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Previous neuroimaging studies have revealed abnormal brain networks in patients with major depressive disorder (MDD) in emotional processing. While any cognitive task consists of a series of stages, little is yet known about the topology of functional brain networks in MDD for these stages during emotional face recognition. To address this problem, electroencephalography (EEG)-based functional brain networks of MDD patients at different stages of facial information processing were investigated in this study. First, EEG signals were collected from 16 patients with MDD and 18 age-, gender-, and education-matched normal subjects when performing an emotional face recognition task. Second, the global field power (GFP) method was employed to divide group-averaged event-related potentials into different stages. Third, using the phase transfer entropy (PTE) approach, the brain networks of MDD patients and normal individuals were constructed for each stage in negative and positive face processing, respectively. Finally, we compared the topological properties of brain networks of each stage between the two groups using graph theory approaches. The results showed that the analyzed three stages of emotional face processing corresponded to specific neurophysiological phases, namely, visual perception, face recognition, and emotional decision-making. It was also demonstrated that depressed patients showed abnormally decreased characteristic path length at the visual perception stage of negative face recognition and normalized characteristic path length in the stage of emotional decision-making during positive face processing compared to healthy subjects. Furthermore, while both the MDD and normal groups’ brain networks were found to exhibit small-world network characteristics, the brain network of patients with depression tended to be randomized. Moreover, for patients with MDD, the centro-parietal region may lose its status as a hub in the process of facial expression identification. Together, our findings suggested that altered emotional function in MDD patients might be associated with disruptions in the topological organization of functional brain networks during emotional face recognition, which further deepened our understanding of the emotion processing dysfunction underlying MDD.

OBJECTIVE: We evaluated a variety of non-invasive physiological technologies and a series of test approaches for examination of aviator performances under conditions of mental workload in order to provide a standard real-time test for physiological and psychological pilot fatigue assessments. METHODS: Twenty-one male aviators were selected for a simulated flight in a hypobaric cabin with artificial altitude conditions of 2400 meter above sea level. The simulated flight lasted for 1.5 h, and was repeated for two times with an intervening 0.5 h rest period outside the hypobaric cabin. Subjective criteria (a fatigue assessment instrument [FAI]) and objective criteria (a standing-position balance test as well as a critical flicker fusion frequency (CFF) test) were used for fatigue evaluations. RESULTS: No significant change was observed in the FAI scores before and after the simulated flight, indicating that there was no subjective fatigue feeling among the participants. However, significant differences were observed in the standing-position balance and CFF tests among the subjects, suggesting that psychophysiological indexes can reflect mental changes caused by workload to a certain extent. The CFF test was the simplest and clearly indicated the occurrence of workload influences on pilot performances after a simulated flight. CONCLUSIONS: Results showed that the CFF test was the easiest way to detect workload caused mental changes after a simulated flight in a hypobaric cabin and reflected the psychophysiological state of aviators. We suggest that this test might be used as an effective routine method for evaluating the workload influences on mental conditions of aviators.