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Brain, as we all know, produces electrical potential. Though the voltage is often 1/millionth of a volt this can be recorded, measured and compared using sophisticated equipment. This measure is called Electroencephalography (EEG). EEG is the measurement of electrical patterns at the surface of the scalp which reflect cortical activity, and are commonly referred to as “brainwaves”. Quantitative EEG (qEEG) is the analysis of the digitized EEG, and in layman’s terms this sometimes also termed as “Brain Mapping”. The qEEG is an extension of the analysis of the visual EEG interpretation which may assist and even augment our understanding of the EEG and brain function.

Quantitative Electroencephalography (qEEG) is a procedure that processes the recorded EEG activity from a multi-electrode recording using a computer. This multi-channel EEG data is processed with various algorithms, such as the “Fourier” classically, Independent Component Analysis (ICA) or in more modern applications “Wavelet” analysis. The digital data is statistically analyzed, sometimes comparing values with “normative” database. The processed EEG is commonly converted into colour maps of brain functioning called “Brain Maps”.

The EEG and the derived qEEG information can be interpreted and used by experts as a clinical tool to evaluate brain function, and to track the changes in brain function due to various interventions such as Brain Function Training (Neurofeedback) or improve quality of Medication.

Quantitative Electroencephalography (qEEG) processing techniques and the use of modern analytic software to processes the EEG/qEEG gives us the ability to view the dynamic changes taking place throughout the brain during cognitive processing tasks, and this novel approach can be used to assist us in determining which areas of the brain are engaged & processing efficiently, and those that need enhancement.

Various analytic approaches exist, from commercial databases to database free approaches, such as EEG phenotype analysis or the more classic European Vigilance model of Bente (1964) are used in modern clinical application of the EEG/qEEG. The use of advanced techniques such as Independent Component Analysis (ICA) and neuro-imaging techniques such as Low Resolution Electromagnetic Tomography (LORETA) can map the actual sources of the cortical rhythms. These advanced approaches are changing our understanding of the dynamics and function of the human brain.

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