In MATLAB, you might want to try the errorbar function: http://www.mathworks.de/de/help/matlab/ref/errorbar.html
Alternatively, you can do it the dumb and manual way. For example, given a matrix of data points "a", you can calculate your means using the function m = mean(a), calculate your CIs (depending on what CI you need), and plot the results by hand.
Demonstration if you already know the mean and CI, assuming CIs are in a matrix CI (first and second column) and means are in a matrix a:
plot(1:length(CI),a,'o','markersize', 10) % plot the mean
hold on;
plot(1:length(CI),CI(1,:),'v','markersize', 6) % plot lower CI boundary
hold on;
plot(1:length(CI),CI(2,:),'^','markersize', 6) % plot upper CI boundary
hold on;
for I = 1:length(CI) % connect upper and lower bound with a line
line([I I],[CI(1,I) CI(2,I)])
hold on;
end;
axis([0 length(CI)+1 min(CI(1,:))*0.75 max(CI(2,:))*1.25]) % scale axis
Demonstration in the case where you know individual measurements, for a repeated-measures experiment, 3+ conditions, one condition per column, one subject per line in matrix a, no missing samples, 95% CI as by MATLAB's ttest():
[H,P,CI] = ttest(a); % calculate 95% CIs for every column in matrix a
% CIs are now in the matrix CI!
plot(1:length(CI),[mean(a)],'o','markersize', 10) % plot the mean
hold on;
plot(1:length(CI),CI(1,:),'v','markersize', 6) % plot lower CI boundary
hold on;
plot(1:length(CI),CI(2,:),'^','markersize', 6) % plot upper CI boundary
hold on;
for I = 1:length(CI) % connect upper and lower bound with a line
line([I I],[CI(1,I) CI(2,I)])
hold on;
end;
axis([0 length(CI)+1 min(CI(1,:))*0.75 max(CI(2,:))*1.25]) % scale axis