Multichannel-systems NeuroExplorer Uživatelský manuál stáhnout pdf (Strana 57)

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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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