The wavelet transformation feature for ASA offers time-frequency analysis of EEG and MEG data based on the Morlet Wavelet. The wavelet analysis can be applied to both raw EEG/MEG and averaged data.

The new module offers:

• Time-frequency transformation based on Morlet wavelets
  
• Can be applied to continuous and averaged EEG or MEG
  
• Wavelet averaging for different conditions
  
• ERD/ERS based on wavelets
  

Some examples are shown below:

Event related (de-)synchronization ERD/ERS of the wavelet transformation of brain activity. The example shows the ERD/ERS results for a voluntary finger movement task.

The time-frequency maps show a clear ERS related to the onset of the movement (indicated by the blue spot in the map, nicely visible for channel C3). The time course of the activity in the frequency band 18-24 Hz is shown on the right side. The vertical green line marks movement onset, the ERS is visible shortly after movement.
(click image to enlarge)

Averaging of the wavelet transformation of EP and ERP experiments. The example shows the average of the wavelet transformation of an auditory P300 experiment with two conditions, frequent and rare stimuli.
(click image to enlarge)

The time-frequency distribution of spike events is clearly visible with wavelet analysis. For each channel shown in the image on the right, the onset of the spike wave is displayed clearly in the corresponding time-frequency map for that channel.

Clicking on the time-frequency map automatically places the EEG time-marker at the corresponding latency in the EEG curves. This way, it is very evident how the EEG and wavelet time-frequency maps are related. A tooltip appears when moving the mouse over an area in the time-frequency map. The tooltip shows the current latency and frequency in Hz for that spot. (click image to enlarge)