rmeddis@0: function [cv, cvTimes, allTimeStamps, allISIs]=  UTIL_CV(earObject, dt, timeStep)
rmeddis@0: % UTIL_CV computes coefficient of variation for multiple spike trains
rmeddis@0: % earObject must be logical 0/1.  Each row is a separate run
rmeddis@0: % CV is computed for successive time regions specified by timeStep
rmeddis@0: 
rmeddis@0: if ~islogical(earObject),error('UTIL_CV: input is not logical/ spikes'), end
rmeddis@0: 
rmeddis@0: [rows cols]=size(earObject);
rmeddis@0: totalDuration=cols*dt;
rmeddis@0: 
rmeddis@0: if nargin<3, timeStep=totalDuration/5; end
rmeddis@0: 
rmeddis@0: % identify all intervals
rmeddis@0: allISIs=[]; allTimeStamps=[];
rmeddis@0: for i=1:rows
rmeddis@0:     temp=find(earObject(i,:))*dt;    % find spikes
rmeddis@0:     isi{i}=diff(temp);                      % find ISIs
rmeddis@0:     timeStamps{i}=temp(2:end); % time of isi is time of second spike
rmeddis@0:     allISIs=[allISIs isi{i}];
rmeddis@0:     allTimeStamps=[allTimeStamps timeStamps{i}];
rmeddis@0: end
rmeddis@0: 
rmeddis@0: count=0;
rmeddis@0: cvTimes=0: timeStep:totalDuration-timeStep; % bin edges
rmeddis@0: for t= cvTimes
rmeddis@0:     % sort ISIs according to when they happened
rmeddis@0:     idx=find(allTimeStamps>t & allTimeStamps<=t+timeStep);
rmeddis@0:     count=count+1;
rmeddis@0:     if ~isempty(allISIs(idx))
rmeddis@0:         cv(count)=std(allISIs(idx))/mean(allISIs(idx));
rmeddis@0:     else
rmeddis@0:         cv(count)=0;
rmeddis@0:     end
rmeddis@0: end
rmeddis@0: