TRACKPixx Demo 7 – Running a simple saccade to target task with data visualization

Note

This demo requires TRACKPixx Revision 18 or later. You can check for recent firmware updates at vpixx.com/whatsnew

This demo is a simple eight-trial saccade to target experiment. During a trial, a fixation cross is presented in the center of the display, and an eye-tracking schedule is started. We use the IsSubjectFixating flags and GetEyePosition to check whether the participant is fixating on the cross. When a central fixation is detected, the cross is replaced with a target in one of four locations. Participants must saccade to the target as quickly as possible. We again use the fixation flags and eye position to determine whether the target was successfully fixated. On a successful fixation, the time is logged and a 500 ms visual mask appears before the next trial. During this time, gaze data from the trial is imported from the I/O controller to the main computer and saved. After the experiment ends we plot saccade duration, xy position, velocity, acceleration, and pupil size for each trial.

At the beginning of the demo there is an optional calibration step. This step calls TPxTrackpixx3CalibrationTesting, which implements a standard MATLAB TRACKPixx3 calibration script. The tracker must be calibrated for every new participant. We also recommend calibrating after a participant moves away from the chinrest.

function TPxSaccadeToTarget(initRequired)

%

% This demo flashes a sequence of 8 targets and tracks saccades to their

% position. 



% On a given trial, a fixation cross appears. When participants are

% fixating on the cross, a target appears in one of four locations (above,

% below, left, or right). Participants must saccade to the target as

% quickly as possible. When the saccade is complete, a 500ms mask is

% presented, and the next trial begins.



% Targets are circles with high or low luminance (high or low). Each luminance x

% position combination is repeated once, leading to 8 trials. After

% data is collected, data is plotted and output to a .csv file with headers

% for futher analysis 

%

% If initRequired is set to 1, the function first calls

% TPxTrackpixx3CalibrationTesting to connect to the TRACKPixx3 and

% calibrate the tracker. If you are calibrating your own setup, please

% check the calibration function to ensure your settings are correct.



% Made and tested with:

% -- TRACKPixx3 firmware revision 18 

% -- DATAPixx3 firmware revision 19 

% -- MATLAB version 9.6.0.1150989 (R2019a) 

% -- Psychtoolbox verison 3.0.15 

% -- Datapixx Toolbox version 3.7.5735

% -- Windows 10 version 1903, 64bit



% Sep 19, 2019  lef     Written

% Oct 17, 2019  lef     Revised

% Feb 24, 2020  lef     Revised, removes conversion NaN, now automated



%% Step 1 - Initialize (if needed)

if nargin==0

    initRequired=1;

end



% Get some user input

fileName= input('Enter participant name: ', 's');

fileID = [fileName '.mat'];



displayWidth = input('Enter width, in cm, of display monitor: ', 's');

displayWidth = str2double(displayWidth);



displayDistance = input('Enter distance, in cm, of participant to display monitor: ', 's');

displayDistance = str2double(displayDistance);



%If a calibration is needed, call the calibration script

if initRequired

    fprintf('\nInitialization required\n\nCalibrating the device...');

    TPxTrackpixx3CalibrationTesting;

end



%Connect to TRACKPixx3

Datapixx('Open');

Datapixx('SetTPxAwake');

Datapixx('SetupTPxSchedule');

Datapixx('RegWrRd');



%Set some flag settings. These values are the default settings but we

%specify them anyway.

fixationThreshold = 2500;               %pixels/s

framesForFixationFlag = 25;             %how many consecutive frames have to be below threshold for fixation flag to raise

saccadeThreshold = 10000;               %pixels/s

framesForSaccadeFlag = 10;              %how many consecutive frames have to be above threshold for saccade flag to raise



Datapixx('SetFixationThresholds' , fixationThreshold, framesForFixationFlag);

Datapixx('SetSaccadeThresholds' , saccadeThreshold, framesForSaccadeFlag);

Datapixx('RegWrRd');



%% Step 2 - Saccade to target task



%Set experiment parameters

maskPresentationTime = 0.5;

fixationPresentationTime = 0.5;

margin = 35;                                                % +/- margin of error, in pixels, within which the eyes can be considered in position



%open window

Screen('Preference', 'SkipSyncTests', 1 );

screenID = 2;                                              %change to switch display

[windowPtr, rect]=Screen('OpenWindow', screenID, [0,0,0]);

pixelSize = displayWidth/rect(3);

Screen('BlendFunction', windowPtr, 'GL_SRC_ALPHA', 'GL_ONE_MINUS_SRC_ALPHA');

Screen('Flip',windowPtr);



%describe targets and target locations

dotRadius = 20;

luminances = [1, 25,25,25;...                              %dark

              2, 250, 250, 250];                           %light

radius = 300;

center = rect(3:4)/2;

locations = [1, center(1), center(2)-radius;...            %top (in screen coordinates) 

             2, center(1)+radius, center(2);...            %right

             3, center(1), center(2)+radius;...            %bottom

             4, center(1)-radius, center(2)];              %left

         

%generate a stimuli list with target characteristics for each trial, and

%shuffle the order

numTargets = size(luminances(:,1),1);

numLocations = size(locations(:,1),1);

numReps = 1;

numTrials = numTargets*numLocations*numReps;

stimuli = [];



for s = 1:numTargets

    for k = 1:numLocations

        for m = 1:numReps

            stimuli = [stimuli; luminances(s,:), locations(k, :)]; 

        end

    end

end



stimuli=stimuli(randperm(size(stimuli,1)),:);           %shuffle



%create a structure to hold our trial data

trials = struct('Trial', [],...

