Multichannel-systems NeuroExplorer Manuel d'utilisateur télécharger pdf (Page 118)

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Summary of Numerical Results

The following information is available in the Summary of Numerical Results

Column Description

Variable Variable name.

YMin Y axis minimum.

YMax Y axis maximum.

Color Scale Min Color scale minimum.

Color Scale Max Color scale maximum.

Algorithm

If Use Log Bins and Axes option is not selected:

Matrix of binCounts[x,y] is created. Each element of the matrix is initialized as zero.

For each spike that occurred at time t[i], the following values are calculated:

Interval_I = t[i] - t[i-1]

binX = (Interval_I – MinInterval)/Bin

Interval_I_Plus_1 = t[i+1] - t[i]

binY = (Interval_I_Plus_1 – MinInterval)/Bin

Then, the corresponding bin count is incremented:

binCounts[binX, binY] = binCounts[binX, binY] + 1

The graph shows binCounts matrix values using color scale.

If Use Log Bins and Axes option is selected:

The i-th bin (i=1,2,...) on each axis is [IntMin * 10 ^ ((i -1)/D), IntMin * 10 ^ (i/D)), where D is Number

of Bins Per Decade. binX and binY are calculated accordingly:

binX = ( log10(Interval_I) – log10(MinInterval) )* NumBinsPerDecade

Reference

For discussion on using logarithm of interspike intervals, see:

Alan D. Dorval, Probability distributions of the logarithm of inter-spike intervals yield accurate entropy

estimates from small datasets. Journal of Neuroscience Methods 173 (2008) 129–139

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Multichannel-systems NeuroExplorer Manuel d'utilisateur Page 118

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