If you have the Statistics Toolbox, you might find the dfittool distribution fitting tool quite useful.
If not, you can normalize a histogram by scaling the counts in each bin. With the normalized counts, you can plot both the normalized histogram and your curve. The trick is to identify the appropriate scaling factor.
Here is some example code where I plot the normal probability with the normalized histogram data:
dataVec = randn(1000,1);
muData = mean(dataVec);
stdData = std(dataVec);
binStep = 0.1;
binCenters = -5:binStep:5;
binCount = histc(dataVec,binCenters);
probScale = sum(binCount)*binStep;
histHandle = bar(binCenters,binCount/probScale,'hist');
x = binCenters;
y = normpdf(x,muData,stdData);
Hope this helps to get you started!