence time, and tuning curve. We apply our method to simulated and experimental data to verify its performance.

Highlights

In recent years, many researchers have used calcium imaging to measure spiking activities in large neuron populations
To compare the performance quantitatively in terms of spike detection and regions of interest (ROI) detection, we calculated the F-measure to evaluate the performance of binary classification
Recent studies have used the matrix deconvolution approach for this preprocessing; such an approach ignores the spiking nature of the neurons, and it cannot use the covariates information, which may have a great influence on the spiking activities

Summary

Introduction

Many researchers have used calcium imaging to measure spiking activities in large neuron populations. Calcium imaging is an imaging technique that observes calcium ion concentrations inside neurons as a movie. This technique enables researchers to obtain various types of information about the neurons that cannot be obtained by the potential measurement approach. Calcium imaging offers a considerable amount of information, it is difficult to deal with the observed movie directly. When using calcium imaging to investigate the structure of the brain system, we need to extract crucial information from the raw movie beforehand. For example, the cell shapes, positions, and spiking times of neurons are extracted from the raw movie

Objectives

Methods

Results

Conclusion