Baseline EEG Temporal Dynamics as a Thalamic Filter State Biomarker: A Thalamic Filter Model Account of Ketamine Antidepressant Response Prediction and Depression as Thalamic Over-Filtering
Zenodo (CERN European Organization for Nuclear Research) April 27, 2026 Ryan Malone
A new mechanistic model called the Thalamic Filter Model (TFM) proposes that depression may involve chronically elevated inhibitory tone in the thalamic reticular nucleus, which narrows conscious bandwidth and produces cognitive rigidity and rumination. Ketamine's rapid antidepressant effect may work by temporarily reducing this thalamic over-filtering. Baseline EEG features—including vigilance stage distribution and spectral dynamics—predict ketamine response in treatment-resistant depression. A review of six independent EEG biomarker studies (total n > 200) found that lower baseline vigilance, lower gamma power, and higher alpha power all predict better response, consistent with the model's prediction that higher baseline filter impedance predicts greater benefit. The model generates three falsifiable predictions and proposes lag-1 autocorrelation as a practical baseline biomarker.