Ketamine, a drug that blocks NMDA receptors and is thought to boost neuroplasticity, increased whole-brain EEG signal complexity during infusion in patients with major depressive disorder (MDD), most of whom had treatment-resistant depression. Higher complexity at the end of infusion predicted less symptom improvement the next day, while lower occipital complexity before treatment predicted a favorable response. A logistic model using occipital complexity had moderate predictive accuracy. No changes were seen in a different complexity measure, suggesting it is not useful as a biomarker. Occipital EEG complexity may help predict which patients will benefit from ketamine therapy.
Ketamine, a rapid-acting antidepressant for treatment-resistant depression, may work by altering the brain's excitation-inhibition balance, measurable via the aperiodic exponent of EEG power spectra. In a placebo-controlled trial of 24 patients with major depressive disorder, ketamine infusion significantly reduced the aperiodic exponent across the scalp. Patients who responded to treatment had steeper pretreatment occipital aperiodic exponents, which predicted better outcomes. A meta-analysis within the study revealed substantial variability in ketamine's effect on this measure. The occipital aperiodic exponent may serve as a biomarker for predicting antidepressant response, but further large-scale studies are needed.