<p>Depression is a highly prevalent mental disorder that impacts an individual’s functioning, societal productivity, and quality of life. It is associated with disrupted neural activity (e.g., balance of excitation-inhibition) across networks implicated in emotional processing, such as between prefrontal and limbic regions. Gamma and beta activity measured with electroencephalography (EEG) differ between healthy individuals and those with depression, and predict treatment outcomes following pharmacological intervention. However, to date research has focussed on binary comparisons between individuals with a clinical depression diagnosis relative to healthy control populations, providing limited insight into how these measures may shift as a function of illness severity. To establish the utility of EEG measures as potential biomarkers for depression, an improved understanding across the spectrum of symptom profiles is required. Here, we aimed to bridge this gap and investigate changes in beta and gamma power and the 1/f slope in resting-state EEG across a spectrum of mild to severe depression symptom presentations. In line with expectations, we demonstrate graded alterations to gamma and beta power and the 1/f slope across a spectrum of depression severity. Our findings provide critical new insights into the neurophysiological signature of depression symptoms, and highlight the utility of EEG markers to inform future precision psychiatry approaches to more effectively assess and treat depression.</p>