mloss.org Spike train feature extraction by Bayesian binninghttp://mloss.orgUpdates and additions to Spike train feature extraction by Bayesian binningenWed, 24 Sep 2008 16:19:14 -0000Spike train feature extraction by Bayesian binning 0.1http://mloss.org/software/view/67/<html><p><em>binsdfc</em> is a command line implementation of the algorithm described in <a href="http://books.nips.cc/nips20.html">Endres,Oram,Schindelin,Foldiak:<em>Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms</em>, Advances in NIPS, 2007</a>. It computes spike density functions (SDF) or peri-stimulus time histograms (PSTH). Given that it performs exact Bayesian averaging, the result is somewhere in the middle between the two: while the underlying model is comprised of bins like a PSTH, the averaging process gives rise to a more "continuous" prediction like a SDF.
<em>binsdfc</em> accepts input from stdin or a supplied file, and computes the expected SDF, its variance, latencies (as described in <a href="http://www.st-andrews.ac.uk/~dme2/binsdf.neucomp2007.pdf">Endres, Schindelin, Foldiak, Oram (2007): Examining the joint neural code of latency and firing rate by Bayesian binning</a>, paper will follow soon), and various other averages such as marginal likelihoods and model complexity posteriors.
This work is supported by a MRC training fellowship.
</p></html>Dominik EndresWed, 24 Sep 2008 16:19:14 -0000http://mloss.org/software/rss/comments/67http://mloss.org/software/view/67/bioinformaticsexact bayesian methodsneurosciencenips2008