Evaluating the efficacy of three classical EEG paradigms in the discrimination of bipolar depression.

Objective: Given the lack of consensus regarding the optimal EEG paradigm for identifying bipolar depression (BD), this study sought to systematically evaluate the efficacy of three classic EEG paradigms-eyes open, eyes closed, and free viewing-in diagnosing BD.

Methods: EEGs were collected from 28 individuals diagnosed with BD and 42 healthy controls(HCs) across three experimental conditions: eyes closed, eyes open, and free viewing. Sociodemographic data and neuropsychological testing were also collected. This research investigated notable variations in brain functional connectivity between the two groups across paradigms, the correlation of features with neuropsychological assessments, and classification outcomes.

Results: The results demonstrated that under the eyes-closed paradigm, significant differences in the Phase Lag Index (PLI) were consistently observed across the δ, θ, β, and γ frequency bands. This paradigm also featured the highest number of electrodes significantly correlated with cognitive scales. Furthermore, the eyes-closed condition achieved the highest accuracy in bipolar depression recognition, with the Random Forest classifier yielding the highest accuracy of 79.43% and an F1 score of 76.82%. These findings underscore the eyes closed paradigm as a superior, straightforward EEG experimental approach for the diagnosis of bipolar depression.

Conclusions: This study indicates that the eyes closed experimental paradigm more effectively demonstrates the electrophysiological disparities between patients with BD and HCs, in comparison to the eyes open paradigm and the action observation-based free viewing paradigms, as determined through the analysis of various outcome metrics.