Mental fatigue, a prevalent yet underestimated state, impairs cognitive performance and increases the risk of errors and accidents, creating persistent challenges in occupational and clinical contexts. While rest is commonly used for recovery, its benefits are context-dependent and typically short-lived. Acute aerobic exercise has shown promise in alleviating cognitive impairments, yet the neural mechanisms distinguishing exercise and rest, as well as their recovery effects during interventions, remain unclear. In this study, a within-subject design was employed with three prolonged psychomotor vigilance task (PVT) sessions: one with mid-task exercise, one with passive rest, and one as a no-intervention control. EEG-derived functional networks were constructed and analyzed to characterize immediate, carryover, and recovery effects across task and intervention periods. Both interventions elicited immediate behavioral improvements but induced divergent frequency-specific network reorganization. During task reengagement, exercise exhibited a state of functional integration characterized by reduced [Formula: see text]-band local efficiency and sustained [Formula: see text]-band global efficiency, whereas rest displayed network segregation. Recovery analyses revealed that exercise modulated distributed [Formula: see text]-band connectivity, with discriminative frontal features reliably distinguishing recovery pathways. Despite similar behavioral outcomes between exercise and rest, acute exercise uniquely sustained network integration distinct from the topological segregation observed during rest, highlighting its potential for fatigue regulation under cognitively demanding contexts from a brain network perspective.

Background:: Sleep deprivation (SD) is a common occupational hazard, particularly for shift workers like nurses, leading to significant impairments in cognitive functions such as sustained attention and working memory. High-frequency repetitive transcranial magnetic stimulation (rTMS) is a promising neuromodulation technique for cognitive enhancement, but its effects in sleep-deprived individuals and the underlying neural mechanisms remain poorly understood. This study aimed to investigate the efficacy of high-frequency rTMS over the left dorsolateral prefrontal cortex (DLPFC) in modulating sustained attention and working memory after a night shift and to explore the associated changes in brain network topology. Methods:: In a within-subject design, 28 healthy female night-shift nurses participated in two experimental sessions after a night of work: one with real 5 Hz rTMS and one with sham rTMS applied to the left DLPFC. Following stimulation, participants performed a psychomotor vigilance task (PVT) and a 2-back task while their electroencephalography (EEG) data were recorded. Behavioral performance (reaction time and accuracy) and subjective fatigue were assessed. Graph theory analysis was applied to the EEG data to evaluate changes in functional brain network topology at both global and nodal levels. Results:: Real rTMS significantly reduced subjective mental fatigue compared to sham stimulation. However, the behavioral effects were task-dependent. For the 2-back task, real rTMS led to a significant impairment in performance, characterized by slower reaction times and lower accuracy. For the PVT, there was a non-significant trend towards improved performance. These behavioral outcomes were mirrored by distinct patterns of network reorganization. During the PVT, real rTMS induced decreased functional segregation (lower clustering coefficient and local efficiency) in the alpha band. Conversely, during the 2-back task, it resulted in increased functional segregation and small-worldness in the theta band. Conclusion:: High-frequency rTMS over the left DLPFC exerts differential, task-specific effects on cognitive function in a sleep-deprived state. The impairment in working memory, despite a network configuration theoretically supportive of local processing, likely results from an inverted-U effect, where the rTMS pushed an already strained and compensating brain system past its optimal level of cortical excitability. The findings highlight the critical role of both baseline brain state and specific cognitive demands in determining the outcomes of neuromodulation, providing crucial insights for the targeted application of rTMS to mitigate cognitive deficits from sleep deprivation.

