I've followed the tutorial, but I'm not sure how to extract the single value I need. Where is it in the Matlab structure? (see "accessing FOOOF model parameters" in the tutorial)

If you are only interested in the frequency that has the maximum power between 8 and 12 Hz, you don't need any model to your spectrum, and you probably don't need FOOOF.

PsdMat = in_bst_timefreq('sepi01/@rawtutorial_eeg/timefreq_psd_230117_1242.mat');
for iChannel = 1:size(PsdMat.TF,1)
% Find the indices of the frequency bins of the alpha band
iFreqs = find((PsdMat.Freqs >= 8) & (PsdMat.Freqs <= 12));
% Find the maximum power
[maxPower, maxIndex] = max(squeeze(PsdMat.TF(iChannel, :, iFreqs)));
% Get the frequency value that has the max power
maxFreq = PsdMat.Freqs(iFreqs(maxIndex));
% Display the result
disp(sprintf('Channel %s: maxFreq=%1.2fHz, maxPower=%g', PsdMat.RowNames{iChannel}, maxFreq, maxPower));
end

Thanks for checking in: you can proceed as Francois indicated above (script or visual inspection) ; you can also retrieve and process the output parameters of FOOOF using a relatively straightforward script.

Thank you. Unfortunately, I don't have much experience with these kinds of scripts. I couldn't find an example in any tutorial (including the EEG & Epilepsy tutorial cited above). By any chance, do you have any examples?

Thanks, Sylvain. I've managed to make the script work, but unfortunately it has an extremely low resolution. It gives me values in the 9, 10, 11 Hz, but it should have a precision around 0.125 Hz. Do you know what is the problem?

For example, this is what a paper describes:

"For each participant and for all electrodes, including the ROI, a full power spectrum was obtained through a Fast Fourier Transform (FFT) with zero-padded window (nominal frequency resolution 0.125Hz) and individual alpha frequency (IAF) was determined for each participant as the value corresponding to the maximum peak frequency within the 8-14 Hz range"

I believe it's the settings in bold that determines this precision?

The minimum frequency that can be resolved, (aka frequency resolution), is the reciprocal of the window length that was used con compute the Fourier transform (FT). In this case, the FT was computed over 1-s windows.

In Brainstorm, the FT does not use zero padding.

While zero-padding can be used to increase the number of frequency bins, it does not increases the frequency resolution. The only way to increase the frequency resolution is by increasing the window length. Zero-padding (in the time domain), has the same effect that interpolating the spectrum using a sinc kernel.

Few resources on this digital signal processing (DSP) topic:

Thank you very much for your reply, Raymundo. I've just tested this using different window lengths and indeed it seems to be the only way to increase frequency resolution.