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h-coefficient

version 1.2 (62.4 KB) by Michael
Generate MC simulated peristimulus time histograms and calculate their h-coefficient

735 Downloads

Updated 28 Oct 2014

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Peristimulus time histograms are a widespread form of visualizing neuronal responses. Kernel convolution methods transform these histograms into a smooth, continuous probability density function. This provides an improved estimate of a neuron’s actual response envelope. In a recent publication we developed a classifier, called the h-coefficient, to determine whether time-locked fluctuations in the firing rate of a neuron should be classified as a response or as random noise. Unlike previous approaches, the h-coefficient takes advantage of the more precise response envelope estimation provided by the kernel convolution method. The h-coefficient quantizes the smoothed response envelope and calculates the probability of a response of a given shape to occur by chance. Please refer to the original publication for further information.

Cite As

Michael (2022). h-coefficient (https://www.mathworks.com/matlabcentral/fileexchange/48293-h-coefficient), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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