Spike Train Analysis Toolkit Documentation  Spike Train Analysis Toolkit Function Reference  binless

Spike Train Analysis Toolkit

binless

BINLESS Binless method analysis.
   Y = BINLESS(X,OPTS) performs a binless method to find the amount
   of information conveyed by the spike trains in X about their
   category membership. The results are stored in the structure
   Y.

   The members of Y are:
      Y.times: A cell array of spike trains. See BINLESSOPEN
         for details.
      Y.counts: A cell array of spike counts. See BINLESSOPEN
         for details.
      Y.categories: A vector of the categories of the spike
         trains. SEE BINLESSOPEN for details.
      Y.warped: A warped version of the spike trains. See
         BINLESSWARP for details.
      Y.embedded: An embedded version of the spike trains. See
         BINLESSEMBED for details.
      Y.I_part: The information conveyed by zero-distance spike
         trains and singletons. See BINLESSINFO for details.  
      Y.I_cont: The continuous component of the information
         which describes the separability of the embedded spike
         trains.See BINLESSINFO for details. 
      Y.I_count: The information conveyed by the number of
         spikes in the spike trains. See BINLESSINFO for details. 
      Y.I_total: The sum of all of the information
         components. See BINLESSINFO for details. 

   The options and parameters for this function are:
      OPTS.start_time: The start time of the analysis window. The
         default is the maximum of all of the start times in X. 
      OPTS.end_time: The end time of the analysis window. The
         default is the minimum of all of the end times in X.
      OPTS.start_warp: The lower limit of the warping. The default
         is -1.  
      OPTS.end_warp: The upper limit of the warping. The
         default is 1. 
      OPTS.warping_strategy: The strategy for warping. 
         OPTS.warping_strategy=0 means the spike times in X are
            linearly scaled to fall between OPTS.start_warp and
            opts.end_warp.  
         OPTS.warping_strategy=1 means the spike times are
            uniformly spaced between OPTS.start_warp and
            opts.end_warp.  
         The default value is 1.
      OPTS.min_embed_dim: The minimal embedding dimension. The
         default is 1.  
      OPTS.max_embed_dim: The maximal embedding dimension. The
         default is 2.  
      OPTS.stratification_strategy: The strategy for stratifying
         spike trains by spike count. 
         OPTS.stratification_strategy=0 puts all spike trains
            in a single stratum. 
         OPTS.stratification_strategy=1 stratifies spike trains
            by spike count. Each spike count gets its own
            stratum. 
         OPTS.stratification_strategy=2 is similar to option 1
            except that all spike trains with more than
            OPTS.embed_dim_max-OPTS.embed_dim_min spikes go into a
            single stratum. 
         The default value is 2.
      OPTS.singleton_strategy: The strategy for handling
         singletons.  
         OPTS.singleton_strategy=0 means that singletons are
            considered uninformative and are ignored. 
         OPTS.singleton_strategy=1 means that singletons are
            considered maximally informative and are included.
         The default value is 0.

   Y = BINLESS(X) uses the default options and parameters.

   [Y,OPTS_USED] = BINLESS(X) or [Y,OPTS_USED] = BINLESS(X,OPTS)
   additionally return the options used. 

   See also BINLESSOPEN, BINLESSWARP, BINLESSEMBED, BINLESSINFO,
   BINLESS_SHUF, BINLESS_JACK.

Cross-reference information

This function calls:

This function is called by:


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