                'Target', [],...

                'TargetLocation', [],...

                'TrialStart', [],...

                'TargetOnset', [],...

                'SaccadeOnset', [],...

                'SaccadeEnd', [],...

                'SaccadeReactionTime', [],...

                'SaccadeDuration', [],...

                'EyeData', []);





%show instructions to participant

Screen('DrawLine', windowPtr, [255,255,255], center(1) + 8, center(2), center(1)-8, center(2), 2);

Screen('DrawLine', windowPtr, [255,255,255], center(1), center(2)+8, center(1), center(2)-8, 2);

text_to_draw = ['SACCADE TO TARGET EXPERIMENT:\n\nStare at the cross in the middle of the screen.'...

                '\nAs soon as you see a dot appear, move your eyes to look at it as quickly as possible!\n\nPress any key to start.'];

DrawFormattedText(windowPtr, text_to_draw, 'center', 700, 255);

Screen('Flip', windowPtr);



%wait for participant to continue

[~, ~, ~] = KbPressWait;

Screen('Flip', windowPtr);

WaitSecs(1);



start_time = Datapixx('GetTime');



for k=1:numTrials

    

    trials(k).Trial = k;

    trials(k).Target = stimuli(k,1:4);

    trials(k).TargetLocation = stimuli(k,5:7);



    %draw fixation cross

    Screen('DrawLine', windowPtr, [255,255,255], center(1) + 8, center(2), center(1)-8, center(2), 2);

    Screen('DrawLine', windowPtr, [255,255,255], center(1), center(2)+8, center(1), center(2)-8, 2);

    Screen('Flip', windowPtr);

    trials(k).TrialStart = Datapixx('GetTime');

    WaitSecs(fixationPresentationTime); 

    

    %start logging eye data

    Datapixx('StartTPxSchedule');

    Datapixx('RegWrRd');

    

    %wait until subject is fixating on fixation cross

    while 1

        

        %get new eye data

        Datapixx('RegWrRd');

 

        %check for a fixation

        [lFlag, rFlag] = Datapixx('IsSubjectFixating');

        if lFlag && rFlag

            %if fixating, get eye position

            [xScreenRight, yScreenRight, xScreenLeft, yScreenLeft, ~, ~, ~, ~, ~] = Datapixx('GetEyePosition');

            

            %convert screen coordinates in VPixx coordinates (origin in middle of

            %screen) to Psychtoolbox Screen coordinates (origin in top left)

            fixationLocs = Datapixx('ConvertCoordSysToCustom', [xScreenRight, yScreenRight; xScreenLeft, yScreenLeft]);

            

            %confirm fixation is on cross in Psychtoolbox Screen coordinates 

            if inpolygon(fixationLocs(1,1), fixationLocs(1,2), [center(1)-margin, center(1)+margin] , [center(2)-margin, center(2)+margin])...

               && inpolygon(fixationLocs(2,1), fixationLocs(2,2), [center(1)-margin, center(1)+margin] , [center(2)-margin, center(2)+margin])                

                break;

            end

        end

    end

    

    %draw target

    colour = trials(k).Target(2:4);

    x = trials(k).TargetLocation(2);

    y = trials(k).TargetLocation(3);

    Screen('FillOval', windowPtr, colour, [x-dotRadius, y-dotRadius, x+dotRadius, y+dotRadius]);

    

    %set a marker to get the exact time the screen flips

    Datapixx('SetMarker');

    Datapixx('RegWrVideoSync');

    Screen('Flip', windowPtr);

    

    %collect marker data

    Datapixx('RegWrRd');

    trials(k).TargetOnset = Datapixx('GetMarker');

    

    %Now that the target has been shown, start a while loop to repeatedly

    %check to see if participant is fixating on the target

    while 1

        

        %get new eye data

        Datapixx('RegWrRd');



        %check for a fixation

        [lFlag, rFlag] = Datapixx('IsSubjectFixating');

        if lFlag && rFlag

            [xScreenRight, yScreenRight, xScreenLeft, yScreenLeft, ~, ~, ~, ~, ~] = Datapixx('GetEyePosition');

            

            %convert screen coordinates in VPixx coordinates (origin in middle of

            %screen) to Psychtoolbox Screen coordinates (origin in top left)

            fixationLocs = Datapixx('ConvertCoordSysToCustom', [xScreenRight, yScreenRight; xScreenLeft, yScreenLeft]);

            

            %confirm fixation is on target in Psychtoolbox Screen coordinates 

            if inpolygon(fixationLocs(1,1), fixationLocs(1,2), [x-margin, x+margin] , [y-margin, y+margin])...

