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d190729_wkv_change_touch_adaptation.m
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d190729_wkv_change_touch_adaptation.m
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% purpose: to look at changes in wkv during subsequent touches, vs object
% angle
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK037'},{'JK038'},{'JK039'},{'JK041'},{'JK052'},{'JK053'},{'JK054'},{'JK056'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
% baseDir = 'Y:\Whiskernas\JK\suite2p\';
baseDir = 'Y:\Whiskernas\JK\suite2p\';
nFeatures = 11; % 11 features (wkv excluding touch count)
featureNames = {'\Delta\theta', '\Delta\phi', '\Delta\kappa_H', '\Delta\kappa_V', 'Slide distance', 'touch duration', ...
'\theta', '\phi', '\kappa_H', '\kappa_V', 'Arc length'};
nMice = length(mns);
wkvChanges = cell(nMice,1);
maxTouchNum = zeros(nMice,1);
for mi = 1 : nMice
% wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]);
load([baseDir, mns{mi}(3:5), filesep, 'Uber', mns{mi}, sns{mi}, '_NC'])
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTouchChunksByWhisking), u.trials));
touchTrialInd = find(cellfun(@(x) length(x.protractionTouchChunksByWhisking), u.trials));
featureMat = cell(nFeatures, 1);
featureMat{1} = cellfun(@(x) x.protractionTouchDThetaByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.protractionTouchDPhiByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{3} = cellfun(@(x) x.protractionTouchDKappaHByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) x.protractionTouchDKappaVByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{5} = cellfun(@(x) x.protractionTouchSlideDistanceByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{6} = cellfun(@(x) x.protractionTouchDurationByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{8} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{9} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{10} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{11} = cellfun(@(x) x.arcLength(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
angles = unique(cellfun(@(x) x.angle, u.trials(touchTrialInd)));
% angles = unique(cellfun(@(x) x.poleAngle, wfa.trials(touchTrialInd)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.angle == angles(ai), u.trials(touchTrialInd)));
% angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialInd)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
wkvChanges{mi}{ai,fi} = cell2mat(featureCell);
end
end
end
%
colors = jet(length(angles));
maxTn = max(maxTouchNum);
figure('units','normalized','outerposition',[0.1 0.1 0.66 0.67])
for fi = 1 : nFeatures
subplot(3,4,fi), hold on
% for ai = 1 : length(angles)
% tempMat = nan(length(mns), maxTn);
% for mi = 1 : nMice
% tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
% end
% % errorbar(mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), '-', 'color', colors(ai,:))
% shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
% % plot(mean(tempMat), '-', 'color', colors(ai,:))
% end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
plot(mean(tempMat), '-', 'color', colors(ai,:))
end
title(featureNames{fi})
if fi==8
xlabel('Touch order')
end
% set(gca,'fontsize',12)
end
% subplot(3,4,nFeatures+1)
legend(cellfun(@(x) [num2str(x), '\circ'], mat2cell(angles, ones(length(angles),1)), 'uniformoutput', false), 'location', 'northeastoutside')
%% Results:
%% (1) theta and phi at touch changes during subsequent touches -> They might discriminate the angle by gathering information from multiple touches
%% -> Test this by looking at # of touches before answer lick, first lick, putting dphi dtheta(across touches)/dphi(across touches) as an input in glm.
%% (2) at 135 degrees, theta stays the same when phi goes up... how could this be happening? (It happens only in expert mice)
%% -> Figure out this first. Somethings fishy.
%% Relative change in every touch.
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK037'},{'JK038'},{'JK039'},{'JK041'},{'JK052'},{'JK053'},{'JK054'},{'JK056'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
% sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
% baseDir = 'Y:\Whiskernas\JK\suite2p\';
baseDir = 'Y:\Whiskernas\JK\suite2p\';
nFeatures = 11; % 11 features (wkv excluding touch count)
featureNames = {'\Delta\theta', '\Delta\phi', '\Delta\kappa_H', '\Delta\kappa_V', 'Slide distance', 'touch duration', ...