In Moyamoya syndrome (MMS), cerebral perfusion and tissue microstructure are impaired, but regional differences remain unclear. This study analyzed 22 adult MMS patients using CT perfusion (CTP) and intravoxel incoherent motion (IVIM). All hemispheres were classified into four ischemia grades based on symptoms and imaging. CTP parameters (CBF, CBV, MTT, TTP) and IVIM parameters (ADC, D, D*, f) were measured in the temporal lobe and basal ganglia. The relative values of CTP parameters and absolute values of IVIM parameters were compared across hemispheres with different ischemia grades. Additionally, correlation analyses were conducted between CTP and IVIM parameters. Results showed that in the temporal lobe, rMTT and rTTP were significantly increased ( p = 0.018 and 0.002, respectively) with higher ischemia grades, while basal ganglia changes were similar but milder, with only rTTP delay being significant ( p = 0.011). IVIM analysis revealed significantly elevated ADC values in association with higher ischemia grades (overall p = 0.011). Additionally, significant variations were observed in both D* (overall p = 0.041) and the perfusion fraction f (overall p = 0.043). In the basal ganglia, IVIM parameters showed no significant differences across ischemia grades. Weak or insignificant correlations were found between IVIM parameters and CTP parameters. The study suggested that perfusion and microstructural damage in the basal ganglia were less severe than in the temporal lobe, and that IVIM offers insights into microvascular status that are complementary to those from hemodynamic perfusion imaging.

To mitigate the economic losses and safety risks caused by reduced alertness of individuals in the context of an aging workforce, mental fatigue among the elderly is an issue worthy of in-depth exploration. Despite convergent studies on cognitive aging, the differential alterations in brain network topology between the elderly and young individuals during vigilance decline remain unclear. Here, a prolonged 30-min psychomotor vigilance task (PVT) was employed to induce mental fatigue, where both behavioral performance and electroencephalography (EEG) data were collected from healthy elderly (n =30) and young participants (n =40). Subsequently, EEG functional connectivity was constructed and the differences in network topological properties between the two groups were quantitatively evaluated based on global and nodal metrics. Both groups an exhibited age-independent significant decline in behavioral performance with time on task. Moreover, age-related dysconnectivity pattern was revealed over a wide frequency range ( $1-45$ Hz) in the elderly group, which further developed toward less optimal network architecture. Specifically, significant deficits in nodal efficiency were revealed in most of the brain regions, and the frontal area exhibited significant age-by-time interaction effect, which was attributed to a significant decline in the elderly group. Statistically significant correlation between behavioral and network metrics was also found. Overall, our results provide some of the first quantitative insights for revealing the neural mechanisms of age differences during mental fatigue, which may contribute to the rational arrangement of personnel in real-world scenarios with high alertness demands.

For the apparent importance of mental fatigue in neuroergonomics, continuous efforts have been made to reveal the underlying neural mechanisms. Using concurrent EEG-fMRI network analysis, this work aims to reveal fatigue-related brain network reorganization. Specifically, multimodal neuroimaging data were acquired from 35 healthy participants during a 15-min sustained attention task (i.e., psychomotor vigilance task). A monotonically decreasing pattern of behavioral performance was revealed where the first and last 3-min windows were determined as the most vigilant and fatigued states. Multimodal brain network architectures within these two states were then quantitatively compared. We found that EEG and fMRI networks exhibited divergent yet interrelated reorganizations. Specifically, MF-related deficiency in parallel information transmission was revealed in multiple EEG frequency bands, yet only local efficiency was altered in fMRI networks. Moreover, a convergent decrease of nodal efficiency mainly resided in the default mode network was found in both EEG and fMRI networks, indicating a decline in cognitive control capacity during mental fatigue. Overall, by integrating multimodal EEG-fMRI network analyses, this work provides novel insights into the dynamic neural adaptations to mental fatigue, enhancing our understanding of the underlying neural mechanisms.

Background: Night-shift nurses experience chronic sleep deprivation, which impairs cognitive functions crucial for patient safety. However, the underlying reorganization of brain functional networks remains poorly understood. This study aimed to investigate the task-specific effects of sleep deprivation on brain network topology during sustained attention and working memory in night-shift female nurses. Methods: In a within-subjects design, electroencephalography (EEG) data from 28 female nurses were recorded during a rested session (R-Session) and a sleep-deprived session (SD-Session) immediately following a night shift. Participants performed the psychomotor vigilance test (PVT) and 2-back tasks. Functional connectivity was estimated using the weighted phase lag index (wPLI), and brain network properties were quantified using graph theoretical analysis at both global and nodal levels. Results: Our findings revealed a clear behavioral dissociation: sleep deprivation significantly impaired PVT performance but had no effect on 2-back task performance. This dissociation was mirrored by distinct patterns of neural reorganization. During the PVT, the brain network exhibited a compensatory enhancement of global topology, characterized by a significant increase in clustering coefficient, global efficiency, local efficiency, and small-worldness, alongside a decrease in characteristic path length, particularly in the theta and beta bands. In contrast, the 2-back task showed only a localized increase in the theta-band clustering coefficient. Nodal analysis further revealed a critical topographical distinction: PVT-related efficiency changes were strongly right-lateralized, whereas 2-back changes were bilaterally distributed. Conclusion: In conclusion, these results demonstrate that sleep deprivation elicits task-specific neurocognitive adaptations. Sustained attention appears highly vulnerable, prompting a broad compensatory reorganization of the right-hemispheric attention network. Conversely, working memory function remains behaviorally stable, underpinned by a more specific network reorganization, primarily involving increased local connectivity. This study deepens our understanding of the neural mechanisms underlying cognitive vulnerability and resilience in nurses group.

