It would help to have your data, however I created some to illustrate the approach:
f = linspace(0, 0.5, 25); % Frequency Vector
allspectrums_cortex_young = 1E+3*rand(5, 25) + 1600*exp(-10*f); % Synthetic Spectrum
mn_allspectrums_cortex_young = mean(allspectrums_cortex_young);
sd_allspectrums_cortex_young = std(allspectrums_cortex_young);
figure
plot(f, mn_allspectrums_cortex_young)
hold on
patch([f fliplr(f)], [(mn_allspectrums_cortex_young+sd_allspectrums_cortex_young) fliplr(mn_allspectrums_cortex_young-sd_allspectrums_cortex_young)], 'r', 'FaceAlpha',0.5, 'EdgeColor','none')
hold off
The approach (using the patch function) is to create a closed curve that patch then fills. That is done here by adding and then subtracting the std from the mean, after plotting the mean.
Example —
