Abnormal Symbolic Transfer Entropy in Depression

Abstract

Depression is a mental illness and considered the main cause of disability worldwide. Further study is still needed to enhance the accuracy of depression detection. The aim of this study was to explore the potential EEG biomarker for cortical dysfunction to help the diagnosis with depression clinically. In this study, symbolic transfer entropy (STE) of five sleep periods (Wake, REM, N1, N2, N3) and four frequency bands (δ, θ, α, β) were obtained from six sleep EEG channels. Significant differences between the two groups were found. The average STE values in the patients with depression were lower than those of normal participants in all sleep periods and frequency bands. These findings indicated the lower complexity of brain and abnormalities in sleep cortical activity in patients with depression. It may provide insights into the influence of depression on cognitive function and important indicators for studying depression pathological mechanisms.