Enhancing Psychiatric Drug Development and Clinical Care with Quantitative Tomographic Electroencephalography Neural Signatures Tracking

Neuroscience is driving a transformative shift in psychiatry, with brain neuroimaging at the forefront of personalized medicine. This poster presents preclinical and clinical approaches to track and analyze the neural signatures of psychiatric conditions over time using platform-based quantitative tomographic electroencephalography (qEEGt). Using minimally invasive ‘snapshot EEG’ rapid ‘brain current source density maps’ and ‘brain functional connectivity maps’ are generated, reflecting network measures of brain activity and synaptic plasticity. We include here a step-by-step summary of qEEGt methods (i.e., swLORETA source localization) and present AI-informed algorithms to predict the contribution of 19 key neurotransmitters to a patient’s EEG brain patterns.

We present a clinical case study showcasing how individualized tracking of qEEG data can guide treatment decisions in cases with multiple diagnoses. Our qEEGt results showed global alpha and beta band dysregulation and an abnormal contribution of serotonin to this pattern, which supported an informed approach to prescribing serotonergic medication. A second example is presented highlighting the value of qEEGt during a clinical trial with a psychiatric compound targeting depression, in identifying a pharmacologic effect under the threshold of behavioral biomarkers. In this case qEEGt had the resolution to discern subtle effects on the brain network and detect a dose relationship.

This novel multivariate platform approach places electrophysiological and molecular relationships at the center of personalized psychiatric care and provides a powerful tool for optimizing therapeutic outcomes and reducing trial-and-error prescribing.