'\theta', '\phi', '\kappa_H', '\kappa_V', 'Arc length'};
nMice = length(mns);
wkvChanges = cell(nMice,1);
maxTouchNum = zeros(nMice,1);
for mi = 1 : nMice
% wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]);
load([baseDir, mns{mi}(3:5), filesep, 'Uber', mns{mi}, sns{mi}, '_NC'])
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTouchChunksByWhisking), u.trials));
touchTrialInd = find(cellfun(@(x) length(x.protractionTouchChunksByWhisking), u.trials));
featureMat = cell(nFeatures, 1);
featureMat{1} = cellfun(@(x) x.protractionTouchDThetaByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.protractionTouchDPhiByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{3} = cellfun(@(x) x.protractionTouchDKappaHByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) x.protractionTouchDKappaVByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{5} = cellfun(@(x) x.protractionTouchSlideDistanceByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{6} = cellfun(@(x) x.protractionTouchDurationByWhisking, u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{8} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{9} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{10} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
featureMat{11} = cellfun(@(x) x.arcLength(cellfun(@(y) y(1)-1, x.protractionTouchChunksByWhisking))', u.trials(touchTrialInd), 'uniformoutput', false);
angles = unique(cellfun(@(x) x.angle, u.trials(touchTrialInd)));
% angles = unique(cellfun(@(x) x.poleAngle, wfa.trials(touchTrialInd)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.angle == angles(ai), u.trials(touchTrialInd)));
% angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialInd)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvMat = tempMat - tempMat(:,1);
wkvChanges{mi}{ai,fi} = wkvMat;
end
end
end
%
colors = jet(length(angles));
maxTn = max(maxTouchNum);
figure('units','normalized','outerposition',[0.1 0.1 0.66 0.67])
for fi = 1 : nFeatures
subplot(3,4,fi), hold on
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
% errorbar(mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), '-', 'color', colors(ai,:))
shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
% plot(mean(tempMat), '-', 'color', colors(ai,:))
end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
plot(mean(tempMat), '-', 'color', colors(ai,:))
end
title(featureNames{fi})
if fi==8
xlabel('Touch order')
end
% set(gca,'fontsize',12)
end
% subplot(3,4,nFeatures+1)
legend(cellfun(@(x) [num2str(x), '\circ'], mat2cell(angles, ones(length(angles),1)), 'uniformoutput', false), 'location', 'northeastoutside')
%% Look at other cases - expert and radial distance
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK037'},{'JK038'},{'JK039'},{'JK041'},{'JK052'},{'JK053'},{'JK054'},{'JK056'}];
sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
% sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
% baseDir = 'Y:\Whiskernas\JK\suite2p\';
nFeatures = 11; % 11 features (wkv excluding touch count)
featureNames = {'\Delta\theta', '\Delta\phi', '\Delta\kappa_H', '\Delta\kappa_V', 'Slide distance', 'touch duration', ...
'\theta', '\phi', '\kappa_H', '\kappa_V', 'Arc length'};
nMice = length(mns);
wkvChanges = cell(nMice,1);
maxTouchNum = zeros(nMice,1);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]);
wfa.trials = wfa.trials';
% load([baseDir, mns{mi}(3:5), filesep, 'Uber', mns{mi}, sns{mi}, '_NC'])
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialInd = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
featureMat = cell(nFeatures, 1);
featureMat{1} = cellfun(@(x) cellfun(@(y) x.theta(y(find(nanmax(abs(x.theta(y)-x.theta(y(1))))==abs(x.theta(y)-x.theta(y(1))),1)))-x.theta(y(1)), ...
x.protractionTFchunksByWhisking(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunksByWhisking)))))), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) cellfun(@(y) x.phi(y(find(nanmax(abs(x.phi(y)-x.phi(y(1))))==abs(x.phi(y)-x.phi(y(1))),1)))-x.phi(y(1)), ...
x.protractionTFchunksByWhisking(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunksByWhisking)))))), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{3} = cellfun(@(x) cellfun(@(y) x.kappaH(y(find(nanmax(abs(x.kappaH(y)-x.kappaH(y(1))))==abs(x.kappaH(y)-x.kappaH(y(1))),1)))-x.kappaH(y(1)), ...
x.protractionTFchunksByWhisking(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunksByWhisking)))))), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) cellfun(@(y) x.kappaV(y(find(nanmax(abs(x.kappaV(y)-x.kappaV(y(1))))==abs(x.kappaV(y)-x.kappaV(y(1))),1)))-x.kappaV(y(1)), ...
x.protractionTFchunksByWhisking(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunksByWhisking)))))), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{5} = cellfun(@(x) cellfun(@(y) nanmax(y), x.protractionSlideByWhisking), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{6} = cellfun(@(x) x.protractionTouchDurationByWhisking, wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{8} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{9} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{10} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{11} = cellfun(@(x) x.arcLength(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialInd), 'uniformoutput', false);
% angles = unique(cellfun(@(x) x.angle, wfa.trials(touchTrialInd)));
angles = unique(cellfun(@(x) x.poleAngle, wfa.trials(touchTrialInd)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
% angleInd = find(cellfun(@(x) x.angle == angles(ai), u.trials(touchTrialInd)));
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialInd)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChanges{mi}{ai,fi} = tempMat;
% wkvMat = tempMat - tempMat(:,1);
% wkvChanges{mi}{ai,fi} = wkvMat;
end
end
end
%
colorsList = jet(7);
colors = colorsList([1,7],:);
% colors = colorsList([1:7],:);
maxTn = max(maxTouchNum);
figure('units','normalized','outerposition',[0.1 0.1 0.66 0.67])
for fi = 1 : nFeatures
subplot(3,4,fi), hold on
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
% errorbar(mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), '-', 'color', colors(ai,:))
shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
% plot(mean(tempMat), '-', 'color', colors(ai,:))
end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
plot(mean(tempMat), '-', 'color', colors(ai,:))
end
title(featureNames{fi})
if fi==8
xlabel('Touch order')
end
% set(gca,'fontsize',12)
end
% subplot(3,4,nFeatures+1)
legend(cellfun(@(x) [num2str(x), '\circ'], mat2cell(angles, ones(length(angles),1)), 'uniformoutput', false), 'location', 'northeastoutside')
%%
%% Result: the trend in theta/phi looks the same in other cases
%%
%% How does the touch height on the pole change?
