Enhancing emotion regulation: investigating the efficacy of transcutaneous electrical acupoint stimulation at PC6 in reducing fear of heights.

This study investigated the impact of transcutaneous electrical acupoint stimulation (TEAS) at Neiguan acupoint (PC6) on the physiological and behavioral responses of participants exposed in virtual height. 40 participants were included in the study and were randomly assigned to either a control group or an intervention group. Participants had an immersive experience with a VR interactive platform that provided somatosensory interaction in height stimulation scenes. Psychological scores, behavioral and cognitive performance, and physiological responses were recorded and analyzed. The results indicated that the intervention group had significantly lower fear scores compared to the control group. Analysis of heart rate variability revealed that the intervention group exhibited improved heart rate variability, indicating enhanced cardiovascular function and emotion regulation. The behavioral and cognitive results demonstrated that the intervention group exhibited higher left eye openness, faster reaction times, and greater movement distance, suggesting enhanced attentional focus, cognitive processing, and reduced avoidance behaviors. These findings suggest that TEAS at PC6 can effectively reduce fear and improve the regulation of physiological and behavioral responses to negative emotional stimuli.

Acute combined effects of concurrent physical activities on autonomic nervous activation during cognitive tasks.

Backgrounds: The validity of heart rate variability (HRV) has been substantiated in mental workload assessments. However, cognitive tasks often coincide with physical exertion in practical mental work, but their synergic effects on HRV remains insufficiently established. The study aims were to investigate the combined effects of cognitive and physical load on autonomic nerve functions. Methods: Thirty-five healthy male subjects (aged 23.5 ± 3.3 years) were eligible and enrolled in the study. The subjects engaged in n-back cognitive tasks (1-back, 2-back, and 3-back) under three distinct physical conditions, involving isotonic contraction of the left upper limb with loads of 0 kg, 3 kg, and 5 kg. Electrocardiogram signals and cognitive task performance were recorded throughout the tasks, and post-task assessment of subjective experiences were conducted using the NASA-TLX scale. Results: The execution of n-back tasks resulted in enhanced perceptions of task-load feelings and increased reaction times among subjects, accompanied by a decline in the accuracy rate (p < 0.05). These effects were synchronously intensified by the imposition of physical load. Comparative analysis with a no-physical-load scenario revealed significant alterations in the HRV of the subjects during the cognitive task under moderate and high physical conditions. The main features were a decreased power of the high frequency component (p < 0.05) and an increased low frequency component (p < 0.05), signifying an elevation in sympathetic activity. This physiological response manifested similarly at both moderate and high physical levels. In addition, a discernible linear correlation was observed between HRV and task-load feelings, as well as task performance under the influence of physical load (p < 0.05). Conclusion: HRV can serve as a viable indicator for assessing mental workload in the context of physical activities, making it suitable for real-world mental work scenarios.

Disrupted properties of functional brain networks in major depressive disorder during emotional face recognition: an EEG study via graph theory analysis.

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.

Standard low-resolution electromagnetic tomography imaging of brain for the analysis of mental fatigue during a simulated air traffic control task.

BACKGROUND: Standard low-resolution electromagnetic tomography (sLORETA) was used to accurately detect EEG changes in mental fatigue of air traffic controllers (ATCo) under a simulated air traffic control (ATC) task. We explored the changes in standard current density, activated cortical intensity, and brain source location. METHODS: The participants were instructed to use the tower flight command simulation training system for three hours of uninterrupted ATC task. The 3-hour EEG signal was divided into four stages: task start, 1st hour, 2nd hour, and task end. Each stage was preprocessed for 3 minutes to explore the EEG changes and then processed by sLORETA in a statistical non-parametric mapping analysis. RESULTS: The current density distribution of δ and α oscillations differed significantly during the four tasks, while θ, ß and γ oscillations did not. Changes in δ oscillations of the brain during mental fatigue were detected mainly in the postcentral gyrus (BA2 and BA3), precentral gyrus (BA4 and BA6), inferior temporal gyrus (BA20), and superior temporal gyrus (BA38). The α oscillations were found mainly decreased in the postcentral gyrus (BA2) and inferior parietal lobule (BA40) when the task was in progress compared with the end of the task. CONCLUSION: The superior temporal gyrus and somatosensory cortex were the main activated cortical regions during the simulated ATC task. The α and δ oscillations showed contrasting activity during simulated ATC task, which might reflect the release of task-relevant brain's areas from inhibition and enhance the neural activity.

Posturographic Balance's Validity in Mental and Physical Fatigue Assessment Among Cadet Pilots.

BACKGROUND: Postural control is adversely affected by mental and physical fatigue, but its validity in fatigue assessment has not been investigated systemically among pilots. We explored the correlations of posturographic balance with physiological and psychological signals among cadet pilots.METHODS: In experiment 1, 37 cadet pilots performed a posturographic balance test, heart rate variability (HRV), and profile of mood states (POMS) during 40 h of sleep deprivation. For experiment 2, physiological signals of 60 subjects, including breathing rate (BR), systolic blood pressure (SBP), and heart rate (HR) were measured under the effects of physical fatigue. Then correlations with a mental and physical fatigue index based on effective posturographic parameters with those subjective and objective methods were analyzed by linear regression.RESULTS: The mental fatigue index correlated linearly with the depression score of the POMS (r = 0.212), standard deviation of normal to normal beats (r = 0.286), and square root of the mean differences of successive beat intervals (r = 0.207). Meanwhile, linear correlations with frequency-domain parameters of HRV such as total power, low frequency power, and high frequency power were also statistically significant. With the increase in the physical fatigue index, physiological signals such as SBP (r = 0.300), HR (r = 0.349), and BR (r = 0.266) increased linearly.CONCLUSIONS: Impairment of postural stability can reflect the aggravation of mental and physical fatigue among cadet pilots, which provides a potential method for assessing fatigue level before flight tasks and preventing errors by pilots.Cheng S, Sun J, Ma J, Dang W, Tang M, Hui D, Zhang L, Hu W. Posturographic balance's validity in mental and physical fatigue assessment among cadet pilots. Aerosp Med Hum Perform. 2018; 89(11):961-966.