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Spatio-temporal EEG data
processing under MATLAB

What is g.EEGtoolbox for g.BSanalyze?

g.EEGtoolbox is an interactive environment for spatio-temporal EEG data processing.

Specialized functions for EEG artifact detection and data quality computations assure highest-quality results. Adaptive Filtering or bandpower analyses allow to extract EEG signal parameters. The parameter extraction section includes also the extraction of Hjorth and Barlow parameters.

Signal similarities in the time domain are determined by cross-correlation methods. In the frequency domain coherence analysis yield linear couplings as function of frequency. Signal Averaging methods allow to determine phase-locked Evoked-Potentials. A section with sophisticated functions for Event-Related Desynchronization and Event-Related Synchronization analyses allow to investigate stimulus- but non-phase locked EEG phenomena.

The graphical user interface for g.EEGtoolbox enables you to explore EEG data sets and to extract relevant information that can not be seen from raw data only. Results of multi-channel computations are visualized in the result2D tool allowing also topographical arangement of the results. You can load and save your preferred processing steps as a script program and automatically process your data in batch mode.

Toolbox Highlights

Data quality  
Power spectrum estimation and comparison with significance analysis  
Bandpower estimation, Hjorth Parameter estimation, Barlow Parameter estimation  
Cross correlation based template matching  
Wavelet Analysis  
Electrode montages definition and topographical mapping  
Event-related coherence / Coherence analysis  
Event-Related Desynchronization (ERD) / Event-Related Synchronization (ERS) analysis  
Time-Frequency ERD/ERS analysis  

Example: Determination of Event-Related Synchronization (ERD)

Power Spectral Density estimation (Fourier Transformation)

The first step in ERD quantification is to identify the subject's specific most reactive frequency bands.

EEG during right hand and foot movement imagery was recorded over electrode positions C3 and Cz. The type of movement imagery was given via experimental instructions on the computer screen. A total of 160 imaginations of movements were performed (80 hand and 80 foot movements).

The analyze menu Spectrum allows to compute the power spectral density (PSD) of your data. PSD is a measure of how power in a signal changes as a function of frequency. The spectral analysis detects periodic oscillations (amplitude and frequency) and has been employed in a great variety of signal processing applications.

g.BSanalyze allows not only to compute the PSD for specific time segments, but also to statistically compare the PSD between data segments.

Hence differences in the PDS between reference periods versus active periods can be found easily.

The figure to the right displays the PSDs for an EEG signal in the reference period (color coded blue) and active period (color coded green). At a frequency of about 17 Hz there is a significant amplitude difference for the 2 period. The graph at the top (color coded violett) displays the amplitude difference. The dashed lines represent the 95% siginifance level. Values exceeding the dashed lines indicate significant differences.

Quantification of ERD as function of time

The second step is to quantify ERD within the most reactive frequency bands as function of time. Hence one can observe time evolution of ERD over different brain areas.

Different options exist to express Event-Related Synchronization and Event-Related Synchronization.

(i) ERD/ERS values can be expressed as absolute power values varying over time or

(ii) ERD/ERS values can be related to a so-called reference period. Then time varying ERD/ERS values are given in percentage values indicating the relative power decrease or increase with respect to the reference period.

The figure to the left displays percentage values of ERD/ERS over time. The reference period is indicated as a horizontal red line. After second 2 ERD values decrease to about -50%. Between second 5 and 8 an ERS can be observed with a bandpower increase of up to 300 %.

Time-Frequency distribution of ERD/ERS

g.EEGtoolbox allows for a third option in calculating ERD/ERS:
A novel time-frequency computation and representation allows to conveniently identify the most reactive frequency bands and the related channels.

The analyze menu ERDmaps allows to calculate ERD and ERS for multiple frequency bands and to present the results in a single colormap per channel.

ERDmaps can be calculated without a significance statistics (fast) or with a bootstrap algorithm. When using the bootstrap algorithm it is possible to define a significance level. Then, ERD and ERS are only displayed if they are within the specific confidence range.
 

Example: Topographical Mapping of results

The result of spatio-temporal computations can be displayed in the 2D result presentation tool g.Result2D.

After defining the corresponding electrode montage for the EEG experiment in the montage creator g.MONcreator, including electrode co-ordinates and electrode names, computational results can be displayed topographically.

The figure to the left displays the average and standard deviation for a 60 channel ERD/ERS experiment.

Topographical plots of grand averages and standard deviations are a very useful tool to discover artifacts in the data.

If technical artifacts (e.g. cross-talk of trigger channels) can not be ruled out, then such artifact can be detected and made visible by simple averaging across trials.


Download brochure: EEG-Toolbox (PDF 1.5 MByte)

Download complete brochure: g.BSanalyze (PDF 5.7 MByte)
 

Package includes Software modules, help manual, hardlock
Technical Requirements MATLAB, g.BSanalyze base version

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