A comparison of methods to determine neuronal phase-response curves

TL;DR

This paper reviews and compares five methods for calculating neuronal phase-response curves, highlighting their reliability and providing guidelines for selecting the best method based on data quality and quantity.

Contribution

It offers a comprehensive comparison of existing PRC estimation methods and provides practical guidelines for their application in experimental and model data.

Findings

Reliability varies among methods depending on data fluctuations.

Number of spikes influences the accuracy of PRC estimation.

Guidelines help choose the appropriate method based on data conditions.

Abstract

The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data.