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Spike Train Analysis Toolkit

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METRIC Metric space analysis
   Y = METRIC(X,OPTS) performs a metric space 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. If OPTS.shift_cost is a vector (see below), then Y will be a
   vector of output structures.

   The members of Y are:
      Y.categories: A vector of the spike train category
      indices. See METRICOPEN for details.
      Y.d: The matrix of the distances between all possible spike
         train pairs. See METRICDIST for details.
      Y.cm: The confusion matrix resulting from clustering of the
         distances. See METRICCLUST for details.
      Y.table: A HIST2D structure version of the confusion
         matrix. See MATRIX2HIST2D and INFO2D 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.shift_cost: The cost of shifting a spike per unit time
         relative to inserting or deleting a spike. This option may
         be a vector of such values. The default is
         1/(end_time-start_time).
      OPTS.label_cost: This applies only to data sets with
         simultaneously recorded spike trains. It is the cost of
         altering a spike's label, and may range from 0 to 2. This
         option may be a vector of such values whose length is equal
         to OPTS.shift_cost. The default is 0.
      OPTS.metric_family: Selects the metric to be used.
         OPTS.metric_family=0: Uses D^spike metric.
         OPTS.metric_family=1: Uses D^interval metric. This is
            only applicable to single-site data.
         The default value is 0.
      OPTS.parallel: Selects which algorithm version to
         use.
         OPTS.parallel=0: Computes distances for a single shift_cost,
             label_cost pairs at a time.
         OPTS.parallel=1: Uses an algorithm that computes the
             distances for all shift_cost,label_cost pairs
             concurrently. When many parameters sets are being
             analyzed, this method can provide considerable
             computational savings. 
         The default value is 0 if OPTS.shift_cost has one element
             and 1 if OPTS.shift_cost has multiple elements.
      OPTS.clustering_exponent: A constant that controls the
         clustering. Negative values emphasize smaller distances
         and positive values emphasize larger distances. The
         default is -2.

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

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

   See also METRICDIST, METRICCLUST, MATRIX2HIST2D, INFO2D, METRIC_SHUF,
   METRIC_JACK.

Cross-reference information

This function calls:

This function is called by:


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