               && inpolygon(fixationLocs(2,1), fixationLocs(2,2),[x-margin, x+margin] , [y-margin, y+margin])

                

                %Stop recording

                Datapixx('StopTPxSchedule');

                Datapixx('RegWrRd');

                break;

            end

        end

    end

    

    %create and show visual mask - mask is a full-screen display of 5 pixel wide squares

    %with a random grayscale value.

    squaresize = 5; 

    numsquares=[rect(4)/squaresize, rect(3)/squaresize];

    pattern = rand([numsquares, 1])*128;                    

    mask = imresize(pattern, squaresize, 'nearest');

    textureIndex=Screen('MakeTexture', windowPtr, mask);

    Screen('DrawTexture', windowPtr, textureIndex); 

    Screen('Flip', windowPtr);

    WaitSecs(maskPresentationTime);

    

    %read in eye data

    Datapixx('RegWrRd');

    status = Datapixx('GetTPxStatus');

    toRead = status.newBufferFrames;

    [bufferData, ~, ~] = Datapixx('ReadTPxData', toRead);

    

    %bufferData is formatted as follows:

    %1      --- Timetag (in seconds)

    %2      --- Left Eye X (in pixels)

    %3      --- Left Eye Y (in pixels)

    %4      --- Left Pupil Diameter (in pixels)

    %5      --- Right Eye X (in pixels)

    %6      --- Right Eye Y (in pixels)

    %7      --- Right Pupil Diameter (in pixels)

    %8      --- Digital Input Values (24 bits)

    %9      --- Left Blink Detection (0=no, 1=yes)

    %10     --- Right Blink Detection (0=no, 1=yes) 

    %11     --- Digital Output Values (24 bits)

    %12     --- Left Eye Fixation Flag (0=no, 1=yes) 

    %13     --- Right Eye Fixation Flag (0=no, 1=yes)  

    %14     --- Left Eye Saccade Flag (0=no, 1=yes) 

    %15     --- Right Eye Saccade Flag (0=no, 1=yes)  

    %16     --- Message code (integer) 

    %17     --- Left Eye Raw X (in pixels) 

    %18     --- Left Eye Raw Y (in pixels)  

    %19     --- Right Eye Raw X (in pixels)  

    %20     --- Right Eye Raw Y (in pixels)

    

    %IMPORTANT: "RIGHT" and "LEFT" refer to the right and left eyes shown

    %in the console overlay. In tabletop and MEG setups, this view is

    %inverted. This means "RIGHT" in our labelling convention corresponds

    %to the participant's left eye. Similarly "LEFT" in our convention

    %refers to left on the screen, which corresponds to the participant's

    %right eye.



    %If you are using an MRI setup with an inverting mirror, "RIGHT" will

    %correspond to the participant's right eye.

    

    %save eye data from trial as a table in the trial structure

    trials(k).EyeData = array2table(bufferData, 'VariableNames', {'TimeTag', 'LeftEyeX', 'LeftEyeY', 'LeftPupilDiameter', 'RightEyeX', 'RightEyeY', 'RightPupilDiameter',...

                                    'DigitalIn', 'LeftBlink', 'RightBlink', 'DigitalOut', 'LeftEyeFixationFlag', 'RightEyeFixationFlag', 'LeftEyeSaccadeFlag', 'RightEyeSaccadeFlag',...

                                    'MessageCode', 'LeftEyeRawX', 'LeftEyeRawY', 'RightEyeRawX', 'RightEyeRawY'});

    %interim save

    save(fileID, 'trials');

end



%Finish presentation

Screen('Closeall');

Datapixx('StopTPxSchedule');

Datapixx('RegWrRd');

finish_time = Datapixx('GetTime');





%% Step 3 - Read and process data

fprintf('\nRecording lasted %f seconds', finish_time-start_time);

fprintf('\nProcessing... this will take a while...');



%Data processing steps

% 1  - Adjust eye movement flags. The flags require calculating velocity

% over several frames and are therefore offset in a deterministic way, and

% need to be shifted to align with true event onset

% 2 - Get some saccade details - onset, reaction time, duration, end

% 3 - Convert x, y positions into degrees of visual angle

% 4 - Calculate Velocity (and filter) in degrees of visual angle

% 5 - Calculate Acceleration (and filter) in degrees of visual angle

% 6 - Create a "proportionOfTrial" variable for plotting purposes





% 1 - Loop throught and create adjusted eye movement flags that are

% correctly aligned with movement onset/end. This has three discrete steps:



% a) Both types of eye movement flags are based on the 4 previous frames,

% and the 4 subsequent frames. As a result, velocity for frame j is not

% calculated until frame j+5. All flags must be moved back 5 frames to

% account for this.



