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Find server port number under "Pupil Remote" menu.
In run.py in Spyder:
Set port number for the pupil remote server (port).
Set address and port of TCP server (TCPAddr, TCPPort). Address should be Linux computers adress on network.
Set filename name for pickle file (use subject ID).
2. Set up Windows/MATLAB computer.
Check cable 7 is plugged in at back of MOTU and cable 16 isn't.
Turn on MOTU. Check that sampling rate indicator light on front settles on a value. If it doesn't, restart the Windows computer.
Turn on both amplifiers.
Run testSpeakersLights.m to check all speakers and lights are working as expected. Each speaker/light pair should come on one by one.
If multiple speakers/lights don't work, check amplifiers are both on.
If light/sound are sperated, check cable mapping.
If audible clicks, LED output is going to a speakers. Check cable mapping (specifically switching channels 7 and 16).
Set up touch screen.
Check it's plugged in.
Check it's virtually located to the bottom right of the main monitor.
Open MATLAB 2013b.
Set working directory to C:\Gareth\SpatialTaskV2\MATLABTask.
Open run.m in editor.
Set temporary subject ID
Set TCP address and port (params.TCPAddr, params.TCPPort) to match Python values.
On Python computer click run in run.py
On MALAB computer click run for run.m
Check touchscreen figure is aligned with monitor.
Check touchscreen figure calibration is correct (do the plotted dots align with the red dots?) If yes, enter 'y' and press enter.
If not:
Press crtl+c to stop the task.
dbquit if necessary.
Enable calibration in run.m's parameters.
Run run.m and re-calibrate.
Check the touchscreen's touch calibration is correct (does pressing on the screen click in the correct place?).
If not, double click eGalaxTouch icon in system tray and run monitor mapping.
Check touchscreen again, if calibration is still wrong, right click eGalaxTouch icon and run 4 point calibration.
Enter chamber and check stimuli are working.
End test by pressing ctrl+c.
Type dbquit if in debug mode (indicated by K>> in command window).
Set parameters for task in run.m.
Set subject ID.
Set nBlocks to ~8 (1 block = 100 trials = ~250 S).
Set nBreaks to ~4.
exchangeTime to 1.
PTSKip to 0.
3. Introduce subject
Give information sheet to subject to keep.
Get subject to read and sign consent form.
Explain eye tracker and basic task requirements.
Keep gaze fixated on target during stimulation.
Respond on touchscreen.
Explain paradigm.
Pre-training phase (<5 mins).
AV stimuli will come from same location, subject has to indicate loaction with one press on touchscreen.
They can look around after stimuli before responding to orientate themselves, but should look back to red fixation LED after responding. This will be tracked.
Pre-training will continue until a threshold of localisation accuray is reached.
When finished, a message will appear on touch screen saying ready to begin main task.
When ready, press screen again to continue.
Actual task (~1 hour).
Subject needs to keep eyes on fixation LED while stimuli are playing (~1s).
Subject needs to respond on touchscreen twice:
First to indicate auditory location.
Second to indicate visual location.
If the task stops, check touchscreen message to see if it's a break.
Touchscreen messages will guide subject with what to do.
Outside booth:
Place eyetracker on subject and position eye cameras.
Unplug eye tracker.
Move subject inside booth.
Plug eyetracker in inside booth and re-enable eye detection.
Check eye tracker camera pupil detection and adjust as required. Make sure detect pupil 0 and 1 are both enabled in pupil app.
Check world camera alignment.
Show subject expected fixation LED location.
Raise/lower chair so subject's head is vertically level with fixation LED.
Hand subject touchscreen. Make sure the cables don't drop out.
4. Calibrate and start eye tracker recording.
On the Linux computer select the eye tracker software. If it's already running, don't click the taskbar shortcut again.
In the world window:
Ensure the target surface markers are detected (green boxes around markers).
If not, adjust "min_marker_perimeter" in "Surface Tracker" menu.
Ensure surface is defined, detected, and named "Target".
If not defined, add and name as "Target" in Surface Tracker menu.
If not detected, check markers are being detected.
In the "Calibration" menu select "Natural Features Calibration".
Begin calibration by clicking (C) in the top left.
Ask subject to look at each world marker in turn and click to make these in the world.
Press C key to end calibration.
Check calibration accuracy.
Press (R) to begin recording video/gaze data.
In Spyder:
Click in run.py and click green run button.
Check Python connects to ZMQ server and waits for MATLAB to connect to TCP server.
5. Start task
On the Windows/MATLAB computer:
Run run.m.
Respond 'y' to calibration question.
On Linux computer
Check MATLAB has successfully connected to TCP server and Python has begun collecting data from eyetracker.
6. Monitor task
Tell subject to press touchscreen when ready to start (twice).
Monitor pre-training.
Check subject is looking at fixation light when trials start.
Subject should pass quickly, if not, re-explain task!
Monitor task.
Check subject is returning gaze to fixation LED/Target surface before each trial starts.
Hope Windows computer doesn't bluescreen randomly.
MATLAB task can be stopped with ctrl+c.
If task is stopped, or crashes for another reason, MATLAB enters debug mode.
If there is data that needs to be saved, save the workspace manually (data is only automatically saved during each break, but not after every trial).
When finished, untangle subject from cables and debrief.
7. Save data and shutdown
On Linux computer:
In world view click (R) in world window to stop recording.
In Python click stop to stop collection.
This raises an exception, which will be caught.
Python will then automatically convert the saved pickle file to a .mat file.
Copy the directory containing the eyetracker video from /Home/recordings/ to /Home/recordings/SpatialTaskV2 Recordings/.
Rename the backed up directory from the date to the subject ID.
Close eye tracker software.
Unplug eye tracker.
On Windows computer:
When the task completes, MATLAB saves its data automatically.
In ...\Data[SubjectID][Datetime]\TeComplete.mat.
Copy ...\Data[SubjectID]\ directory to external backup.
Close MATLAB editor (to prevent open files automatically re-opening next time someone starts MATLAB).
Close MATLAB.
Turn off amplifiers.
Turn off MOTU soundcard.
To do
Add live functionality
Via TCP server?
Minor modification to MATLAB code also required to monitor and act on online eye data.
