h-coefficient

Versión 1.2 (62,4 KB) por Michael
Generate MC simulated peristimulus time histograms and calculate their h-coefficient
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Actualizado 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.

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Michael (2024). h-coefficient (https://www.mathworks.com/matlabcentral/fileexchange/48293-h-coefficient), MATLAB Central File Exchange. Recuperado .

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1.2

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