% calculated from the matching wst time point, whiskerPoleIntersection{:,2}(2)
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
% sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
nMice = length(mns);
maxTouchNum = zeros(nMice,1);
touchHeight = cell(nMice,1);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
wsa = Whisker.WhiskerSignalTrialArray_2pad([baseDir, mns{mi}, sns{mi}]); % to get the touch height information
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndWS = find(ismember(wsa.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, wsa.trialNums(touchTrialIndWS))); % assume sorted
% touchOnsetInds = cellfun(@(x) cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialInd));
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsWS = cellfun(@(x,y) cellfun(@(z) find(abs(x.time{2}-z) == nanmin(abs(x.time{2} - z)),1), y, 'uniformoutput', false), wsa.trials(touchTrialIndWS), touchOnsetTimes', 'uniformoutput', false);
touchHeightValid = cellfun(@(x,y) cellfun(@(z) length(x.whiskerPoleIntersection{z,2}), y), wsa.trials(touchTrialIndWS), touchOnsetIndsWS, 'uniformoutput', false);
validInd = find(cellfun(@(x) isempty(find(x==0)), touchHeightValid));
touchHeightCell = cellfun(@(x,y) cellfun(@(z) double(x.whiskerPoleIntersection{z,2}(2))/x.pxPerMm, y), wsa.trials(touchTrialIndWS(validInd)), touchOnsetIndsWS(validInd), 'uniformoutput', false);
%%
angles = unique(cellfun(@(x) x.angle, wsa.trials(touchTrialIndWS)));
touchHeight{mi} = cell(length(angles), 1);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.angle == angles(ai), wsa.trials(touchTrialIndWS(validInd))));
touchHeight{mi}{ai} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], touchHeightCell(angleInd)', 'uniformoutput', false);
tempMat = cell2mat(featureCell);
touchHeight{mi}{ai} = tempMat;
end
end
%
colorsList = jet(7);
if length(angles) == 2
colors = colorsList([1,7],:);
elseif length(angles) == 7
colors = colorsList([1:7],:);
else
error('Error in the length of ''angles''')
end
maxTn = max(maxTouchNum);
figure
hold on
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(touchHeight{mi}{ai} - touchHeight{mi}{ai}(:,1));
end
shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(touchHeight{mi}{ai} - touchHeight{mi}{ai}(:,1));
end
plot(1:size(tempMat,2), mean(tempMat), 'color',colors(ai,:))
end
xlabel('Touch order')
ylabel('Relative height (mm)')
title('Change in touch height on the pole')
%%
%% Results: Height works as expected from theta change. (goes up in 45 degrees, stays the same in 135 degrees)
%%
%% How does the follicle height change?
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
% sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
nMice = length(mns);
maxTouchNum = zeros(nMice,1);
baseHeight = cell(nMice,1);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
w3a = Whisker.Whisker3D_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch height information
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndW3 = find(ismember(w3a.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, w3a.trialNums(touchTrialIndW3))); % assume sorted
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsW3 = cellfun(@(x,y) cellfun(@(z) find(abs(x.time-z) == nanmin(abs(x.time - z)),1), y, 'uniformoutput', false), w3a.trials(touchTrialIndW3), touchOnsetTimes', 'uniformoutput', false);
baseHeightCell = cellfun(@(x,y) cellfun(@(z) x.base(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3), touchOnsetIndsW3, 'uniformoutput', false);
%%
angles = unique(cellfun(@(x) x.servoAngle, w3a.trials(touchTrialIndW3)));
baseHeight{mi} = cell(length(angles), 1);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.servoAngle == angles(ai), w3a.trials(touchTrialIndW3)));
baseHeight{mi}{ai} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], baseHeightCell(angleInd)', 'uniformoutput', false);
tempMat = cell2mat(featureCell);
baseHeight{mi}{ai} = tempMat;
end
end
%
colorsList = jet(7);
if length(angles) == 2
colors = colorsList([1,7],:);
elseif length(angles) == 7
colors = colorsList([1:7],:);
else
error('Error in the length of ''angles''')
end
maxTn = max(maxTouchNum);
figure
hold on
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(baseHeight{mi}{ai} - baseHeight{mi}{ai}(:,1));
end
shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(baseHeight{mi}{ai} - baseHeight{mi}{ai}(:,1));
end
plot(1:size(tempMat,2), mean(tempMat), 'color',colors(ai,:))
end
xlabel('Touch order')
ylabel('Relative height (mm)')
title('Change in whisker base height')
%%
%% Results: Whisker base height remains the same at 135°, while it goes up at 45°.
