The earliest recording of human brain electrical activity was in 1875. Researchers have found the study of the human EEG a fascinating area of investigation, and many thousands of published studies are listed in the scientific literature. Physicians and other health care professionals have also used EEG analysis to identify brain electrical activity patterns associated with epilepsy, mild traumatic brain injury (mTBI), Post-Traumatic Stress Disorder (PTSD), and more (Niedermeyer & da Silva, 1999). Graphic © Chaikom/Shutterstock.com.
Most EEG investigations have involved viewing brain electrical signals plotted on a graph as waves that show the speed of the waves and the amount of electrical energy represented by the waves. This requires a great deal of experience and training because the electrical patterns are quite complex and are often affected by multiple factors such as brain structure, the effects of medications or other substances, and level of alertness or drowsiness (Tatum, 2014).
In the 1970s, researchers introduced digital EEG recording devices and computers to analyze brain electrical activity using new mathematical and statistical tools. Although controversial among some neurologists and electroencephalographers, other EEG professionals have found these techniques helpful (Livint Popa et al., 2020). The qEEG involves digitized statistical brain mapping using at least a 19-channel montage to measure EEG amplitude within specific frequency bins. Graphic © Zyabich/Shutterstock.com.
The qEEG has allowed EEG investigators to create large databases of typical individuals, which are used to compare patients/clients being evaluated in clinical practice settings. For example, Newer and Coutin-Churchman (2012) found that qEEG is more sensitive than routine EEG for detecting cerebral hemispheric abnormalities related to cerebrovascular disease. It is not as spatially precise as the functional MRI (fMRI) but is non-invasive, significantly less expensive, and easier to administer.
Many clinicians have found that adding the qEEG to their practice improves their assessment process, helping to differentiate between anxiety and depression, PTSD and mTBI, ADHD, and learning disabilities. qEEG-guided neurofeedback training helps their clients to decrease dysfunctional brain activity and promote optimal performance. Professional use of the qEEG and neurofeedback is growing. Thousands of psychologists and physicians use these methods worldwide (Arns et al., 2017).
Summary
EEG professionals increasingly employ the qEEG to differentiate between clinical conditions and guide neurofeedback training to decrease dysfunctional brain activity and promote optimal performance.
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References
Arns, M., Batail, J. M., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., Fovet, T., Jardri, R., Le-Van-Quyen, M., Lotte, F., Mehler, D., Micoulaud-Franchi, J. A., Purper-Ouakil, D., Vialatte, F., & NExT group (2017). Neurofeedback: One of today's techniques in psychiatry? L'Encephale, 43(2), 135–145.
Livint Popa, L., Dragos, H., Pantelemon, C., Verisezan Rosu, O., & Strilciuc, S. (2020). The role of quantitative EEG in the diagnosis of neuropsychiatric disorders. Journal of Medicine and Life, 13(1), 8–15. https://doi.org/10.25122/jml-2019-0085
Niedermeyer, E. (1999). Historical aspects. In E. Niedermeyer & F. Lopes da Silva (Eds.), Electroencephalography: Basic principles, clinical applications, and related fields (4th ed.). Williams and Wilkins.
Nuwer, M. R., & Coutin-Churchman, P. (2012). Aminoff's electrodiagnosis in clinical neurology (6th ed.). M. J. Aminoff (Ed.). Elsevier.
Tatum, W. O. (2014). Handbook of EEG interpretation. Demos Medical Publishing.
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