Deep brain stimulation (DBS) targeting the nucleus accumbens (NAc) is a promising therapeutic intervention for treatment-resistant neuropsychiatric disorders such as depression, anxiety, and addiction. However, the molecular mechanisms underlying the clinical efficacy of NAc DBS remain largely unknown. One approach to address this question is by performing spatial gene expression analysis on cells located in different regions of the same circuit following NAc DBS. In this study, we utilized high-resolution spatial transcriptomics (Stereo-seq) to investigate gene expression changes induced by NAc DBS in the mouse brain. Mice were randomly allocated to receive continuous electrical stimulation (0.1 mA, 130 Hz) or sham treatment (electrode implanted, no electrical stimulation given) for one week, and subsequent Stereo-seq analysis identified differentially expressed genes (DEGs) across various brain regions. Functional enrichment analysis highlighted changes in synaptic and neuroplasticity processes as well as stress and inflammatory responses in the NAc circuit. Single-cell resolution mapping further identified key molecular players, including Nlgn1, Snca, Pde10a, and Syt1, particularly in glutamate receptor-expressing neurons in the NAc. These genes are critical for synaptic plasticity and neurotransmitter release, and have been implicated in various psychiatric disorders. These findings shed light on the molecular underpinnings of NAc DBS and provide insights into its therapeutic potential in modulating neural circuits associated with neuropsychiatric disorders.

Substantial inter-individual differences in behavioral performance were repeatedly revealed during prolonged time-on-task (TOT), indicating complex neural mechanisms underlying mental fatigue. In this work, we provide a comprehensive investigation to identify individuals with high susceptibility to mental fatigue and to reveal its influence on brain network reorganization. Specifically, behavioral data and EEG signals were collected from 95 participants when they performed a 20-min psychomotor vigilance task (PVT). A composite index (Findex) was introduced, based upon which the participants were categorized into the fatigue-susceptible (FS, corresponding to top third Findex value) and the fatigue-resistant (FR, corresponding to bottom third Findex value) groups (NFS/NFR = 30/30). Functional connectivity was then estimated and set as input for the following analyses. As expect, significant impairment of behavioral performance was showed in the FS group, while the performance of the FR group remained relatively stable. Subsequent brain network analyses showed frequency-dependent reorganizations in both groups, whereas the FR group exhibited greater stability and higher integrity than the FS group. Further classification analyses revealed satisfactory accuracy for FS identification (95.61%) and the prominent centro-parietal distribution of contributing nodal features. In sum, this study provides further evidence to support the notion of substantial individual differences in fatigue susceptibility and provides a practical approach to identify the individuals whose performance is particularly prone to performance decline.

Introduction:Mental fatigue, resulting from prolonged cognitive tasks or sleep deprivation, significantly impacts safety and performance, particularly in high-risk environments. However, effective intervention methods are limited, highlighting the urgent need for new approaches to alleviate mental fatigue. This study explores the effectiveness of Autonomous Sensory Meridian Response (ASMR) as a novel intervention for alleviating mental fatigue. Methods:A within-subject design was employed in this work, where 28 healthy young subjects (M/F = 17/11, age = 21.82 ± 0.37 years) were requested to perform a continuous 30 min sustained attention task (named No-Break session) and a 30 min task with a 4-min mid-task ASMR break (named ASMR-Break session) at a counterbalanced order. The immediate effect and general effect of ASMR were quantitatively assessed on behavioral performance and EEG characteristics. Results:Behaviorally, only significant immediate effect was revealed as showing in reduced reaction time. Further interrogation of brain dynamics showed complex patterns of spatio-spectrum alterations and an interaction in small-world metric in theta band. Specifically, the ASMR intervention prevented an increase in small-worldness, and the correlation between changes in small-worldness and reaction times diminished after the intervention. Discussion:In sum, this preliminary investigation provides insight into ASMR's neural mechanisms and suggests it may help attenuate fatigue. Further research in larger, more diverse samples will be necessary to confirm its utility for mental fatigue management in real-world settings.

