Multichannel Systems NeuroExplorer - Manual (Page 118)

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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