Neuroscientist Leslie S. Prichep discusses in DATAI how quantitative analysis of brain electrical activity allows for the identification of subtypes in psychiatric disorders.
09 | 03 | 2026
The Institute for data Science data Artificial Intelligence (DATAI) at the University of Navarra hosted a new session of its external seminar program with the participation of neuroscientist Leslie S. Prichep, researcher and scientific director of BrainScope Company, recognized for her contribution to development quantitative methods in brain activity analysis.
In his presentation, entitled "Neurophysiological subtyping in psychiatric disorders," Prichep explained how electroencephalography (EEG), a technique that records the brain's electrical activity using electrodes placed on the scalp and forehead, can then be analyzed using advanced statistical methods to obtain more accurate information about brain function. This approach, known as quantitative electroencephalogram (qEEG), allows a tool interpreted visually to be transformed into a data analysis system.
During the seminar, the researcher reviewed the fundamentals of the neurometric method, developed over decades of work the Brain Research Laboratory of research at the New York UniversitySchool Medicine (NYU SOM). This method compares a patient's brain recordings with reference letter data reference letter from healthy individuals, taking into account variables such as age. By comparing the patient's brain activity with these "normal" values, it is possible to detect deviations in the brain's electrical patterns that could be associated with various neurological disorders.
Prichep highlighted that EEG offers a core topic advantage core topic other neuroimaging techniques: its high temporal resolution, capable of recording neuronal activity on a millisecond scale. This allows for highly accurate study of the dynamics of neural networks. Based on these signals, different characteristics of the brain can be analyzed, such as connectivity between regions, the complexity of neural networks, or the frequency patterns of electrical activity, which are relevant indicators for understanding brain dysfunction.
As he explained, these measures can subsequently be used in classification models that help identify neurophysiological subtypes within the same psychiatric disorder, a core topic step core topic more accurate diagnoses and personalized treatments.
Currently, Prichep continues to develop clinical applications for these technologies at Wave Neuroscience and BrainScope Company, where he works on tools for the assessment of brain injuries and other neurological disorders.
The session is part of DATAI's external seminar program, an initiative that brings the research community up to speed on the latest advances in data science, artificial intelligence, and their application in fields such as health.