%% It suggests their differential control of whisker pad in different pole angle. (to maintain the same height of the base while elevating the base angle requires the whole whisker pad to go down)
%%
%% How does it look like in each touch, not divided by whisking?
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK037'},{'JK038'},{'JK039'},{'JK041'},{'JK052'},{'JK053'},{'JK054'},{'JK056'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
% baseDir = 'Y:\Whiskernas\JK\suite2p\';
nFeatures = 11; % 11 features (wkv excluding touch count)
featureNames = {'\Delta\theta', '\Delta\phi', '\Delta\kappa_H', '\Delta\kappa_V', 'Slide distance', 'touch duration', ...
'\theta', '\phi', '\kappa_H', '\kappa_V', 'Arc length'};
nMice = length(mns);
wkvChanges = cell(nMice,1);
maxTouchNum = zeros(nMice,1);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]);
wfa.trials = wfa.trials';
% load([baseDir, mns{mi}(3:5), filesep, 'Uber', mns{mi}, sns{mi}, '_NC'])
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunks), wfa.trials));
touchTrialInd = find(cellfun(@(x) length(x.protractionTFchunks), wfa.trials));
featureMat = cell(nFeatures, 1);
featureMat{1} = cellfun(@(x) cellfun(@(y) x.theta(y(find(nanmax(abs(x.theta(y)-x.theta(y(1))))==abs(x.theta(y)-x.theta(y(1))),1)))-x.theta(y(1)), ...
x.protractionTFchunks( intersect(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunks)))), find(isfinite(x.kappaH(cellfun(@(z) z(1), x.protractionTFchunks))))) )), ...
wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) cellfun(@(y) x.phi(y(find(nanmax(abs(x.phi(y)-x.phi(y(1))))==abs(x.phi(y)-x.phi(y(1))),1)))-x.phi(y(1)), ...
x.protractionTFchunks( intersect(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunks)))), find(isfinite(x.kappaH(cellfun(@(z) z(1), x.protractionTFchunks))))) )), ...
wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{3} = cellfun(@(x) cellfun(@(y) x.kappaH(y(find(nanmax(abs(x.kappaH(y)-x.kappaH(y(1))))==abs(x.kappaH(y)-x.kappaH(y(1))),1)))-x.kappaH(y(1)), ...
x.protractionTFchunks( intersect(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunks)))), find(isfinite(x.kappaH(cellfun(@(z) z(1), x.protractionTFchunks))))) )), ...
wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) cellfun(@(y) x.kappaV(y(find(nanmax(abs(x.kappaV(y)-x.kappaV(y(1))))==abs(x.kappaV(y)-x.kappaV(y(1))),1)))-x.kappaV(y(1)), ...
x.protractionTFchunks( intersect(find(isfinite(x.theta(cellfun(@(z) z(1), x.protractionTFchunks)))), find(isfinite(x.kappaH(cellfun(@(z) z(1), x.protractionTFchunks))))) )), ...
wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{5} = cellfun(@(x) cellfun(@(y) nanmax(y), x.protractionSlide), wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{6} = cellfun(@(x) x.protractionTouchDuration, wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunks))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{8} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunks))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{9} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunks))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{10} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunks))', wfa.trials(touchTrialInd), 'uniformoutput', false);
featureMat{11} = cellfun(@(x) x.arcLength(cellfun(@(y) y(1)-1, x.protractionTFchunks))', wfa.trials(touchTrialInd), 'uniformoutput', false);
% angles = unique(cellfun(@(x) x.angle, wfa.trials(touchTrialInd)));
angles = unique(cellfun(@(x) x.poleAngle, wfa.trials(touchTrialInd)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
% angleInd = find(cellfun(@(x) x.angle == angles(ai), u.trials(touchTrialInd)));
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialInd)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChanges{mi}{ai,fi} = tempMat;
% wkvMat = tempMat - tempMat(:,1);
% wkvChanges{mi}{ai,fi} = wkvMat;
end
end
end
%
colorsList = jet(7);
if length(angles) == 2
colors = colorsList([1,7],:);
elseif length(angles) == 7
colors = colorsList([1:7],:);
else
error('Error in length of angles')
end
maxTn = max(maxTouchNum);
figure('units','normalized','outerposition',[0.1 0.1 0.66 0.67])
for fi = 1 : nFeatures
subplot(3,4,fi), hold on
% for ai = 1 : length(angles)
% tempMat = nan(length(mns), maxTn);
% for mi = 1 : nMice
% tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
% end
% shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
% end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi});
end
plot(mean(tempMat), '-', 'color', colors(ai,:))
end
title(featureNames{fi})
if fi==8
xlabel('Touch order')
end
% set(gca,'fontsize',12)
end
% subplot(3,4,nFeatures+1)
legend(cellfun(@(x) [num2str(x), '\circ'], mat2cell(angles, ones(length(angles),1)), 'uniformoutput', false), 'location', 'northeastoutside')
%%
%% Results: It's not because of splitting touches into different whiskings
%%
%% Now, show the summarizing figure of theta, phi, kappaV and base height.
