EEG biofeedback is the fastest growing area in biofeedback today Part of this interest is due to the fact that changes in instrumentation hardware and software have provided the means to quickly perform mathematical analysis of brain waves so that feedback about the EEG characteristics can be provided within fractions of a second after they are detected. However, recording the EEG is of great technical difficulty because the electrodes must be placed in the correct location while maintaining acceptable levels of impedance. Impedance is the electrical resistance between the electrodes and the skin and must be kept to a minimum in order to reduce unwanted electrical activity. The electrode placements are based on what is called the 10-20 international system, as described by Jasper in 1958. The 10-20 international system identifies positions on the scalp, which are directly over structures of the cortex. The details of electrode placement are beyond the scope of this article, but must be learned before attempting this biofeedback.
Neurologists interpret the EEG to determine abnormal brain function, as certain wave patterns are associated with brain disorders such as seizures. The EEG is also used to determine sleep stages. In most biofeedback applications, the use of the EEG is based not on the interpretation of the raw or unaltered EEG, but on the quantitative analysis of the EEG, called the QEEG. Mathematical analysis of the frequencies of brain waves determines the amount of each frequency occurring within a period of time or epoch. The mathematical analysis used in most applications is the technique based on the theorem developed by Joseph Fourier in 1822, called the fast Fourier transform (FFT). This is a mathematical routine or algorithm that takes each wave, determines its length in time as well as its amplitude, and then determines the average amount of energy in all the frequencies of interest. Computer systems today are capable of providing feedback about the QEEG characteristics within about 3/10 of a second after it is monitored. The results of this analysis can then be displayed on a computer monitor, allowing the individual to become aware of the nature of his or her brain waves. This occurs fast enough for the brain to alter its activity, according to its ability and the instructions provided the person.
The brain waves have information of interest in their amplitudes and frequencies. The frequencies were categorized into different bandwidths in the 1920s by Berger, and reported in 1929. He recorded the EEG activity from his children and labeled the EEG frequencies that he observed. These labels are still being used today although many are starting to abandon them, as they may be too restrictive. Four bandwidths (theta, alpha, sensory motor rhythm [SMR], and beta) are used extensively in clinical applications. Thus, they will be briefly described. Researchers are inconsistent in the frequency definitions of these bandwidths, so the reader must determine how each author defines them in an article. However, they are usually defined as follows: Theta is 4 to 8 Hz, alpha is 8 to 12 Hz, SMR is 12 to 15 Hz, and beta is 16 to 30 Hz. Beta has been used to define a wide range of frequencies, so it is extremely important for the reader to determine the definition of this bandwidth in an article. The reason these bandwidths have been identified is that they are loosely associated with psychological states: Theta with drowsiness, alpha with nonfocused attention, SMR with muscle activity inhibition, and beta with focused attention. Although these associated states have some heuristic value for adults, they are not consistent across individuals or age ranges. The other important characteristic of the QEEG is its amplitude, measured in microvolts or picawatts. This is a measure of the amount of energy within each frequency or bandwidth. Presently, there are a few databanks available for normative and abnormal values of the QEEG.
The methods presently used in most clinical QEEG biofeedback applications are based on determining which frequency or bandwidth is of interest and then providing the individual with information about its activity either via a shift in frequency or amplitude. There are other techniques used to provide information about the EEG, such as hemisphere asymmetries and average evoked potentials, but their use, at this time, is not as widespread as amplitude or frequency-based applications. The clinical protocol for QEEG feedback for the treatment of attention deficit disorder/attention deficit - hyperactivity disorder (ADD/ADHD) will be presented later in the section Case Illustrations.
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