% b) The arguments framesForFixationFlag and framesForSaccadeFlag specify

% how many consecutive frames a velocity has to be above/below threshold

% for an eye movement flag to raise. This reduces noise but creates an

% offset of the flag onset, corresponding to the number of frames

% specified. We correct for this by adding flags to this number of frames

% prior to flag onset.



% c) For a saccade flag to drop, the previous 2 frames must be

% below/above the threshold. We can remove these last 2 flags to get true

% movement end.

for k = 1:numel(trials) 

    trials(k).EyeData = addvars(trials(k).EyeData, nan(height(trials(k).EyeData), 1),...

                                            nan(height(trials(k).EyeData), 1),...

                                            nan(height(trials(k).EyeData), 1),...

                                            nan(height(trials(k).EyeData), 1),...

                                            'NewVariableNames', {'LeftEyeFixationAdjusted', 'RightEyeFixationAdjusted', 'LeftEyeSaccadeAdjusted', 'RightEyeSaccadeAdjusted'});

    

    % a) correct for velocity calculation offset                                    

    for s = 1: height(trials(k).EyeData)

        if height(trials(k).EyeData)-s >=5

            if trials(k).EyeData.LeftEyeFixationFlag(s+5) ==1

                trials(k).EyeData.LeftEyeFixationAdjusted(s)=trials(k).EyeData.LeftEyeFixationFlag(s+5);

            end

            if trials(k).EyeData.RightEyeFixationFlag(s+5) ==1

                trials(k).EyeData.RightEyeFixationAdjusted(s)=trials(k).EyeData.RightEyeFixationFlag(s+5);

            end

            if trials(k).EyeData.LeftEyeSaccadeFlag(s+5) ==1

                trials(k).EyeData.LeftEyeSaccadeAdjusted(s)=trials(k).EyeData.LeftEyeSaccadeFlag(s+5);

            end

            if trials(k).EyeData.RightEyeSaccadeFlag(s+5)

                trials(k).EyeData.RightEyeSaccadeAdjusted(s)=trials(k).EyeData.RightEyeSaccadeFlag(s+5);

            end

        end

    end

    

    %b) correct for flag onset offset

    for s = 1: height(trials(k).EyeData)

        if height(trials(k).EyeData)-s >= framesForFixationFlag

            %check for an onset a specficied number of frames ahead

            onset = s+framesForFixationFlag;

            if isnan(trials(k).EyeData.LeftEyeFixationAdjusted(onset-1)) && ~isnan(trials(k).EyeData.LeftEyeFixationAdjusted(onset))

                trials(k).EyeData.LeftEyeFixationAdjusted(s:onset)=1;

            end

            

            if isnan(trials(k).EyeData.RightEyeFixationAdjusted(onset-1)) && ~isnan(trials(k).EyeData.RightEyeFixationAdjusted(onset))

                trials(k).EyeData.RightEyeFixationAdjusted(s:onset)=1;

            end

        end

        

        if height(trials(k).EyeData)-s >= framesForSaccadeFlag

            %check for an onset a specficied number of frames ahead

            onset = s+framesForSaccadeFlag;

            if isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(onset-1)) && ~isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(onset))

                trials(k).EyeData.LeftEyeSaccadeAdjusted(s:onset)=1;

            end

            

            if isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(onset-1)) && ~isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(onset))

                trials(k).EyeData.RightEyeSaccadeAdjusted(s:onset)=1;

            end

        end

    end 

    

    % c) correct for flag end offset

    for s = 4: height(trials(k).EyeData)

        %check for a flag drop and clear last 2 flags

        if isnan(trials(k).EyeData.LeftEyeFixationAdjusted(s)) && ~isnan(trials(k).EyeData.LeftEyeFixationAdjusted(s-1))

            trials(k).EyeData.LeftEyeFixationAdjusted(s-2:s)=NaN;

        end

        

        if isnan(trials(k).EyeData.RightEyeFixationAdjusted(s)) && ~isnan(trials(k).EyeData.RightEyeFixationAdjusted(s-1))

            trials(k).EyeData.RightEyeFixationAdjusted(s-2:s)=NaN;

        end

        

        if isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(s)) && ~isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(s-1))

            trials(k).EyeData.LeftEyeSaccadeAdjusted(s-2:s)=NaN;

        end



        if isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(s)) && ~isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(s-1))

            trials(k).EyeData.RightEyeSaccadeAdjusted(s-2:s)=NaN;

        end

    end

end

    



% 2 - Get some saccade details - onset, reaction time, duration, end

for k = 1:numel(trials)

    saccadeStarted = NaN;

    saccadeEnded = NaN;

    

    for s = 1:height(trials(k).EyeData) 

       %If saccade flag is up for both eyes, log this as saccade start

       if isnan(saccadeStarted) && isnan(saccadeEnded) && ~isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(s)) && ~isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(s))

           saccadeStarted = trials(k).EyeData.TimeTag(s);

       end



       %If saccade flag drops for both eyes, then saccade ended

       if ~isnan(saccadeStarted) && isnan(saccadeEnded) && isnan(trials(k).EyeData.LeftEyeSaccadeAdjusted(s)) && isnan(trials(k).EyeData.RightEyeSaccadeAdjusted(s))

           saccadeEnded = trials(k).EyeData.TimeTag(s);

       end

    end

    

