Biomarkers are used for a variety of purposes in medicine and research. They can help diagnose diseases, monitor their progression, predict treatment response, and even assess a person's risk of developing certain conditions.

Psychologists rely on psychometrics to assess personality, psychopathology, motivation, and learning disabilities. However, despite built-in lie scales, split-half designs, and a variety of other statistical manipulations, psychometric measurements still consist of behavioral data that is judged and reported by the individual themselves or by others.

The fifth, revised edition of„The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) was initially aimed at classifying mental disorders based on biological markers. The reserved reaction from the field and currently too many uncertainties prompted the developers to postpone the biomarker approach for the 6th revision. The new approach assumes that psychiatric diagnoses are not made solely on observable behavior, but also on knowledge of which brain system is impaired. The biomarker approach is almost certain to prevail because it creates objectivity and traceability. HBImed, like thousands of other researchers, has already conducted intensive research in this field and identified parameters of quantitative electroencephalography (QEEG) and components of evoked potentials (Event-Related Potentials – ERPs) can be defined as discrimination-capable biomarkers for various mental disorders.

Recent research shows that certain dysfunctions, such as ADHD, schizophrenia, obsessive-compulsive disorder, depression, specific learning disorders, and others, are associated with specific patterns of spontaneous and evoked electrical potentials recorded via multiple surface electrodes on the scalp, and that these spontaneous and especially evoked electrical potentials represent reliable markers of brain function and dysfunction.

Measurements 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 using parametric statistical methods, differences of patients from their corresponding age-adjusted reference group can be calculated. This computer analysis then serves as a valuable tool for diagnosis, therapy planning, and thus enabling personalized medicine.

For more information on QEEG, with a special focus on ADHD, here are two brief introductions:

• Andreas Müller: ADHD Biomarker for Diagnosis and Treatment
• Prof. Juri Kropotov: New tools for the diagnosis and modulation of brain dysfunction.

Do you have questions about ERP-based biomarkers or the HBI database? Then simply contact us!