# Noise Sources and Strategies for Signal Quality Improvement in Biological Imaging: A Review Focused on Calcium and Cell Membrane Voltage Imaging

## TL;DR

This paper reviews the sources of noise in biological imaging and strategies to improve signal quality, focusing on calcium and membrane voltage measurements.

## Contribution

The paper systematically categorizes noise sources and mitigation strategies across four major imaging indicator classes.

## Key findings

- Signal degradation in biological imaging is categorized into photon shot noise, device-related errors, and sample-related errors.
- Mitigation strategies include hardware optimization, sensor selection, and computational correction methods.
- The review emphasizes the importance of experimental design and post-processing for improving data quality.

## Abstract

This review addresses the challenges of obtaining high-quality quantitative data in the optical imaging of membrane voltage and calcium dynamics. The paper provides a comprehensive overview and systematization of recent studies that analyze factors limiting signal fidelity and propose strategies to enhance data quality. The primary sources of signal degradation in biological optical imaging, with an emphasis on membrane voltage and calcium imaging, are systematically explored across four major indicator classes: voltage-sensitive dyes (VSDs), genetically encoded voltage indicators (GEVIs), calcium-sensitive dyes (CSDs), and genetically encoded calcium indicators (GECIs). Common mechanisms that compromise data quality are classified into three main categories: fundamental photon shot noise, device-related errors, and sample-related measurement errors. For each class of limitation, its physical or biological origin and characteristic manifestations are described, which are followed by an analysis of available mitigation strategies, including hardware optimization, choice of sensors, sample preparation and experimental design, post-processing and computational correction methods.