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
nMice = length(mns);
maxTouchNum = zeros(nMice,1);
baseHeight = cell(nMice,1);
nFeatures = 7; % theta, phi, base height, kappaV, touch height
featureNames = {'\theta', '\phi', 'Whisker base height','\kappa_V', 'Touch pole height', 'Touch pole position', '\kappa_H'};
maxTouchOrder = 10;
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
w3a = Whisker.Whisker3D_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the whisker base height information
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndW3 = find(ismember(w3a.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, w3a.trialNums(touchTrialIndW3))); % assume sorted
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsW3 = cellfun(@(x,y) cellfun(@(z) find(abs(x.time-z) == nanmin(abs(x.time - z)),1), y, 'uniformoutput', false), w3a.trials(touchTrialIndW3), touchOnsetTimes', 'uniformoutput', false);
featureMat{1} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{3} = cellfun(@(x,y) cellfun(@(z) x.base(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
featureMat{5} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
featureMat{6} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,1)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
%%
angles = unique(cellfun(@(x) x.servoAngle, w3a.trials(touchTrialIndW3)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialIndWF)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChanges{mi}{ai,fi} = tempMat;
end
end
end
%%
colorsList = jet(7);
if length(angles) == 2
colors = colorsList([1,7],:);
elseif length(angles) == 7
colors = colorsList([1:7],:);
else
error('Error in the length of ''angles''')
end
maxTn = max(maxTouchNum);
% figure('units','normalized','outerposition',[0.1 0.1 0.66 0.67])
figure,
for fi = 1 : nFeatures
subplot(3,3,fi), hold on
% for ai = 1 : length(angles)
% tempMat = nan(length(mns), maxTn);
% for mi = 1 : nMice
% tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi} - wkvChanges{mi}{ai,fi}(:,1));
% end
% tempMat = tempMat(:,1:maxTouchOrder);
% shadedErrorBar(1:size(tempMat,2), mean(tempMat), std(tempMat)./sqrt(sum(~isnan(tempMat))), 'lineprops', {'color',colors(ai,:)})
% end
for ai = 1 : length(angles)
tempMat = nan(length(mns), maxTn);
for mi = 1 : nMice
tempMat(mi,1:maxTouchNum(mi)) = nanmean(wkvChanges{mi}{ai,fi} - wkvChanges{mi}{ai,fi}(:,1));
end
tempMat = tempMat(:,1:maxTouchOrder);
plot(mean(tempMat), '-', 'color', colors(ai,:))
end
title(featureNames{fi})
if fi==7
xlabel('Touch order')
end
% set(gca,'fontsize',12)
end
% subplot(3,4,nFeatures+1)
legend(cellfun(@(x) [num2str(x), '\circ'], mat2cell(angles', ones(1,length(angles))), 'uniformoutput', false), 'location', 'northeastoutside')
%% Find the best representing mouse
%% From matching phi, theta, and whisker base height in 45 and 135 degrees of both naive and expert 7 angles
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
nMice = length(mns);
maxTouchNum = zeros(nMice,1);
baseHeight = cell(nMice,1);
nFeatures = 3; % theta, phi, base height
% featureNames = {'\theta', '\phi', 'Whisker base height','\kappa_V', 'Touch pole height', 'Touch pole position', '\kappa_H'};
maxTouchOrder = 10;
wkvChanges = cell(1,nMice);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
w3a = Whisker.Whisker3D_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the whisker base height information
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndW3 = find(ismember(w3a.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, w3a.trialNums(touchTrialIndW3))); % assume sorted
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsW3 = cellfun(@(x,y) cellfun(@(z) find(abs(x.time-z) == nanmin(abs(x.time - z)),1), y, 'uniformoutput', false), w3a.trials(touchTrialIndW3), touchOnsetTimes', 'uniformoutput', false);
featureMat{1} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
% featureMat{4} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
