A Systematic Review of EEG Predictors and Correlates of Psilocybin’s Treatment in Depression

Background: Major depressive disorder (MDD) affects over 280 million people globally and remains a leading cause of disability. Psilocybin has emerged as a promising treatment, with evidence suggesting modulation of neural oscillatory activity relevant to mood regulation. Electroencephalography (EEG) and magnetoencephalography (MEG) offer non-invasive methods for evaluating these neurophysiological changes.

Objectives: This systematic review pursues two distinct

Aims: (1) to characterise the neurophysiological effects of psilocybin on neural oscillatory activity as measured by EEG and MEG; and (2) to evaluate whether EEG/MEG biomarkers function as correlates of antidepressant efficacy or as predictors of treatment response, clearly distinguishing between these two roles.

Methods: A systematic search of PubMed and Google Scholar identified seven eligible studies published between 2013 and 2025. Studies were required to include adult participants with MDD or healthy volunteers undergoing psilocybin administration with EEG or MEG recording. Findings were synthesised narratively and organised into three conceptual categories: neurophysiological effects, correlates, and predictors.

Results: Seven studies comprising 204 participants were included. Critically, only 20 participants carried a confirmed MDD diagnosis; the remainder were healthy volunteers, which substantially limits the generalisability of clinical conclusions. Psilocybin consistently reduced alpha-band power, increased gamma synchronisation, and enhanced evoked theta activity. Post-treatment evoked theta power was significantly correlated with symptom reduction, representing the strongest treatment correlate identified. No pre-treatment predictive biomarkers were identified.

Conclusions: EEG and MEG capture consistent neurophysiological effects of psilocybin and show early promise as correlate biomarkers of treatment response. However, the evidence base remains limited by small MDD-specific samples, heterogeneous methodology, and an absence of validated predictive biomarkers. Larger, standardised clinical trials with pre-treatment EEG baselines are needed before EEG can be applied predictively in clinical practice.