Conducted by researchers from the South China University of Technology and their international collaborators, the research was published in the journal Nature Biotechnology.

Antidepressants are widely prescribed to relieve depression, but their efficacy varies from person to person and there is a lack of quantitative biomarkers to assist personalized treatment of mental diseases.

The research team proposed a machine-learning algorithm to analyze a large EEG dataset and discovered the EEG signature that can predict the efficacy of antidepressants. Then they validated the signature in multiple datasets and explored the related neural mechanism.

Wu Wei, one of the researchers, told the newspaper that EEG is a low-cost and accessible tool and the research finding is expected to improve treatment plans and promote the personalized treatment of mental diseases.