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delContact.m
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delContact.m
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function contacts=delContact(toDel)
%% Trial Primary Contact Type Determination
%
% Estimates contact times of the whisker into the pole. Good results
% requires a very accurate .bar file and accurate touch thresholds. Four
% touch thresholds are used, for go (protraction, retraction), no-go
% (protraction,retraction). These should be determined by visual
% inspection of the distanceToPoleCenter plots in several example trials,
% in concert with the video of the trial. Use Parameter Estimation cell to
% help.
%
% In general, k represents a trial number, i represents some event number
% in the trial (contact, spike).
%
% First use some generous limits for the touchThresh values. Then, use the
% plot output of the Contact Segmenter cell to refine the touchThresh
% values and rerun the Trial Primary Contact Type Determination
%
% Use Parameter Estimation cell to check how well the contacts are being
% scored (currently broken?)
%
%
% Currently designed to work only with 1 whisker, but could be modified to
% analyze a specific tid.
%
% Designed to be used with the Whisker.WhiskerTrialLiteI subclass, which
% has two additional fields, M0I: Holds the acceleration calculated moment
% contactInds: Index of contact times
%
% Pulls data from array.trials{k}.whiskerTrial.M0I
% Stores data to a subclassed field : array.trials{k}.whiskerTrial.contactInds
% Also writes a contacts{k} structure to the workspace that contains all
% the analysis output.
%
% Version 0.1.0 SAH 06/07/10
%
%
%
%% Contact Segmenter
%
% Segmentation of contacts into an ordered list. Each trial gets its own
% cell within the contacts structure. Analysis of each contact resides in
% within fields of contacts{k}, where k is the trial index.
% (k ~= overall trial number)
%
% This cell also plots the distance to pole of the first trial of each
% class (go pro/ret, nogo pro/ret)
h_app = getappdata(0);
h_pBG = h_app.hParamBrowserGui;
pBG_data = getappdata(h_pBG);
array = pBG_data.array;
params = pBG_data.params;
contacts = pBG_data.contacts;
whiskerTIN = params.sweepNum;
framePeriodInSec = 1000;
if isfield('shanksTrial',array.trials{1})
sampleRate = array.trials{1}.shanksTrial.sampleRate;
elseif isfield('spikesTrial',array.trials{1})
sampleRate = array.trials{1}.spikesTrial.sampleRate;
end
if ~isfield(contacts{whiskerTIN},'manualDel')
contacts{whiskerTIN}.manualDel{1} = [];
end
if ~isfield(contacts{whiskerTIN},'manualAdd')
contacts{whiskerTIN}.manualAdd{1} = [];
end
if isempty(contacts{whiskerTIN}.manualDel{1})
contacts{whiskerTIN}.manualDel{1} = toDel(:)';
else
contacts{whiskerTIN}.manualDel{1} = unique(cat(2,toDel(:)',contacts{whiskerTIN}.manualDel{1}(:)'));
end
contacts{whiskerTIN}.contactInds{1} = setdiff(contacts{whiskerTIN}.contactInds{1},contacts{whiskerTIN}.manualDel{1});
contacts{whiskerTIN}.manualAdd{1} = setdiff(contacts{whiskerTIN}.manualAdd{1},contacts{whiskerTIN}.manualDel{1});
M0(whiskerTIN) = cellfun(@(x)x.whiskerTrial.M0{1}, array.trials(whiskerTIN),'UniformOutput',0);
time(whiskerTIN) = cellfun(@(x)x.whiskerTrial.time{1}, array.trials(whiskerTIN),'UniformOutput',0);
for k=whiskerTIN;
if isempty(contacts{k}.contactInds{1})==0;
contacts{k}.segmentInds{1}=[];
contacts{k}.segmentInds{1}(:,1)=contacts{k}.contactInds{1}([1 find(diff(contacts{k}.contactInds{1})>4)+1]); % don't switch back to intertial if the tracking disappears for 1-3 frames
contacts{k}.segmentInds{1}(:,2)=contacts{k}.contactInds{1}([find(diff(contacts{k}.contactInds{1})>4) end]);
ind=[];
for i=1:length(contacts{k}.segmentInds{1}(:,1))
ind=cat(2,ind,contacts{k}.segmentInds{1}(i,1):contacts{k}.segmentInds{1}(i,2));
end
contacts{k}.inferredInds{1} = setdiff(ind,contacts{k}.contactInds{1});
contacts{k}.contactInds{1} = ind;
else
contacts{k}.segmentInds={[]};
trialContactType(k)=0;
end
end
%% Contact Characterizer
% Find mean M0 for each contact
disp('Finding mean M0 for each contact')
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1})==0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
contacts{k}.meanM0{1}(i)=nanmean(M0{k}(contacts{k}.segmentInds{1}(i,1):contacts{k}.segmentInds{1}(i,2)));
end
else
contacts{k}.meanM0={[]};
end
end
% Find peak M0 for each contact
disp('Find peak M0 for each contact')
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1})==0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
contacts{k}.peakM0{1}(i)=max(abs(M0{k}(contacts{k}.segmentInds{1}(i,1):contacts{k}.segmentInds{1}(i,2))))*...
