The role of quantitative electroencephalography in diagnostic workup of mental disorders.

Abstract

Electroencephalography (EEG) is a non-invasive diagnostic tool, enabling us to assess the electrical activity of the brain and its disturbance in a great number of psychiatric conditions. This paper provides a narrative overview of the most recent advantages of EEG use in various psychiatric disorders that are associated. This article analyses selected psychiatric disorders. We discussed anxiety disorders characterized by chronic fear, dementia leading to cognitive decline, schizophrenia disrupting logical thinking, bipolar affective disorder with alternating episodes of mania and depression, and depression manifested by gradual loss of vital energy. We have shown that EEG testing, by monitoring the electrical activity of the brain, is a helpful tool in identifying specific brain wave patterns associated with these disorders. In the study of mental illness the EEG variant called quantitative EEG (QEEG) is of particular avail as to the spatial discrimination. QEEG is based on digital coding and transformation according to Fourier algorithm. Recently, even more complex methods of EEG data analysis have been implemented, including artificial intelligence (AI), deep learning (DL) and its branch: machine learning (ML). The use of sophisticated EEG postprocessing adds important information about the pathophysiology of mental disorders. More so, EEG/QEEG recording (in particular spectral analysis), if repeated over time may help to follow up the treatment results and to establish a prognosis as to the course of the given condition. Reliability, safety and availability of EEG makes it to be an indispensable tool in modern psychiatry. Use of EEG, QEEG may lead to faster and more precise differential diagnostic workup. Use of EEG/QEEG changes as an objective outcome measure in clinical trials may support the development of personalized pharmacotherapy or psychotherapy.