Wenpeng Cai

This study established and implemented a multidimensional assessment protocol to systematically investigate neurobehavioral changes among 30 preliminary and backup members of the Antarctic inland expedition team undergoing rapid altitude training. The protocol integrates psychometric scales (BFI-44, DASS-21, PSQI), behavioral paradigms (N-back task), functional near-infrared spectroscopy (fNIRS), and wrist actigraphy to assess neurobehavioral adaptations across varying altitudes (0 m above sea level (a.s.l) / 3,700 m a.s.l / 4,300 m a.s.l) over an 8-day cycle. The core design comprises pre-ascent baseline testing; synchronized cognitive-fNIRS measurements at target altitudes; 24/8 sleep monitoring (including 8 h nocturnal actigraphy). This multimodal framework enables quantitative characterization of prefrontal compensatory activation, sleep fragmentation dynamics, and altitude-induced anxiety fluctuations. Findings reveal that, compared to Chinese normative data, participants exhibited significantly elevated agreeableness (t=3.940, P<0.001) and conscientiousness (t=9.736, P<0.001), alongside reduced neuroticism (t=-14.087, P<0.001). Acute hypoxia exacerbated anxiety (Z=-4.098, P<0.001), with greater severity in ethnic minority members (H=6.405, P=0.011). Actigraphy demonstrated altitude-dependent sleep fragmentation (WASO: 4,300 m a.s.l versus baseline, P=0.028). N-back tasks confirmed preserved working memory at 3,700 m a.s.l. (accuracy P=0.027) mediated by compensatory prefrontal activation (L-aPFC activation P=0.043). These data establish evidence-based selection criteria for polar science expeditions in high-altitude settings and delineate neuroplastic resilience thresholds under hypoxic stress.

This study established and implemented a multidimensional assessment protocol to systematically investigate neurobehavioral changes among 30 preliminary and backup members of the Antarctic inland expedition team undergoing rapid altitude training. The protocol integrates psychometric scales (BFI-44, DASS-21, PSQI), behavioral paradigms (N-back task), functional near-infrared spectroscopy (fNIRS), and wrist actigraphy to assess neurobehavioral adaptations across varying altitudes (0 m above sea level (a.s.l) / 3,700 m a.s.l / 4,300 m a.s.l) over an 8-day cycle. The core design comprises pre-ascent baseline testing; synchronized cognitive-fNIRS measurements at target altitudes; 24/8 sleep monitoring (including 8 h nocturnal actigraphy). This multimodal framework enables quantitative characterization of prefrontal compensatory activation, sleep fragmentation dynamics, and altitude-induced anxiety fluctuations. Findings reveal that, compared to Chinese normative data, participants exhibited significantly elevated agreeableness (t=3.940, P<0.001) and conscientiousness (t=9.736, P<0.001), alongside reduced neuroticism (t=-14.087, P<0.001). Acute hypoxia exacerbated anxiety (Z=-4.098, P<0.001), with greater severity in ethnic minority members (H=6.405, P=0.011). Actigraphy demonstrated altitude-dependent sleep fragmentation (WASO: 4,300 m a.s.l versus baseline, P=0.028). N-back tasks confirmed preserved working memory at 3,700 m a.s.l. (accuracy P=0.027) mediated by compensatory prefrontal activation (L-aPFC activation P=0.043). These data establish evidence-based selection criteria for polar science expeditions in high-altitude settings and delineate neuroplastic resilience thresholds under hypoxic stress.

BACKGROUND Although extensive research has investigated attentional biases based on the looming vulnerability model of anxiety, the characteristics of attentional biases in individuals with looming cognitive styles (LCS) remain incompletely elucidated. No prior eye-tracking studies have examined the spatiotemporal dynamics of their threat-related attentional preferences. AIM To investigate the nature and temporal pattern of attentional biases toward threat stimuli in individuals exhibiting different levels of LCS using eye-tracking technology. METHODS A total of 212 participants were stratified according to their Looming Maladaptive Style Questionnaire scores. From the high and low scoring subgroups, 35 participants were randomly selected for an eye-tracking experiment using a classic dot-probe paradigm featuring threat and neutral images. Four eye-tracking metrics, including first fixation latency, first fixation duration, total fixation duration, and fixation count, were analyzed to assess detection speed, attentional orienting, initial maintenance/avoidance, and overall engagement. RESULTS Distinct attentional bias patterns were observed between high and low LCS groups. High LCS individuals exhibited a vigilance-avoidance pattern characterized by initial vigilance toward threat stimuli (evidenced by faster detection and preferential orienting), followed by attentional avoidance, alongside sustained attention maintenance to threat. CONCLUSION These findings reveal a temporal dissociation between early vigilance and later avoidance during threat processing in high LCS individuals, providing novel empirical evidence to refine models of cognitive vulnerability and attentional dynamics in threat perception.

