spikeresponse_tf

   [RESPONSE_CURVE] = SPIKERESPONSE_TF(STIMTIMES_ON, STIMTIMES_OFF, STIM_VALUES,
          SPIKETIMES, BINSIZE, FREQUENCY)

   Return a response curve of responses to the presentation
   of multiple stimuli. In this function, only the portion of the
   response that is modulated at temporal fequency FREQUENCY is
   reported.  Spike trains are first discretized into bins with
   binsize BINSIZE.

   The onset time of each stimulus should be in the vector STIMTIMES_ON,
   and the offset time of each stimulus should be in the vector
   STIMTIMES_OFF. STIM_VALUES should be a vector list with the value
   of the stimulus parameter for each stimulus that is indicated in
   STIMTIMES_ON and STIMTIMES_OFF. One can specify that a stimulus is
   "BLANK" or "CONTROL" by giving NaN as the STIM_VALUE for that stimulus.  
   SPIKETIMES are the spike times of a neuron in the %  same time
   units as STIMTIMES_ON and STIMTIMES_OFF. 

   Output:
     RESPONSE_CURVE is a struture with the following fields:
        curve        |  4xN matrix, where N is the number of distinct
                     |     stimuli; the first row has the stim values
                     |     the second row has the mean responses in 
                     |     spikes per time unit of STIMTIMES_ON/OFF,
                     |     the third row has the standard deivation of
                     |     these spike rates, and the fourth row has
                     |     the standard error.
        blank        |  1x3 vector with the mean, standard deviation, and
                     |     standard error.
        inds         |  1xN cell array; each value inds{i} has the individual
                           responses for the ith repetition of stimulus i
        blankinds    |  1xM vector with individual responses to the blank stimulus
        indexes      |  2xnum_stims Indicates where the nth stim is represented in
                     |     in inds (first column is stimid, second column is entry
                     |     number in vector inds{stimid})

     %  See help gaindriftexample for a description of the spike responses it generates.
     [spiketimes,r,t,stimon,stimoff,stimids,g]=gaindriftexample('gain_amplitude',0,'gain_offset',1,...
        'response_tf',4);
     % Step 2, use spikeresponse to calculate the actual responses
     response_curve = spikeresponse_tf(stimon,stimoff,stimids,spiketimes,0.001,4);
     % see if the average spikes are equal to what we expect from gaindriftexample's help
     abs(response_curve.curve(2,:)),

   See also: SPIKERESPONSE