To plot your data against one another you could use plotyy
% make up some data
volume = [1:13]'+wgn(13,1, 10); % add some wgn noise to the simulated data
pressure = [1:60]'+wgn(60,1, 10);
% create time vectors, assuming each variable is linearly spaced (this may
% not be the case, but just an assumption)
t1 = linspace(0,400, 13)';
t2 = linspace(0,400, 60)';
% plot them against each other
ax = plotyy(t1, volume,t2, pressure); hold on;
ylabel(ax(1), 'Volume');
ylabel(ax(2), 'Pressure');
legend({'Volume', 'Pressure'});
Without knowing more information about the time vs. amplitude relationship of your data, it is hard to give you a direct answer as to how to interpolate your results to any given time point. However, if your data have a linear relationship (e.g. volume increases linearly as a function of time), then you could do a simple regression to get a best fit to your data, and interpolate from the result:
% If your variables have a linear relationship, them find a regressor that
% fits the data. Otherwise, need more info about the x-y relationship of
% your data to fit a proper curve (look at curve fitting toolbox for more info)
% create a vector of all times of interest (e.g. 0-400ms, in 1ms steps)
t3 = linspace(0,400, 401);
% find regression line that fits the data
X = [ones(length(volume),1) t1];
b = X\volume;
y = b*t3;
figure;
plot(t1, volume, 'o'); hold on;
plot(t3,y(2,:)); % plot the slope+intercept
plot(t3(100), y(2,100), '^', 'markersize', 18);
legend({'Volume', 'Regression Fit to Data', 'Data fit at t=100ms'});
