LZeroSpikeInference: A package for estimating spike times from calcium imaging data using an L0 penalty

This package implements an algorithm for deconvolving calcium imaging data for a single neuron in order to estimate the times at which the neuron spikes.

This algorithm solves the optimization problems

AR(1) model

minimize_{c1,...,cT} 0.5 sum_{t=1}^T ( y_t - c_t )^2 + lambda sum_{t=2}^T 1_{c_t neq gamma c_{t-1} }

for the global optimum, where y_t is the observed fluorescence at the tth timepoint.

AR(1) with intercept

minimize_{c1,...,cT,b1,...,bT} 0.5 sum_{t=1}^T (y_t - c_t - b_t)^2 + lambda sum_{t=2}^T 1_{c_t neq gamma c_{t-1}, b_t neq b_{t-1} }

where the indicator variable 1_{(A,B)} equals 1 if the event A cup B holds, and equals zero otherwise.

Install

If devtools is installed type

devtools::install_github("jewellsean/LZeroSpikeInference")

Usage

Once installed type

library(LZeroSpikeInference)
?LZeroSpikeInference

Reference

See Jewell and Witten, Exact Spike Train Inference Via L0 Optimization (2017)