[Eeglablist] Large Unexplained Differences in Power Values

Naomi Heffer nrh31 at bath.ac.uk
Tue Mar 9 01:55:47 PST 2021


Hi there,

I have been trying to calculate power in different frequency bands but I find that whether or not I clean the data using clean_artifacts before running the analysis has a very large impact on the magnitude of the power values.

Here is my code below, along with the absolute power values in each of the frequency bands when (a) I clean the data before running the analysis and (b) I don't use the clean_artifacts function to clean the data. Do you have any idea why I am seeing such massive differences in magnitude? And can you suggest which of the two sets of values is likely to be more realistic?

Many thanks

Naomi

%% 1. Opening & Importing to EEGLAB
        % Get data from .easy to EEGLAB .set/.fdt format

        EEG = pop_easy(filename, 1, 0,[]);

         % Setting the right channel locations. Reading montage file
          EEG = pop_chanedit(EEG, 'load',config,'save','mychans.loc');

 %% 2. Filtering

        % Filter data between 0.1 and 40Hz
        % High-pass filter
         EEG = pop_eegfiltnew(EEG, 0.5,[], 1690, 0, [], 0);
       % Low-pass filter
         EEG = pop_eegfiltnew(EEG, [], 35, 86, 0, [], 0);

 %% 3.Cleaning of continuous data

       clean = clean_artifacts(EEG, 'ChannelCriterion', 'off');
      vis_artifacts(clean, EEG)


%% 4. Spectral Analysis

[spectra,freqs] = spectopo(EEG.data(:,:,:), 0, EEG.srate, 'freqrange', [1 80], 'plotmean', 'on', 'overlap', 250);

% delta=1-4, theta=4-8, alpha=8-13, beta=13-30, gamma=30-80
deltaIdx = find(freqs>1 & freqs<4);
thetaIdx = find(freqs>4 & freqs<8);
alphaIdx = find(freqs>8 & freqs<13);
betaIdx  = find(freqs>13 & freqs<30);
gammaIdx = find(freqs>30 & freqs<80);

% compute absolute power
deltaPower = mean(10.^(spectra(deltaIdx)/10))
thetaPower = mean(10.^(spectra(thetaIdx)/10))
alphaPower = mean(10.^(spectra(alphaIdx)/10))
betaPower  = mean(10.^(spectra(betaIdx)/10))
gammaPower = mean(10.^(spectra(gammaIdx)/10))



  1.  Values with cleaning:
deltaPower =    3.2846
thetaPower =    2.4440
alphaPower =    8.9593
betaPower =    6.9579
gammaPower =    3.3659


  1.  Values without cleaning:
deltaPower =    1.5560e+03
thetaPower =   1.3541e+03
alphaPower =   2.7626e+03
betaPower =   1.0275e+03
gammaPower =   97.3422



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