[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

%% 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