Multichannel Systems NeuroExplorer - Manual (Page 57)

For example, for the first bin
bin_count = number of interspike intervals (isi)
such that isi >= IntMin and isi < IntMin + Bin
If Normalization is Counts/Bin, no further calculations are performed.
If Normalization is Probability, bin counts are divided by the number of interspike intervals in the
spike train.
If Normalization is Spikes/Sec, bin counts are divided by NumInt*Bin, where NumInt is the number
of interspike intervals in the spike train.
If Use Log Bins and X Axis option is selected:
The i-th bin (i=1,2,...) is [IntMin * 10 ^ ((i -1)/D), IntMin * 10 ^ (i/D)), where D is the Number of Bins
Per Decade. For each bin, the number of interspike intervals within this bin is calculated. 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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