# Spike Detection Using FRI Methods and Protein Calcium Sensors: Performance Analysis and Comparisons

## TL;DR

This paper compares new protein calcium sensors with traditional dyes for detecting neural spikes using FRI methods, showing high performance and calculating detection accuracy limits.

## Contribution

The paper introduces a performance comparison of GCaMP6 sensors and Oregon Green BAPTA-1 using FRI methods and Cramér-Rao bounds for spike detection.

## Key findings

- FRI algorithm performs well on surrogate data for both GCaMP6 and Oregon Green BAPTA-1.
- Cramér-Rao lower bounds show the uncertainty limits for spike detection with each calcium indicator.

## Abstract

Fast and accurate detection of action potentials from neurophysiological data is key to the study of information processing in the nervous system. Previous work has shown that finite rate of innovation (FRI) theory can be used to successfully reconstruct spike trains from noisy calcium imaging data. This is due to the fact that calcium imaging data can be modeled as streams of decaying exponentials which are a subclass of FRI signals. Recent progress in the development of genetically encoded calcium indicators (GECIs) has produced protein calcium sensors that exceed the sensitivity of the synthetic dyes traditionally used in calcium imaging experiments. In this paper, we compare the suitability for spike detection of the kinetics of a new family of GECIs (the GCaMP6 family) with the synthetic dye Oregon Green BAPTA-1. We demonstrate the high performance of the FRI algorithm on surrogate data for each calcium indicator and we calculate the Cramér-Rao lower bound on the uncertainty of the position of a detected spike in calcium imaging data for each calcium indicator.