stimulus_response_scalar
STIMULUS_RESPONSE_SUMMARY - compute stimulus responses to stimuli
RESPONSE = STIMULUS_RESPONSE_SCALAR(TIMESERIES, TIMESTAMPS, STIM_ONSETOFFSETID, ...)
Inputs:
TIMESERIES is a 1xT array of the data values of the thing exhibiting the response, such as
a voltage signal, calcium dF/F signal, or spike signals (1s).
TIMESTAMPS is a 1xT array of the occurrences of the signals in TIMESERIES
STIM_ONSETOFFSETID is a variable that describes the stimulus history. Each row should
contain [stim_onset_time stim_offset_time stimid] where the times are in units of TIMESTAMPS (s).
Computes a structure RESPONSE with fields:
Field name: | Description:
------------------------------------------------------------------------
stimid | The stimulus id of each stimulus observed; there will be 1 value of stimid
| for each stimulus presentation (so stimid values may repeat many times)
response | The scalar response to each stimulus response.
control_response | The scalar response to the control stimulus for each stimulus
controlstimnumber | The stimulus number used as the control stimulus for each stimulus
parameters | A structure with the parameters used in the calculation (described below)
The behavior of the function can be modified by name/value pairs:
Parameter (default value) | Description:
------------------------------------------------------------------------
freq_response (0) | The frequency response to measure using FFT of TIMESERIES. Can be
| 0 (to use the mean response), or a number corresponding
| to the frequency to analyze. Can also be a vector
| the same size as the number of stimuli to indicate
| the frequency to be used for each stimulus (freq_response(stimid(i)).
| For example, to compute the response at the fundamental stimulus
| frequency (F1) when that frequency is 1 Hz, pass 1 for 'freq_response'.
control_stimid ([]) | Use this to pass the identity (or identities) of a 'blank' stimulus
| (some sort of control stimulus; in vision, this is often presenting
| a blank screen for same duration as the other stimuli.)
prestimulus_time ([]) | Calculate a baseline using a certain amount of TIMESERIES signal during
| the pre-stimulus time given here.
prestimulus_normalization ([])| Normalize the stimulus response based on the prestimulus measurement.
| [] or 0) No normalization
| 1) Subtract: Response := Response - PrestimResponse
| 2) Fractional change Response:= ((Response-PrestimResponse)/PrestimResponse)
| 3) Divide: Response:= Response ./ PreStimResponse
isspike (see right) | 0/1 Is the signal a spike process? If so, timestamps correspond to spike events.
spiketrain_dt (0.001) | Resolution to use for spike train reconstruction if computing Fourier transform