SULAB (Single Unit Laboratory): PSTH optimization; KERNEL optimization; {Lv, Cv, logT}.

A Method for Selecting the Bin Size of a Time Histogram

This page was created by Hideaki Shimazaki in collaboration with Shigeru Shinomoto based on the theory published in Neural Computation 2007 [pdf], and Advances in NIPS 2007 [pdf].

The time-histogram method is a handy tool for capturing the instantaneous rate of spike occurrence. The bin width that critically determines the goodness of the fit of PSTH to the underlying rate has been selected by individual researchers in an unsystematic manner. Recently, we established a method for optimizing the bin size, so that the time-histogram best approximates the unknown underlying rate on the basis of mean integrated squared error. Here, we present a web application program that performs this optimization. You can obtain the optimal bin size and see the optimized time histogram, by simply copy-and-pasting your spike data.

Web application for bin size selection

1. Copy-and-paste spike sequences

4.37 3.87 4.00 4.03 3.50 4.08 2.25 4.70 1.73 4.93 1.73 4.62 3.43 4.25 1.68 3.92 3.68 3.10 4.03 1.77 4.08 1.75 3.20 1.85 4.62 1.97 4.50 3.92 4.35 2.33 3.83 1.88 4.60 1.80 4.73 1.77 4.57 1.85 3.52 4.00 3.70 3.72 4.25 3.58 3.80 3.77 3.75 2.50 4.50 4.10 3.70 3.80 3.43 4.00 2.27 4.40 4.05 4.25 3.33 2.00 4.33 2.93 4.58 1.90 3.58 3.73 3.73 1.82 4.63 3.50 4.00 3.67 1.67 4.60 1.67 4.00 1.80 4.42 1.90 4.63 2.93 3.50 1.97 4.28 1.83 4.13 1.83 4.65 4.20 3.93 4.33 1.83 4.53 2.03 4.18 4.43 4.07 4.13 3.95 4.10 2.27 4.58 1.90 4.50 1.95 4.83 4.12

2. Select a Bin Size

3. To obtain details, push

Web Application for the Bin Size Selection © 2006 2007 Hideaki Shimazaki

 The underlying formula:

[Neural Computation 2007]

Note that the optimal bin size diverges if only a small number of experimental trials are available from a moderately fluctuating rate process. In this case, any attempt to characterize the underlying spike rate will lead to spurious results. We also developed a formula with which one can estimate how many more trials are needed until the set of data can be analyzed with the required resolution. We wish to implement the web application program of this extrapolation method, in near future. For the derivation of the formula, see references below.

REFERENCES

[1] A method for selecting the bin size of a time histogram

H. Shimazaki and S. Shinomoto, Neural Computation 19 (2007) 1503-1527. [PDF]

[2] A recipe for optimizing a time-histogram

H. Shimazaki and S. Shinomoto, Advances in NIPS 19 (2007) 1289-1296. [PDF]

Version 2.1: Apr. 25^th 2007 (Version1.0: 12^th Dec 2006); The number of visitors since Apr. 12^th 2007:

If you have any questions, or have suggestions for improving the programs, please contact Shigeru Shinomoto, who is conducting these studies.