spikeresponse
[RESPONSE_CURVE] = SPIKERESPONSE(STIMTIMES_ON, STIMTIMES_OFF, STIM_VALUES, SPIKETIMES)
Return a response curve of responses to the presentation
of multiple stimuli. 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})
Test example:
% Step 1, use gaindriftexample.m to generate spike responses.
% 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);
% Step 2, use spikeresponse to calculate the actual responses
response_curve = spikeresponse(stimon,stimoff,stimids,spiketimes);
% see if the average spikes are equal to what we expect from gaindriftexample's help
response_curve.curve(2,:),
See also: SPIKERESPONSE_TF