% featureMat{7} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{3} = cellfun(@(x,y) cellfun(@(z) x.base(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
% featureMat{5} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
% featureMat{6} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,1)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
%%
angles = unique(cellfun(@(x) x.servoAngle, w3a.trials(touchTrialIndW3)));
wkvChanges{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialIndWF)));
for fi = 1 : nFeatures
wkvChanges{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChanges{mi}{ai,fi} = tempMat(:,1:maxTouchOrder);
end
end
end
%%
templateNaiveEach = cellfun(@(x) cellfun(@nanmean, [x(1,:),x(7,:)], 'uniformoutput', false), wkvChanges, 'uniformoutput', false);
templateNaive = zeros(maxTouchOrder, nFeatures*2);
for i = 1 : nFeatures*2
templateNaive(:,i) = mean(cell2mat(cellfun(@(x) x{i}, templateNaiveEach', 'uniformoutput', false)))';
end
%%
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
wkvChangesExpert = cell(1,nMice);
for mi = 1 : nMice
% for mi = 3
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
w3a = Whisker.Whisker3D_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the whisker base height information
maxTouchNum(mi) = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndW3 = find(ismember(w3a.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, w3a.trialNums(touchTrialIndW3))); % assume sorted
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsW3 = cellfun(@(x,y) cellfun(@(z) find(abs(x.time-z) == nanmin(abs(x.time - z)),1), y, 'uniformoutput', false), w3a.trials(touchTrialIndW3), touchOnsetTimes', 'uniformoutput', false);
featureMat{1} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
% featureMat{4} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
% featureMat{7} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{3} = cellfun(@(x,y) cellfun(@(z) x.base(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
% featureMat{5} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
% featureMat{6} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,1)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
%%
angles = unique(cellfun(@(x) x.servoAngle, w3a.trials(touchTrialIndW3)));
wkvChangesExpert{mi} = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialIndWF)));
for fi = 1 : nFeatures
wkvChangesExpert{mi}{ai,fi} = nan(length(angleInd),maxTouchNum(mi));
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum(mi) - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChangesExpert{mi}{ai,fi} = tempMat(:,1:maxTouchOrder);
end
end
end
%%
templateExpertEach = cellfun(@(x) cellfun(@nanmean, [x(1,:),x(7,:)], 'uniformoutput', false), wkvChangesExpert, 'uniformoutput', false);
templateExpert = zeros(maxTouchOrder, nFeatures*2);
for i = 1 : nFeatures*2
templateExpert(:,i) = mean(cell2mat(cellfun(@(x) x{i}, templateExpertEach', 'uniformoutput', false)))';
end
%% same naive and expert mouse
templateAll = [templateNaive, templateExpert];
templateAllEach = cellfun(@(x,y) [x,y], templateNaiveEach, templateExpertEach, 'uniformoutput', false);
corrVal = zeros(nMice,nFeatures*2*2);
for i = 1 : nFeatures*2*2
temp = corr(templateAll(:,i), cell2mat(cellfun(@(x) x{i}', templateAllEach, 'uniformoutput', false)));
corrVal(:,i) = (temp-min(temp))./(max(temp)-min(temp));
end
[~, corrSortedInd] = sort(sum(corrVal,2),'descend');
%% result: 3,2,6,1,4,5
%% only from naive
corrValNaive = zeros(nMice,nFeatures*2);
for i = 1 : nFeatures*2
temp = corr(templateNaive(:,i), cell2mat(cellfun(@(x) x{i}', templateNaiveEach, 'uniformoutput', false)));
corrValNaive(:,i) = (temp-min(temp))./(max(temp)-min(temp));
end
[~, corrNaiveSortedInd] = sort(sum(corrValNaive,2),'descend');
%% result: 3,1,6,2,5,4
%% only from expert
corrValExpert = zeros(nMice,nFeatures*2);
for i = 1 : nFeatures*2
temp = corr(templateExpert(:,i), cell2mat(cellfun(@(x) x{i}', templateExpertEach, 'uniformoutput', false)));
corrValExpert(:,i) = (temp-min(temp))./(max(temp)-min(temp));
end
[~, corrExpertSortedInd] = sort(sum(corrValExpert,2),'descend');