    %get some saccade data 

    reactionTime = saccadeStarted - trials(k).TargetOnset;

    duration = saccadeEnded - saccadeStarted;

   

    trials(k).SaccadeOnset = saccadeStarted;

    trials(k).SaccadeEnd = saccadeEnded;

    trials(k).SaccadeReactionTime = reactionTime;

    trials(k).SaccadeDuration = duration;

end

       



% 3 - Convert x, y positions into degrees of visual angle

for k = 1:numel(trials)    

    trials(k).EyeData = addvars(trials(k).EyeData, nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        'NewVariableNames', {'LeftEyeXDegrees', 'LeftEyeYDegrees', 'RightEyeXDegrees', 'RightEyeYDegrees'});



    for s = 1:height(trials(k).EyeData)

        xL = trials(k).EyeData.LeftEyeX(s) * pixelSize;

        trials(k).EyeData.LeftEyeXDegrees(s) = 2*atand(xL/(2*displayDistance));

        

        yL = trials(k).EyeData.LeftEyeY(s) * pixelSize;

        trials(k).EyeData.LeftEyeYDegrees(s) = 2*atand(yL/(2*displayDistance));



        xR = trials(k).EyeData.RightEyeX(s) * pixelSize;

        trials(k).EyeData.RightEyeXDegrees(s) = 2*atand(xR/(2*displayDistance));

        

        yR = trials(k).EyeData.RightEyeY(s) * pixelSize;

        trials(k).EyeData.RightEyeYDegrees(s) = 2*atand(yR/(2*displayDistance));

    end

end







% 4 - Calculate velocity

for k = 1:numel(trials)

    trials(k).EyeData = addvars(trials(k).EyeData, nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        'NewVariableNames', {'LeftEyeVelocityRaw', 'RightEyeVelocityRaw', 'LeftEyeVelocity', 'RightEyeVelocity'});



    for s = 5:height(trials(k).EyeData)



        %Formula for velocity (as the tracker calulates it)

        %where i is the current frame 

        %deltaX = (sum(x(i+1):x(i+4)) - sum(x(i-4):x(i-1))) / 0.01;

        %deltaY = (sum(y(i+1):y(i+4)) - sum(y(i-4):y(i-1))) / 0.01;

        %velocity = sqrt(deltaX^2 + deltaY^2) 

        

        if height(trials(k).EyeData)-s >= 4

            

            leftX1 = sum(trials(k).EyeData.LeftEyeXDegrees(s-4:s-1));

            leftX2 = sum(trials(k).EyeData.LeftEyeXDegrees(s+1:s+4));

            

            leftY1 = sum(trials(k).EyeData.LeftEyeYDegrees(s-4:s-1));

            leftY2 = sum(trials(k).EyeData.LeftEyeYDegrees(s+1:s+4));

            

            trials(k).EyeData.LeftEyeVelocityRaw(s)= sqrt(((leftX2 - leftX1)/0.01)^2 + ((leftY2 - leftY1)/0.01)^2); 

            

            rightX1 = sum(trials(k).EyeData.RightEyeXDegrees(s-4:s-1));

            rightX2 = sum(trials(k).EyeData.RightEyeXDegrees(s+1:s+4));

            

            rightY1 = sum(trials(k).EyeData.RightEyeYDegrees(s-4:s-1));

            rightY2 = sum(trials(k).EyeData.RightEyeYDegrees(s+1:s+4));

            

            trials(k).EyeData.RightEyeVelocityRaw(s) = sqrt(((rightX2 - rightX1)/0.01)^2 + ((rightY2 - rightY1)/0.01)^2); 

        end



    end



    %Do some filtering on our data using a moving window average. Reverse

    %and forward filter to remove any phase-shift.

    windowSize = 25; 

    b = (1/windowSize)*ones(1,windowSize);

    a = 1;



    leftEye = trials(k).EyeData.LeftEyeVelocityRaw(:);

    rightEye = trials(k).EyeData.RightEyeVelocityRaw(:);



    %reverse filter

    leftEye = filter(b, a, flip(leftEye));

    rightEye = filter(b, a, flip(rightEye));



    %forward filter

    leftEye = filter(b, a, flip(leftEye));

    rightEye = filter(b, a, flip(rightEye));



    %assign to table

    trials(k).EyeData.LeftEyeVelocity = leftEye;

    trials(k).EyeData.RightEyeVelocity = rightEye;



end





%5 - Derive acceleration from velocity data. Acceleration is the change in

%velocity across a frame, which has a fixed duration of 1/2000th of a

%second

for k = 1:numel(trials)

    trials(k).EyeData = addvars(trials(k).EyeData, nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        nan(height(trials(k).EyeData), 1),...