As a common complaint in contemporary society, mental fatigue is a key element in the deterioration of the daily activities known as time-on-task (TOT) effect, making the prediction of fatigue-related performance decline exceedingly important. However, conventional group-level brain-behavioral correlation analysis has the limitation of generalizability to unseen individuals and fatigue prediction at individual-level is challenging due to the significant differences between individuals both in task performance efficiency and brain activities. Here, we introduced a cross-validated data-driven analysis framework to explore, for the first time, the feasibility of utilizing pre-task idiosyncratic resting-state functional connectivity (FC) on the prediction of fatigue-related task performance degradation at individual level. Specifically, two behavioral metrics, namely $\Delta$ RT (between the most vigilant and fatigued states) and $TOT_{slope}$ over the course of the 15-min sustained attention task, were estimated among three sessions from 37 healthy subjects to represent fatigue-related individual behavioral impairment. Then, a connectome-based prediction model was employed on pre-task resting-state FC features, identifying the network-related differences that contributed to the prediction of performance deterioration. As expected, prominent populational TOT-related performance declines were revealed across three sessions accompanied with substantial inter-individual differences. More importantly, we achieved significantly high accuracies for individualized prediction of both TOT-related behavioral impairment metrics using pre-task neuroimaging features. Despite the distinct patterns between both behavioral metrics, the identified top FC features contributing to the individualized predictions were mainly resided within/between frontal, temporal and parietal areas. Overall, our results of individualized prediction framework extended conventional correlation/classification analysis and may represent a promising avenue for the development of applicable techniques that allow precaution of the TOT-related performance declines in real-world scenarios.

The effectiveness of surgical interventions, whether direct or indirect, for Moyamoya disease (MMD) remains controversial. This study aims to investigate CT perfusion (CTP) as an objective method to evaluate the outcomes of different surgical modalities for adult MMD. The clinical and imaging data of 41 patients who underwent superficial temporal artery-middle cerebral artery (STA-MCA) bypass and 43 who received encephaloduroarteriosynangiosis (EDAS) were retrospectively analyzed. Intra- and intergroup differences in the Modified Rankin Scale (mRS) score, the change in clinical symptoms, collateral grade, and CTP parameters pre- and postoperatively were compared. The overall level of the change in clinical symptoms in the STA-MCA group was higher than in the EDAS group (p < 0.05). In the operative area, the relative cerebral blood flow (rCBF) was significantly higher whereas the relative time to peak (rTTP) and the relative mean transit time (rMTT) were significantly lower in the STA-MCA and EDAS groups postoperatively than preoperatively (all p < 0.05). In the ipsilateral frontal lobe and basal ganglia, the postoperative rCBF was significantly higher, and the rTTP was significantly lower than the preoperative in the STA-MCA group (all p < 0.05). The postoperative rCBF improvement was higher in each brain area for STA-MCA than in the EDAS group (all p < 0.05). Highlighting the utility of CTP, this study demonstrates its effectiveness in assessing postoperative cerebral hemodynamic changes in adult MMD patients. STA-MCA yielded a larger postoperative perfusion area and greater improvement compared to EDAS, suggesting CTP’s potential to elucidate symptom variation between two surgical revascularization procedures. We analyzed computed tomography perfusion parameters in pre- and postoperative adult Moyamoya disease patients undergoing superficial temporal artery-middle cerebral artery bypass and encephaloduroarteriosynangiosis. Our findings suggest computed tomography perfusion’s potential in objectively elucidating symptom variations between these surgical revascularization approaches for MMD. • Postoperative perfusion improvement is only confined to the operative area after EDAS. • Besides the operative area, postoperative perfusion in the ipsilateral frontal lobe and basal ganglia was also improved after STA-MCA. • The degree of perfusion improvement in each brain area in the STA-MCA group was generally greater than that in the EDAS group.

