A novel spatio-temporal decomposition of the EEG: derivation, validation and clinical application.

Objective: To obtain clinically useful graphical and numerical data on the distribution of activities in the EEG using a novel type of spatio-temporal decomposition.

Methods: The EEG is divided into 1/4 s epochs. An approximation to the spatial distribution of the locally dominant activity in each epoch is represented as a point in a spatial component space. Points representing epochs dominated by activity from the same source form a cluster. The centres of these clusters represent the global spatial component of each source. As each spatial component is identified, its corresponding temporal activity is removed from the record, allowing activity from sources with smaller amplitude to become dominant in the reduced record. Successive components are identified in the reduced record. The method was applied to 40 normal EEGs and features were identified, which were common to them all. The method was also applied to 4 separate records with different forms of focal abnormality.

Results: The method successfully separated components from the EEG representing alpha rhythm, eye artefact, electrode artefact and EEG. In 40 normal EEGs the method isolated spatial components that were common to all EEGs, and in 4 abnormal EEGs it achieved a high degree of mutual separation of alpha rhythm, focal spikes, focal theta and focal delta activities.

Conclusions: The method achieved a high degree of mutual separation of the EEG components and successfully differentiated the artefacts due to eye movement, ECG and electrode faults. The clinical implications are discussed.