                                        'NewVariableNames', {'LeftEyeAccelerationRaw', 'RightEyeAccelerationRaw', 'LeftEyeAcceleration', 'RightEyeAcceleration'});



    for s = 2:height(trials(k).EyeData)

        trials(k).EyeData.LeftEyeAccelerationRaw(s) = (trials(k).EyeData.LeftEyeVelocityRaw(s) - trials(k).EyeData.LeftEyeVelocityRaw(s-1))/(1/2000);

        trials(k).EyeData.RightEyeAccelerationRaw(s) = (trials(k).EyeData.RightEyeVelocityRaw(s) - trials(k).EyeData.RightEyeVelocityRaw(s-1))/(1/2000);

    end



    %Do some filtering on our data using a moving window average. Reverse

    %and forward filter to remove any phase-shift.

    windowSize = 25; 

    b = (1/windowSize)*ones(1,windowSize);

    a = 1;



    leftEye = trials(k).EyeData.LeftEyeAccelerationRaw(:);

    rightEye = trials(k).EyeData.RightEyeAccelerationRaw(:);



    %reverse filter

    leftEye = filter(b, a, flip(leftEye));

    rightEye = filter(b, a, flip(rightEye));



    %forward filter

    leftEye = filter(b, a, flip(leftEye));

    rightEye = filter(b, a, flip(rightEye));



    %assign to table

    trials(k).EyeData.LeftEyeAcceleration = leftEye;

    trials(k).EyeData.RightEyeAcceleration = rightEye;



end



% 6 Finally, for plotting purposes, create a column with proportion of trial time

for k = 1:numel(trials)

    trials(k).EyeData = addvars(trials(k).EyeData, nan(height(trials(k).EyeData), 1),...

                                        'NewVariableNames', 'ProportionTrial', 'After', 'TimeTag');



    trialStart = trials(k).EyeData.TimeTag(1);

    trialDuration = trials(k).EyeData.TimeTag(end)- trialStart;

    for s = 1:height(trials(k).EyeData)

        trials(k).EyeData.ProportionTrial(s) = (trials(k).EyeData.TimeTag(s)- trialStart)/trialDuration;

    end

end



save(fileID, 'trials');





%% Step 4 - Plot results



%Figure 1 - Saccade Reaction Time

%Figure 2 - Saccade Duration

%Figure 3 - X,Y screen position over time for target 1

%Figure 4 - X,Y screen position over time for target 2

%Figure 5 - Filtered velocity (degrees/second) for target 1

%Figure 6 - Filtered velocity (degrees/second) for target 2

%Figure 7 - Filtered acceleration (degrees/second^2) for target 1

%Figure 8 - Filtered acceleration (degrees/second^2) for target 2

%Figure 9 - Pupil dilation for target 1

%Figure 10 - Pupil dilation for target 2



lineColours = rand(numLocations, 3);



%Figure 1 - plot saccade reaction time

figure();

for k = 1:numTargets

    for s = 1:numLocations

        temp = [];

        for h= 1:numel(trials)

            if trials(h).Target(1) == k &&  trials(h).TargetLocation(1) == s

                temp = [temp; trials(h).SaccadeReactionTime];

            end

        end

        

    average = mean(temp);

    sterr = std(temp)/sqrt(numel(temp));

    subplot(1,2,k)

    hold on

    errorbar(s, average, sterr, 'Color', lineColours(s, :), 'MarkerFaceColor', lineColours(s, :), 'Marker', 'o');

    end

    

    xticks(1:numLocations);

    xticklabels({'Up', 'Right', 'Down', 'Left'});

    titleText=['Saccade Reaction times for target ' int2str(k)];

    title(titleText);

    ylabel('Reaction time (s)');

    xlabel('Saccade direction');

    xlim([0,numLocations+1]);

    ylim([0,1]);

end





%Figure 2 - plot saccade duration

figure();

for k = 1:numTargets

    for s = 1:numLocations

        temp = [];

        for h = 1:numel(trials)

            if trials(h).Target(1) == k &&  trials(h).TargetLocation(1) == s

                temp = [temp; trials(h).SaccadeDuration];

            end

        end

        

    average = mean(temp);

    sterr = std(temp)/sqrt(numel(temp));

    subplot(1,2,k)

    hold on

    errorbar(s, average, sterr, 'Color', lineColours(s, :), 'MarkerFaceColor', lineColours(s, :), 'Marker', 'o');

    end

    

    xticks(1:numLocations);

    xticklabels({'Up', 'Right', 'Down', 'Left'});

    titleText=['Saccade duration for target ' int2str(k)];

    title(titleText);

    ylabel('Duration (s)');

    xlabel('Saccade direction');

    xlim([0,numLocations+1]);

    ylim([0,0.05]);

end





%Figure 3 & 4 - Plot x and y position on each trial, by location, for each

%target type. If you have a lot of reps this graph will get very messy. Consider

%creating multiple figures to handle large datasets.

