With EEG source analysis we attempt to bridge the gap between surface EEG data and the respective neural source generators: EEG dynamics reflect the collective action (superposition) of many neuronal systems distributed across the brain. Source analysis disentangles the different neuronal sources and gives you a hint where and when it happened. Information pathways in the brain can be studied by using either the reconstructed activation waveforms or by time-frequency analysis. Source analysis can identify the brain regions involved in different tasks and depending on data quality and model quality, yield a precise localization of the generators in both space and time.

=> Flyer – EEG ERP Source Analysis: open flyer

THE IDEAL PREREQUISITES WHEN DOING EEG SOURCE ANALYSIS are (A) high-quality EEG data, (B) precise localization of (individual) electrode positions and (C) a highly versatile / sophisticated but still user-friendly software solution.

• There is no substitute for good EEG data and this is particularly true for source analysis. The bulk of recent publications suggest using gel based active EEG electrodes as standard for EEG / ERP research, particularly if good data quality is important.
• Digitizing electrodes’ spatial positions in a precise and fast way is helpful for other applications as well. However, it is especially important for source analysis. For best results individual electrode positions from a EEG cap with an equidistant layout are used in a model with realistic head shapes (more details).
• An easy to use and powerful software, that can handle spatio-temporal dipole modelling, and source imaging methods that work in the brain volume or on the cortex, in the time domain or in the time-frequency domain. Optimally, all this should be available with standard realistic head models for various age groups or with superior individual finite element models that are generated from the subjects’ MRI data.