The role of frontal EEG in predicting clinical response of major depressive disorder to intranasal ketamine and esketamine.
Journal of affective disorders – November 22, 2025
Source: PubMed
Summary
Brainwave patterns may predict who responds to rapid-acting depression treatments. Researchers found that specific frontal EEG biomarker patterns, like increased functional connectivity and decreased Entropy, before treatment, successfully identified individuals with Depression who would benefit from Ketamine or Esketamine. These distinct brain signals offer a promising way to personalize care, highlighting the potential of EEG to guide effective treatment for depression.
Abstract
Ketamine and its enantiomer esketamine are NMDA receptor antagonists that have shown consistent antidepressant effects in major depression disorder (MDD). These effects suggest an active role of glutamate in the pathophysiology of depression. It has been hypothesized that acute increase of glutamate neurotransmission in the prefrontal cortex following treatment with (es)ketamine leads to synaptic plasticity and neurotrophic changes with following influence on theta activity of encephalography (EEG). The present retrospective study included a total of 43 patients affected by MDD and treated with either esketamine or ketamine. EEG recordings before treatment were related to clinical outcome as measured by both a self-rating and a rater-based psychometric scale. EEG measures were considered as possible predictive biomarkers for responsivity of MDD to (es)ketamine. In particular, we utilized phase locking value (PLV), phase lag index (PLI), Renyi and Tsallis entropy, as well as aperiodic spectral parameters (offset and decay exponent) by focusing on the frontal region and theta band. We found increased functional connectivity (PLI and PLV) and decreased entropy in responders to (es)ketamine compared to non-responders. Although, we did not find a predictive effect of aperiodic spectral parameters, we observed decreased values in responders compared to non-responders. Our results emphasize the role of frontal EEG as possible biomarker [area under the ROC curve of 0.7065 (Renyi entropy), 0.7101 (Tsallis entropy) and 0.7283 (PLI)] in predicting antidepressant effects of (es)ketamine.