numRows = 2;

numCols = 2;



for m = 1:numTargets

    figure();

    for k = 1:numel(trials)

        if trials(k).Target(1) == m

            subplot(numRows, numCols,  trials(k).TargetLocation(1));

            plot3(trials(k).EyeData.ProportionTrial, trials(k).EyeData.LeftEyeXDegrees, trials(k).EyeData.LeftEyeYDegrees, 'b');

            hold on

            plot3(trials(k).EyeData.ProportionTrial, trials(k).EyeData.RightEyeXDegrees, trials(k).EyeData.RightEyeYDegrees, 'r');

            

            %plot target position at onset

            trialDuration = trials(k).EyeData.TimeTag(end)- trials(k).EyeData.TimeTag(1);

            targetx = (trials(k).TargetOnset- trials(k).EyeData.TimeTag(1))/trialDuration;

            targety = (trials(k).TargetLocation(2)-rect(3)/2) * pixelSize;

            targety =  2*atand(targety/(2*displayDistance));

            targetz = -(trials(k).TargetLocation(3)-rect(4)/2) * pixelSize;

            targetz =  2*atand(targetz/(2*displayDistance));

            plot3(targetx, targety, targetz, 'ok'); 

            

            zlabel('Y (degrees)');

            ylabel('X (degrees)');

            xlabel('Proportion of Trial');

            zlim([-15, 15]);

            ylim([-15, 15]);



            titleText=['Position of target ' int2str(trials(k).Target(1)) ' location ' int2str(trials(k).TargetLocation(1))];

            title(titleText);

            legend({'Left eye', 'Right eye', 'Target onset'});

        end

    end

end





%Figure 6 & 7- Velocity on each trial, by location, for each target type.

%If you have a lot of reps this graph will get very messy. Consider

%creating multiple figures to handle large datasets.

numCols = numLocations;

numRows = numReps;



for m = 1:numTargets

    figure();

    repCount= zeros(1,numLocations);

    for k = 1:numel(trials)

        if trials(k).Target(1) == m

            

            %get which iteration this is

            location = trials(k).TargetLocation(1);

            repCount(location)= repCount(location)+1;

            iteration = repCount(location);

            plotPosition = location+(numLocations*(iteration-1));

            

            subplot(numRows, numCols, plotPosition);

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.LeftEyeVelocity, 'b');

            hold on     

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.RightEyeVelocity, 'r');



            %Put some markers to delineate saccade when the participant was

            %saccading or fixating. Lift them up over data.

            statusL = 470; 

            statusR = 490;



            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeFixationAdjusted*statusL), ':b');

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeFixationAdjusted*statusR), ':r');

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeSaccadeAdjusted*statusL), 'b', 'LineWidth', 5);

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeSaccadeAdjusted*statusR), 'r',  'LineWidth', 5);

            

            %plot target onset as a vertical line

            trialDuration = trials(k).EyeData.TimeTag(end)- trials(k).EyeData.TimeTag(1);

            targetx = (trials(k).TargetOnset- trials(k).EyeData.TimeTag(1))/trialDuration;

            line([targetx, targetx], [0, 500]); 



            %add peak velocity values to plot

            [mL,iL]=max(trials(k).EyeData.LeftEyeVelocity);

            xL = trials(k).EyeData.ProportionTrial(iL);

            plot(xL, mL, 'ob');

            txtL = ['Peak left eye: ' num2str(mL) ' degrees/s'];

            text(0.1, 100, {txtL}, 'FontSize', 8, 'Color', 'b');

            

            [mR,iR]=max(trials(k).EyeData.RightEyeVelocity);

            xR = trials(k).EyeData.ProportionTrial(iR);

            plot(xR, mR, 'or');

            txtR = ['Peak right eye: ' num2str(mR) ' degrees/s'];

            text(0.1, 80, {txtR}, 'FontSize', 8, 'Color', 'r');

            

            ylabel('Velocity (degrees/s)');

            xlabel('Proportion Trial');

            xlim([0,1]);

            ylim([0, 500]);

            if iteration == 1

                legend({'Left eye velocity', 'Right eye velocity', 'Left eye fixation', 'Right eye fixation', 'Left eye saccade', 'Right eye saccade', 'Target onset'}, 'Location', 'southoutside' );

            end



            titleText=['Trial velocity for target ' int2str(trials(k).Target(1)) ' location ' int2str(trials(k).TargetLocation(1))];

            title(titleText);

            

            txt = {'**Data forward and reverse filtered with';'a 10-frame moving window average**'};

            text(.1, 50,txt, 'FontSize', 8, 'Color', [.5, .5, .5])

        end

    end

end





%Figure 7 & 8- Acceleration on each trial, by location, for each target

numCols = numLocations;

numRows = numReps;



for m = 1:numTargets

    figure();

    repCount= zeros(1,numLocations);

    for k = 1:numel(trials)

        if trials(k).Target(1) == m

            

            %get which iteration this is

            location = trials(k).TargetLocation(1);

            repCount(location)= repCount(location)+1;

            iteration = repCount(location);

            plotPosition = location+(numLocations*(iteration-1));

