function analyze_correlation_between_successive_pscs(pscmat,casecolor,livetrials_preinduc,livetrials_postinduc)
%designed for testing the hypothesis that the relation between the first and second PSCs of a given sweep have a  relationship at a given IPI -- does the bouton state fluctuate on these time scales?

livetrials=[livetrials_preinduc(1):livetrials_postinduc(end)];
    label_addendum='all trials';
markersize=4;

interval_vector=pscmat(1,livetrials)
psco=pscmat(3,livetrials);psco(find(psco<0))=0;
psca=pscmat(4,livetrials);psca(find(psca<0))=0;
possible_intervals=[25 50 100 200 400];

for present_interval=1:5
    figure(possible_intervals(present_interval)),hold on
    good_uns=find(interval_vector==possible_intervals(present_interval))
    if ~isempty(good_uns)
        x_vals=psco(good_uns)/mean(psco(good_uns));
        y_vals=psca(good_uns)/mean(psca(good_uns));
        plot(x_vals,y_vals,'o','markerfacecolor',casecolor,'markeredgecolor',casecolor,'markersize',markersize) 
        [p,s]=polyfit(x_vals,y_vals,1)
        plot([0 max(x_vals)],[p(2) p(2)+p(1)*max(x_vals)],'color',casecolor,'linewidth',.1)
        xlabel(strcat('PSC1', label_addendum))
        ylabel(strcat('PSC2', label_addendum))
        title(num2str(possible_intervals(present_interval)))
	end
end