sign(contacts{k}.meanM0{1}(i));
end
else
contacts{k}.peakM0={[]};
end
end
% Find spikes associated with each contact
disp('Finding spikes associated with each contact')
if isfield('shanksTrial',array.trials{1})
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1}) == 0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
lim = time{k}(contacts{k}.segmentInds{1}(i,:)) + params.spikeSynapticOffset;
contacts{k}.spikeCount{1}(i,:) = cellfun(@(x)...
sum(double(x.spikeTimes) / sampleRate - array.whiskerTrialTimeOffset > lim(1)...
& double(x.spikeTimes) / sampleRate - array.whiskerTrialTimeOffset < lim(2)),...
array.trials{k}.shanksTrial.clustData);
end
else
contacts{k}.spikeCount={[]};
end
end
elseif isfield('spikesTrial',array.trials{1})
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1}) == 0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
lim = time{k}(contacts{k}.segmentInds{1}(i,:)) + params.spikeSynapticOffset;
contacts{k}.spikeCount{1}(i,:) = sum(double(array.trials{k}.spikesTrial.spikeTimes) / sampleRate - array.whiskerTrialTimeOffset > lim(1)...
& double(array.trials{k}.spikesTrial.spikeTimes) / sampleRate - array.whiskerTrialTimeOffset < lim(2));
end
else
contacts{k}.spikeCount={[]};
end
end
else
end
% Find timelength for each contact
disp('Finding timelength for each contact')
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1})==0
contacts{k}.contactLength{1}=time{k}(contacts{k}.segmentInds{1}(:,2))-time{k}(contacts{k}.segmentInds{1}(:,1));
else
contacts{k}.contactLength={[]};
end
end
disp('Merging contact/curvature-derived moment (M0) and axial force (FaxialAdj) with acceleration based moment (M0I)')
% Find mean M0 for each contact
disp('Finding mean Faxial for each contact')
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1})==0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
contacts{k}.meanFaxial{1}(i)=nanmean(contacts{k}.FaxialAdj{1}(contacts{k}.segmentInds{1}(i,1):contacts{k}.segmentInds{1}(i,2)));
end
else
contacts{k}.meanFaxial={[]};
end
end
% Find peak M0 for each contact
disp('Find peak Faxial for each contact')
for k = whiskerTIN
if isempty(contacts{k}.segmentInds{1})==0
for i=1:length(contacts{k}.segmentInds{1}(:,1));
contacts{k}.peakFaxial{1}(i)=min(contacts{k}.FaxialAdj{1}(contacts{k}.segmentInds{1}(i,1):contacts{k}.segmentInds{1}(i,2)));
end
else
contacts{k}.peakFaxial={[]};
end
end
setappdata(h_pBG,'contacts',contacts);
assignin('base','contacts',contacts);
display('Contact Deleted')