Saccade Cookbook

Analysis

Finally, you can start some high-level analysis (see also saccade [[1]])

After all these obligatory steps, you can actually start analyzing the data. This usually involves custom-made analysis functions, suited for your experiment. First, you have to load the data:

load MW-RG-2011-03-02-0001

You will now have a Sac- and a Stim-matrix. The Sac-matrix contains all the movement parameters, the Stim-matrix all the stimulus parameters. You can combine them into a single matrix, containing in each column a relevant parameter, and each row containing a single saccade.

SupSac = pa_supersac(Sac,Stim,XX,YY);

Note that the XX and YY should be numbers describing the type of stimulus, and the number of that type of stimulus in the trial, e.g.

SupSac = pa_supersac(Sac,Stim,1,2);

for the second (YY=2) stimulus of type 1 (XX=1, usually an LED) in a trial, or

SupSac = pa_supersac(Sac,Stim,2,1);

for the first (YY=1) stimulus of type 2 (XX=2, usually a sound) in the trial (you have to check what number is assigned to which stimulus type, by typing:

help pa_readcsv

in the trial information of the LOG-matrix, line 5).

To plot target location versus response location:

plot(SupSac(:,23),SupSac(:,8),'k.');

or

pa_plotloc(SupSac);