%% result: 2,4,3,6,1,5
%% show summary graphs
mi = 3;
figure
subplot(231), hold on
plot(templateNaiveEach{mi}{1}, 'b-')
plot(templateNaiveEach{mi}{4}, 'r-')
title('\theta')
subplot(232), hold on
plot(templateNaiveEach{mi}{2}, 'b-')
plot(templateNaiveEach{mi}{5}, 'r-')
title('\phi')
subplot(233), hold on
plot(templateNaiveEach{mi}{3}, 'b-')
plot(templateNaiveEach{mi}{6}, 'r-')
title('whisker base height')
subplot(234), hold on
plot(templateExpertEach{mi}{1}, 'b-')
plot(templateExpertEach{mi}{4}, 'r-')
subplot(235), hold on
plot(templateExpertEach{mi}{2}, 'b-')
plot(templateExpertEach{mi}{5}, 'r-')
subplot(236), hold on
plot(templateExpertEach{mi}{3}, 'b-')
plot(templateExpertEach{mi}{6}, 'r-')
%% Show video and consecutive touch kinematics of whisker in 3D
mns = [{'JK025'},{'JK027'},{'JK030'},{'JK036'},{'JK039'},{'JK052'}];
% sns = [{'S05'},{'S02'},{'S04'},{'S02'},{'S02'},{'S05'}]; %naive
% sns = [{'S18'},{'S07'},{'S20'},{'S16'},{'S21'},{'S20'}]; %expert
sns = [{'S04'},{'S03'},{'S03'},{'S01'},{'S01'},{'S03'}]; %naive discreteAngles
% sns = [{'S19'},{'S10'},{'S21'},{'S17'},{'S23'},{'S21'}]; %expert discreteAngles
% sns = [{'S22'},{'S14'},{'S22'},{'S18'},{'S24'},{'S26'}]; %radial distance
baseDir = 'Y:\Whiskernas\JK\whisker\tracked\';
mi = 3;
nFeatures = 7; % theta, phi, base height, kappaV, touch height
featureNames = {'\theta', '\phi', 'Whisker base height','\kappa_V', 'Touch pole height', 'Touch pole position', '\kappa_H'};
maxTouchOrder = 10;
wfa = Whisker.WhiskerFinal_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the touch information
wfa.trials = wfa.trials';
w3a = Whisker.Whisker3D_2padArray([baseDir, mns{mi}, sns{mi}]); % to get the whisker base height information
maxTouchNum = max(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialTotalIndWF = find(cellfun(@(x) length(x.protractionTFchunksByWhisking), wfa.trials));
touchTrialNum = cellfun(@(x) x.trialNum, wfa.trials(touchTrialTotalIndWF));
touchTrialIndW3 = find(ismember(w3a.trialNums, touchTrialNum)); % assume sorted
touchTrialIndWF = find(ismember(wfa.trialNums, w3a.trialNums(touchTrialIndW3))); % assume sorted
touchOnsetTimes = cellfun(@(x) cellfun(@(y) x.time(y(1)-1), x.protractionTFchunksByWhisking, 'uniformoutput', false), wfa.trials(touchTrialIndWF), 'uniformoutput', false);
touchOnsetIndsW3 = cellfun(@(x,y) cellfun(@(z) find(abs(x.time-z) == nanmin(abs(x.time - z)),1), y, 'uniformoutput', false), w3a.trials(touchTrialIndW3), touchOnsetTimes', 'uniformoutput', false);
featureMat{1} = cellfun(@(x) x.theta(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{2} = cellfun(@(x) x.phi(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{4} = cellfun(@(x) x.kappaV(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{7} = cellfun(@(x) x.kappaH(cellfun(@(y) y(1)-1, x.protractionTFchunksByWhisking))', wfa.trials(touchTrialIndWF), 'uniformoutput', false);
featureMat{3} = cellfun(@(x,y) cellfun(@(z) x.base(z-1,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
featureMat{5} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,3)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
featureMat{6} = cellfun(@(x,y) cellfun(@(z) x.intersectPoint(z,1)/x.pxPerMm, y), w3a.trials(touchTrialIndW3)', touchOnsetIndsW3', 'uniformoutput', false);
angles = unique(cellfun(@(x) x.servoAngle, w3a.trials(touchTrialIndW3)));
angleTn = cell(length(angles),1);
%
wkvChanges = cell(length(angles), nFeatures);
for ai = 1 : length(angles)
angleInd = find(cellfun(@(x) x.poleAngle == angles(ai), wfa.trials(touchTrialIndWF)));
angleTn{ai} = wfa.trialNums(touchTrialIndWF(angleInd));
for fi = 1 : nFeatures
wkvChanges{ai,fi} = nan(length(angleInd),maxTouchNum);
featureCell = cellfun(@(x) [x, nan(1,maxTouchNum - length(x))], featureMat{fi}(angleInd), 'uniformoutput', false);
tempMat = cell2mat(featureCell);
wkvChanges{ai,fi} = tempMat(:,1:maxTouchOrder);
end
end
%% finding the best correlated trial
% ai = 1; % for 45 degrees
ai = 7; % for 135 degrees
sorti = 3;
tempCell = wkvChanges(ai,:);