            

            subplot(numRows, numCols, plotPosition);

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.LeftEyeAcceleration, 'b');   

            hold on     

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.RightEyeAcceleration, 'r');

         

            %Put some markers to delineate saccade when the participant was

            %saccading or fixating. Lift them up over data.

            statusL = 32000; 

            statusR = 30000;



            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeFixationAdjusted*statusL), ':b');

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeFixationAdjusted*statusR), ':r');



            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeSaccadeAdjusted*statusL), 'b', 'LineWidth', 5);

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeSaccadeAdjusted*statusR), 'r',  'LineWidth', 5);

            

            %plot target onset as a vertical line

            trialDuration = trials(k).EyeData.TimeTag(end)- trials(k).EyeData.TimeTag(1);

            targetx = (trials(k).TargetOnset- trials(k).EyeData.TimeTag(1))/trialDuration;

            line([targetx, targetx], [-35000,35000]); 



            ylabel('Acceleration (degrees/s^2)');

            xlabel('Proportion Trial');

            xlim([0,1]);

            ylim([-35000,35000]);

            if iteration ==1

                legend({'Left eye acceleration', 'Right eye acceleration', 'Left eye fixation', 'Right eye fixation', 'Left eye saccade', 'Right eye saccade', 'Target onset'}, 'Location', 'southoutside' );

            end

            titleText=['Trial Acceleration for target ' int2str(trials(k).Target(1)) ' location ' int2str(trials(k).TargetLocation(1))];

            title(titleText);

            

            txt = {'**Data forward and reverse filtered with';'a 10-frame moving window average**'};

            text(.1,-20000,txt, 'FontSize', 8, 'Color', [.5, .5, .5])

        end

    end

end







%Figure 9 & 10 - Dilation on each trial, by location, for each target type

numCols = numLocations;

numRows = numReps;



for m = 1:numTargets

    figure();

    repCount= zeros(1,numLocations);

    for k = 1:numel(trials)

        if trials(k).Target(1) == m

            

            %get which iteration this is

            location = trials(k).TargetLocation(1);

            repCount(location)= repCount(location)+1;

            iteration = repCount(location);

            plotPosition = location+(numLocations*(iteration-1));

            

            subplot(numRows, numCols, plotPosition);

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.LeftPupilDiameter, 'b');

            hold on     

            plot(trials(k).EyeData.ProportionTrial, trials(k).EyeData.RightPupilDiameter, 'r');

            

            %Put some markers to delineate saccade when the participant was

            %saccading or fixating. Lift them up over data.

            statusL = 70; 

            statusR = 75;



            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeFixationAdjusted*statusL), ':b');

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeFixationAdjusted*statusR), ':r');



            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.LeftEyeSaccadeAdjusted*statusL), 'b', 'LineWidth', 5);

            plot(trials(k).EyeData.ProportionTrial, (trials(k).EyeData.RightEyeSaccadeAdjusted*statusR), 'r',  'LineWidth', 5);



            ylabel('Dilation (pixels)');

            xlabel('Proportion Trial');

            xlim([0,1]);

            ylim([0,80]);

            if iteration ==1

                legend({'Left pupil diameter', 'Right pupil diameter', 'Left eye fixation', 'Right eye fixation', 'Left eye saccade', 'Right eye saccade'}, 'Location', 'southoutside' );

            end

            titleText=['Pupil dilation for target ' int2str(trials(k).Target(1)) ' location ' int2str(trials(k).TargetLocation(1))];

            title(titleText);

        end

    end

end









%% Step 5 - Write data to csv



rawResults = table();

for k = 1:numel(trials)

    newTrial = trials(k).EyeData;

    newTrial.TrialNumber = repmat(trials(k).Trial, [height(newTrial), 1]);

    newTrial.Target = repmat(trials(k).Target(1), [height(newTrial), 1]);

    newTrial.TargetLocation = repmat(trials(k).TargetLocation(1), [height(newTrial), 1]);

    newTrial.TrialStart = repmat(trials(k).TrialStart, [height(newTrial), 1]);

    newTrial.TargetOnset = repmat(trials(k).TargetOnset, [height(newTrial), 1]);

    newTrial.SaccadeOnset = repmat(trials(k).SaccadeOnset, [height(newTrial), 1]);

    newTrial.SaccadeEnd = repmat(trials(k).SaccadeEnd, [height(newTrial), 1]);

    newTrial.SaccadeReactionTime = repmat(trials(k).SaccadeReactionTime, [height(newTrial), 1]);

    newTrial.SaccadeDuration = repmat(trials(k).SaccadeDuration, [height(newTrial), 1]);

    newTrial = newTrial(:, [40:end, 1:37]);

    rawResults = [rawResults; newTrial];

end



csvFileID = [fileName '_Results.csv'];

writetable(rawResults, csvFileID);



%% Step 6 - Finish up



Datapixx('SetTPxSleep');

Datapixx('RegWrRd');

Datapixx('Close');



end