Electroencephalography (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 lay terms this sometimes is also called “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, or in more modern applications “Wavelet” analysis). The digital data is statistically analysed, sometimes comparing values with “normative” database reference values. 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 neurofeedback or 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 and processing efficiently.
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.
Introduction to QEEG based Neurofeedback:
It is presumptuous to think that the fields of QEEG and neuro-feedback (NF) are advanced far enough to have a scientifically QEEG based protocol that is a hard and fast rule. The field is scientific, but it is a scientific art at this time to use a QEEG to design an intervention. It is entirely foolhardy to make rules for this artistic task, so that is undoubtedly why I was approached for this task.
How does neurofeedback work?
An effective intervention into any system is to introduce feedback of the signal to be changed into the system This allows the system to self regulate, like the heating or cooling system in a house as a simple analogy. The models of how this works vary from systems theory, to anatomical/structural models, learning theory, even non-linear dynamics or “chaos theory”.
The organic models have some measurable validity, with the observed expansion of cortical areas dedicated to the structures utilized in tasks. Another observation supporting this model is the dendritic density increase in the cortex utilized in learned tasks. There are even reports recently of memory or ‘long term potentiation’ being predicted by the electro physiologic brain state measured at the time of the perception to be recalled (Wagner et al., Science, August 1988).
The learning theory models have learning curve data to show the stages of the acquisition of the skill of volitional control over the autonomic activity with NT. They also predict the effect on efficacy of the sessions’ scheduling to shorten the total treatment times; massing the initial sessions and stretching out the later session’s intervals. The systems theorists suggest the mere introduction of feedback may initiate self-regulation. This is seen with the audible heart beat normalizing the inter-beat interval, without any instructions to the subject.