templates = cellfun(@nanmean, tempCell, 'uniformoutput', false);
% %%
% figure,
% for i = 1 : 7
% subplot(3,3,i), plot(templates{i})
% end
% %%
corrValNorm = zeros(size(tempCell{1},1), nFeatures);
for fi = 1 : nFeatures
tempMat = tempCell{fi}';
tempMat(isnan(tempMat)) = 0;
tempCorr = corr(templates{fi}', tempMat);
corrValNorm(:,fi) = (tempCorr - min(tempCorr)) ./ (max(tempCorr) - min(tempCorr));
end
[~, indSorted] = sort(sum(corrValNorm,2), 'descend');
tn = angleTn{ai}(indSorted(sorti));
w3ind = find(w3a.trialNums == tn);
w3 = w3a.trials{w3ind};
wfind = find(wfa.trialNums == tn);
wf = wfa.trials{wfind};
%
touchTimes = wf.time(cell2mat(cellfun(@(x) x', wf.protractionTFchunks, 'uniformoutput', false)));
touchOnsetTimes = wf.time(cellfun(@(x) x(1), wf.protractionTFchunksByWhisking));
touchIndsW3 = find(ismember(w3.time, touchTimes));
touchOnsetIndsW3 = find(ismember(w3.time, touchOnsetTimes));
% %
% % v = VideoWriter(sprintf('expert%03dd_%02d.avi',angles(ai),sorti),'Uncompressed AVI');
% v = VideoWriter(sprintf('naive%03dd_%02d.avi',angles(ai),sorti),'Uncompressed AVI');
% v.FrameRate = 31;
% open(v)
%
% maxLim = max(cell2mat(cellfun(@max, w3.trackerData(w3.poleUpFrames), 'uniformoutput', false)));
% minLim = min(cell2mat(cellfun(@min, w3.trackerData(w3.poleUpFrames), 'uniformoutput', false)));
%
% fh = figure;
% for i = 1 : length(w3.poleUpFrames)
% clf
% currFrame = w3.poleUpFrames(i);
% subplot(221), hold on
% show_one_3D(w3, currFrame, ismember(currFrame, touchIndsW3))
% xlim([minLim(1) maxLim(1)]), ylim([minLim(2) maxLim(2)]), zlim([minLim(3) maxLim(3)])
%
% subplot(222), hold on
% show_one_3D(w3, currFrame, ismember(currFrame, touchIndsW3), [0 90])
% title('Top-down view')
% xlim([minLim(1) maxLim(1)]), ylim([minLim(2) maxLim(2)]), zlim([minLim(3) maxLim(3)])
%
% text(maxLim(1)+10, maxLim(2)-10, [num2str(round( w3.time(currFrame) - w3.time(w3.poleUpFrames(1)) , 2)), ' s'])
%
% subplot(223), hold on
% show_one_3D(w3, currFrame, ismember(currFrame, touchIndsW3), [90 0])
% title('Front view')
% xlim([minLim(1) maxLim(1)]), ylim([minLim(2) maxLim(2)]), zlim([minLim(3) maxLim(3)])
%
% subplot(224), hold on
% show_one_3D(w3, currFrame, ismember(currFrame, touchIndsW3), [0 0])
% title('Lateral view')
% xlim([minLim(1) maxLim(1)]), ylim([minLim(2) maxLim(2)]), zlim([minLim(3) maxLim(3)])
%
% drawnow
% writeVideo(v,getframe(fh))
% end
% close(v)
%
maxLim = max(cell2mat(cellfun(@max, w3.trackerData(touchOnsetIndsW3), 'uniformoutput', false)));
minLim = min(cell2mat(cellfun(@min, w3.trackerData(touchOnsetIndsW3), 'uniformoutput', false)));
minColorVal = 0.2;
% figure('units','normalized','outerposition', [0.1 0.1 0.66 0.67])
figure,
numTouch = length(touchOnsetIndsW3);
whiskerColor = [linspace(1-minColorVal,0,numTouch); linspace(1-minColorVal,0,numTouch); linspace(1-minColorVal,0,numTouch)]';
baseColor = [linspace(1-minColorVal,minColorVal,numTouch); zeros(1,numTouch); zeros(1,numTouch)]';
touchColor = [zeros(1,numTouch); zeros(1,numTouch); linspace(1-minColorVal,minColorVal,numTouch)]';
for i = 1 : length(touchOnsetIndsW3)
frameNum = touchOnsetIndsW3(i);
x = w3.trackerData{frameNum}(w3.baseInd(frameNum):end,1);
y = w3.trackerData{frameNum}(w3.baseInd(frameNum):end,2);
z = w3.trackerData{frameNum}(w3.baseInd(frameNum):end,3);
subplot(221), hold on
plot3(x, y, z, '-', 'color', whiskerColor(i,:))
plot3(w3.base(frameNum,1), w3.base(frameNum,2), w3.base(frameNum,3), '.', 'markersize', 20, 'color', baseColor(i,:))
whisker = [x,y,z];
ind = find(sum((whisker-w3.intersectPoint(frameNum,:)).^2,2) == min(sum((whisker-w3.intersectPoint(frameNum,:)).^2,2)) );
plot3(x(ind), y(ind), z(ind), '.', 'markersize', 20, 'color', touchColor(i,:))
axis equal
xlim([minLim(1) maxLim(1)]), ylim([minLim(2) maxLim(2)]), zlim([minLim(3) maxLim(3)])
xlabel('A-P'), ylabel('M-L'), zlabel('D-V')
view(3)
subplot(222), hold on
plot3(x, y, z, '-', 'color', whiskerColor(i,:))
plot3(w3.base(frameNum,1), w3.base(frameNum,2), w3.base(frameNum,3), '.', 'markersize', 20, 'color', baseColor(i,:))
whisker = [x,y,z];