BACKGROUND As a substitute for traditional drug therapy, digital cognitive-behavioral therapy positively impacts the regulation of brain function, which can improve insomnia. However, there is currently a paucity of studies on digital cognitive behavioral therapy as a treatment for insomnia. AIM To assess digital cognitive behavioral therapy for insomnia regarding its positive impact on brain function. METHODS Participants were randomly assigned to either a go/no-go group or a dot-probe group. The primary outcome was quality of sleep as assessed by the actigraphy sleep monitoring bracelet, Pittsburgh sleep quality index (PSQI), insomnia severity index (ISI), and depression anxiety and stress scale (DASS-21). RESULTS Eighty patients were included in the analysis (go/no-go group: n = 40; dot-probe group: n = 40). We combined the total scale scores of the two groups before and after the intervention in the analysis of covariance. Our study explored whether insomnia symptoms in both groups can be improved by using digital cognitive behavioral therapy instead of trying to compare the two trials; therefore, only one P value is listed. In both groups, we found a short-term time effect on insomnia symptom severity (PSQI: P < 0.001, η 2 = 0.336; ISI: P < 0.001, η 2 = 0.667; DASS-depression: P < 0.001, η 2 = 0.582; DASS-anxiety: P < 0.001, η 2 = 0.337; DASS-stress: P < 0.001, η 2 = 0.443) and some effect on sleep efficiency (but it was not significant, P = 0.585, η 2 = 0.004). CONCLUSION Go/no-go task training of inhibitory function had a short-term positive effect on sleep efficiency, whereas dot-probe task training had a positive short-term effect on emotion regulation.

Anxiety is known to significantly impair cognitive function, particularly attentional control. While exercise has been demonstrated to alleviate these cognitive deficits, the precise neural mechanisms underlying these effects remain poorly understood. This study examines the effects of exercise on attentional control in individuals with high trait anxiety, based on attentional control theory, which suggests that such individuals have reduced top-down attention. Thirty-eight participants were randomly assigned to either an exercise group or a reading group. The exercise group engaged in 30 min of moderate-intensity cycling, while the reading group spent 30 min reading quietly. In Experiment 1, goal-directed attention was assessed using a cue-object paradigm, and in Experiment 2, inhibitory control was evaluated through a visual search task. EEG data indicated that the exercise group exhibited significantly larger Pd components in both experiments, suggesting enhanced attentional focus and improved inhibition of distractors. These findings suggest that aerobic exercise enhances top-down attentional processes, particularly goal-directed attention and distractor inhibition, offering potential as an intervention for individuals with high trait anxiety.

Polysomnography (PSG) is commonly used to diagnose sleep disorders. However, manual sleep staging is a time-consuming task due to high human effort and technical thresholds, and it involves certain subjective factors. To improve the efficiency of sleep staging, this paper proposes a deep learning automatic sleep staging method based on multidimensional sleep data, the MCSSN model. This model uses continuous wavelet transform (CWT) to first extract sleep features, followed by data enhancement of time-frequency features using the SMOTE algorithm. Finally, a two-step training algorithm is used to learn the sleep features and sleep state transition rules. The evaluation results show that the model achieved an excellent overall accuracy of 85.87% on a sample of 104 subjects, with a macro average score ( F _1M ) of 0.82 and a Kappa of 0.80. The model achieved excellent classification performance for N1 stage detection, with an F1 of 0.64, outperforming the other models. The experimental results show that the SMOTE oversampling algorithm plays an active role in detecting sleep stages, especially the N1 stage, which is difficult to identify. In addition, learning sleep transition rules through a two-step training algorithm helps to improve the performance, and the MCSSN algorithm provides a reference for the automatic design of subsequent sleep classification networks.

Background: Suicide is the fourth leading cause of death among young individuals, with the number of suicide-related fatalities escalating annually, which gets widespread concern worldwide. A substantial body of evidence suggests that suicidal ideation serve as a crucial predictive factor of suicidal actions. In particular, individuals are vulnerable to develop negative cognitions, suicidal ideation and subsequent suicidal behavior following an acute stressful event. The objective of this study is to examine the correlation between emotions and suicidal ideation in a youthful population before and after a stressful event. Methods:The psychological status and suicidal ideation of the group were conducted by adopting a whole group sampling method before and after the acute stressful event. The data were analyzed utilizing SPSS Version 26 (IBM, Illinois, USA), including the Spearman correlation analysis, meditating effect analysis, the binary logistic regression analysis. Results: The findings demonstrated that individuals with suicidal ideation exhibited higher levels of stress perception, depression and anxiety compared to those without suicidal ideation at all times. Comparing to the results of daily screening, the mediating effect of depression between stress and suicidal ideation was significantly more pronounced (53.11% - 79.66%) in the group following the stressful event, while the mediating effect of anxiety was smaller (33.48% - 31.03%). Logistic regression analysis revealed that depression subsequent to a stressful event increased the risk of suicidal ideation (OR: 1.74). The results of the logistic regression analysis corroborated the alterations in the mediating effects, suggesting that depression play a more crucial role in prompting suicidal ideation after a stressful event. Conclusions:The findings offer an enhanced and refined theoretical foundation for both crisis and clinical interventions, providing greater efficacy and specificity.