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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

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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.

Comments and Ratings (1)

Matt No

Cool idea, but the code is not ready for use. The main function lacks documentation and contains many hard-coded constants that depend on the data.

Updates

1.2

Minor bug fixes during launch phase...

1.1.0.0

Minor bug fixes during launch phase...

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
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