Spectral Data Quality (continuous eeg)
The Spectral Data Quality (continuous eeg) routine provides coarse information about the amount of power in different frequency bands. This is useful for assessing types of noise that are confined to specific EEG bands. For example, skin potentials predominantly produce low-frequency voltages (under ~3 Hz), and line noise produces narrow spikes at the line frequency (60 Hz in North America and some other parts of the world, 50 Hz in Europe and most of Asia). This routine allows you to quantify the amplitude or power in whatever frequency bands you like. More precise information about data quality can be obtained at the time of averaging with our other data quality metrics. However, those metrics require more extensive preprocessing, and the Spectral Data Quality (continuous eeg) routine provides a quick assessment of data quality on the continuous EEG with minimal preprocessing. This routine works only with continuous EEG data.
Important Notes:
- Before using this routine, you should do a quick cleaning of the continuous EEG using both Delete Time Segments (continuous EEG) and Artifact Rejection (continuous EEG).
- These routines will eliminate the periods of time between trial blocks and periods with extreme noise (e.g., when an electrode has become disconnected or the subject scratches the electrode cap).
- These periods will not impact your final data quality, but they can have a large impact on the Spectral Data Quality (continuous eeg) routine. If you do not remove them, the output of this routine may be misleading.
- For a more sophisticated analysis of EEG frequency content, see the FOOOF package.
This routine returns the averaged single-sided amplitude of frequency bands via Fast Fourier Transform from 5 second windowed segments of the continuous EEG. The windows are created and randomly selected from 20% of entire dataset to speed the routine performance. Using the GUI (see below), you can press "RESET" to use the default frequency bands that are commonly used in the neurosciences, or input new bands. In addition, you can select which channels to output spectral data from (you should not include channels that are not brain data, like eye-tracking channels or photodiodes).
[EEG, fft_out] = pop_continuousDFT( EEG, 'ChannelIndex', 1:64, 'Frequencies', [ 0 3; 3 8; 8 12; 8 30; 30 48; 49 51; 59 61; 0 250], 'FrequencyLabel',... {'delta' 'theta' 'alpha' 'beta' 'gamma' '60hz-noise' '70hz-noise' 'broadband' }, 'PercentRandom', 20, 'viewGUI',... 'true' );
Using the Viewer, you are able to change between spectra information in Amplitude or Power, and the results can be exported to either a matlab data file or Excel.
In order to plot spectral information, you must select one column in the data table as the frequency band, and as many channels/rows to represent the average across all the channels in that frequency band. The selection is made by clicking on the data table with your mouse. After the selection is made, press "PLOT".