巨结肠症是原发或继发因素导致的粪便积留和结肠扩张而引发的持续性便秘病症,是猫的常见肠道疾病.成年猫患该病机率较高,发病平均年龄为五岁左右.该病常发于短毛家猫,公猫发病率高于母猫,肥胖猫巨结肠症患病率更高. 结肠机械性或机能性的阻塞均可引发该病,如骨盆或骶骨段脊神经病变、家族性自主神经机能异常、骨盆腔狭窄,饮食中有骨头、石块、毛团等都可引起发病.巨结肠症如不及时治疗,可导致患猫死亡.

Objective:To investigate the chemical components of epoxy lignans of Eucommia ulmoides leaves.Methods:The compounds were isolated and purified by various column chromatography methods,and the structures were identified by physical and chemical constants determination and spectral analysis.Results:Twelve epoxy lignans were isolated from Eucommia ulmoides leavesand identified as（+）-neoolivine（1）,8’-hydroxyl-lariciresinol-4’-O-β-D-glueopyranoside（2）,（-）-dehydrodiconiferylalcohol-4-O-β-D-glucopyrano side（3）,（-）-massoniresinol-3 a-O-β-D-glucopyranoside（4）,（8 S,7’S,8’R）-vladinol D-4,4’-O-β-D-diglucopyranoside（5）,arctiinoside B（6）,（+）-8-hydroxy-pinoresinol-4’-O-β-D-glucopyranoside（7）,（+）-8-hydroxyl-pinoresinol-4,4’-O-β-D-diglucopyranoside（8）,（+）-medioresinol-4,4’-O-β-D-diglueopyranoside（9）,prinsepiol-4-O-β-D-glucopyranoside（11）,forsythialanside E（11）,eucommin A（12）,respectively.Conclusion:Among them,compounds 1 to 11 are isolated from Eucommia ulmoides for the first time.

Conventional wisdom suggests mid-task rest as a potential approach to relieve the time-on-task (TOT) effect while accumulating evidence indicated that acute exercise might also effectively restore mental fatigue. However, few studies have explored the neural mechanism underlying these different break types, and the results were scattered. This study provided one of the first looks at how different types of fatigue-recovery break exerted influence on the cognitive processes by evaluating the corresponding behavioral improvement and neural response (EEG power spectral) in a sustained attention task. Specifically, 19 participants performed three sessions of psychomotor vigilance tasks (PVT), with one session including a continuous 30-min PVT while the other two sessions additionally inserted a 15-min mid-task cycling and rest break, respectively. For behavioral performance, both types of break could restore objective vigilance transiently, while subjective feeling was only maintained after mid-task rest. Moreover, divergent patterns of EEG change were observed during post-break improvement. In detail, relative theta decreased and delta increased immediately after mid-task exercise, while decreased delta was found near the end of the rest-inserted task. Meanwhile, theta and delta could serve as neurological indicators to predict the reaction time change for exercise and rest intervention, respectively. In sum, our findings provided novel evidence to demonstrate divergent neural patterns following the mid-task exercise and rest intervention to counter TOT effects, which might lead to new insights into the nascent field of neuroergonomics for mental fatigue restoration.

Because of the undesired fatigue-related consequences, accumulating efforts have been made to find an effective intervention to alleviate the suboptimal cognitive function caused by mental fatigue. Nonetheless, limitations of intervention and evaluation methods may hinder the revealing of underlying neural mechanisms of fatigue recovery. Through the newly-developed dynamic functional connectivity (FC) analysis framework, this study aims to investigate the effects of two types of mid-task interventions (i.e., rest-break and moderate-intensity exercise-break) on the dynamic reorganization of FC during the execution of psychomotor vigilance test (PVT). Using a sliding window approach, temporal brain networks within each frequency band (i.e., δ , θ , α , & β ) were estimated before and immediately after the intervention, and towards the end of the task to investigate the immediate and delayed effects respectively during post-break task reengagement. Behaviourally, similar beneficial effects of exercise- and rest-break on performance were observed, manifested by the immediate improvements after both interventions and a long-lasting influence towards the end of tasks. Moreover, temporal brain networks assessment showed significant immediate decreases of fluctuability, which was followed by an increase of fluctuability towards the end of intervention tasks. Furthermore, the temporal nodal measure revealed the channels with significant differences across tasks were mainly resided in the fronto-parietal areas that exhibited interesting frequency-dependent distribution. The observations of immediate and delayed dynamic FC reorganizations extend previous fatigue-related intervention and static FC studies, and provide new insight into the dynamic characteristics of FC during post-break task reengagement.

