Why do I need Biomarkers?

Quantitative EEGPsychologists rely on psychometrics to gauge personality, pathology, motivation, learning difficulties. But despite built in lie scales, split half designs and a host of other clever statistical manipulations psychometric measurements are still represented by behavioral data gained from self or other report.

The fifth revised edition of The Diagnostic and Statistical Manual of Mental Disorders (DSM-V) in the beginning aimed to classify mental disorders according to biological markers. Due to the reluctant reactions of practices and the fact that there are still several uncertainties, the makers of the biomarker approach decided to postpone the inclusion of the approach into the DSM until the 6th revision. The new approach assumes that a psychiatric diagnosis is made not only from behavior, but also from the knowledge of which brain system is impaired. It is almost certain that the biomarker approach will become widely accepted because it leads to objectivity and transparency. Like thousands of other researchers, HBImed has already performed extensive research in this field and has defined parameters of quantitative electroencephalogram (QEEG) and components of event-related potentials (ERPs) as highly specific biomarkers for a variety of mental disorders.

Recent research shows that certain dysfunctions, such as ADHD, schizophrenia, OCD, depression, specific learning disabilities, and others are associated with specific patterns in spontaneous and evoked electrical potentials, recorded from the head by multiple surface electrodes, and that these spontaneous and especially the evoked electric potentials provide reliable markers of the brain function and dysfunction.

Measured data of spontaneous and evoked electrical potentials can be compared with data from a normative database (e.g. the Human Brain Index Reference Database (HBIRD)). By comparing the data by means of parametric statistical procedures the differences between the patients and their appropriate age-matched reference group can be calculated. This computer analysis then serves as a valuable tool in the aid of diagnosis and treatment planning.

For an article on QEEG, with a special focus on ADHD, by Prof. Juri Kropotov, a leading and worldwide renowned scientist in the field of quantitative EEG, evoked potentials, neurophysiology and neurotherapy, please visit the following link: New tools for diagnosis and modulation of brain dysfunction.

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