目的 评价烟雾综合征(MMS)不同出血模式之间的重要侧支血管扩张程度的差异.方法 回顾性分析以出血为首发症状就诊的MMS患者45例,按出血模式的不同将其分为4个亚组:丘脑出血、纹状体出血、脑叶出血以及脑室出血.所有患者均行数字减影血管造影(DSA)检查,将5支重要的侧支血管豆纹动脉(LSA)、脉络膜前动脉(AChA)、脉络膜后动脉(PChA)、后交通动脉(PComA)和丘脑穿通动脉(TPA)血管扩张程度分为扩张组和非扩张组,计算不同出血模式内各侧支血管的扩张率,对不同组年龄采用单因素方差分析进行比较,对不同出血模式之间各侧支血管扩张率、性别及临床特点(头痛、头晕、反应迟钝、突发意识不清)用卡方检验进行比较.结果 LSA、AChA、PComA在4个出血亚组中均表现为较明显的扩张,其中LSA在丘脑出血、纹状体出血、脑叶出血组中扩张率最高,分别为66.7％、77.0％、77.0％;AChA在脑室出血组中扩张率最高,扩张率为57.1％.PChA在4个亚组中扩张率不同,在丘脑出血组中扩张率最高(58.3％),差异有统计学意义(χ2=9.674,P<0.05).TPA仅在丘脑出血组中出现了扩张,扩张率为25％,差异有统计学意义(χ2=9.347,P<0.05).结论 不同出血模式下MMS患者的各侧支血管均表现为不同程度的代偿性扩张,以LSA、AChA和PComA的扩张率最高.PChA和TPA在丘脑出血组中的扩张率最高,推断是引起丘脑型出血的相关因素.

OBJECTIVE:To explore the value of computed tomography perfusion (CTP) imaging for evaluating the efficacy of encephaloduroarteriosynangiosis (EDAS) treatment of moyamoya syndrome (MMS).METHODS:Forty-three patients with MMS (48 hemispheres) who received EDAS treatment were examined using CTP and DSA before and after surgery. CTP of the ipsilateral cortex, contralateral mirror area, and pons region were measured, and the relative cerebral blood flow (rCBF) and volume (rCBV), mean transit time (rMTT), and time-to-peak (rTTP) were calculated. Based on postoperative DSA, 48 hemispheres were apportioned to two groups based on rich (grades 2, 3) or poor (grades 0, 1) collateral vessel formation, and the pre- and post-operative differences in perfusion changes were compared. The association between clinical outcome, CTP, and the degree of DSA collateral vessels was explored.RESULTS:rCBF and rMTT significantly improved in both the poor and rich collateral vessel formation groups (n = 21 and 27, respectively), while rTTP significantly improved only in the latter. Postoperative CTP improved in the rich and the grade 1 collateral vessel groups (p < 0.01). The clinical improvement was consistent with the improvement of CTP (p = 0.07), but less consistent with the degree of collateral angiogenesis (p = 0.003).CONCLUSION:CTP can quantitatively evaluate the improvement of brain tissue perfusion in the operated area after EDAS. Brain tissue perfusion in operated areas improved regardless of postoperative rich or poor collateral vessel formation observed via DSA. A significant improvement in rTTP in the operated area may indicate the formation of abundant collateral vessels.KEY POINTS:• CTP showed that brain tissue perfusion in the operated area after EDAS improved regardless of rich or poor collateral vessel formation observed via DSA. • Significant improvement of rTTP in the operated area may indicate the formation of abundant collateral vessels.

Driving fatigue in monotonous or demanding driving situations has been a major concern for modern traffic and public safety. Continuous efforts have been made to develop a practical method for driving fatigue detection. Because of its non-invasive and high-temporal resolution, EEG has long been considered as a salient biomarker for driving fatigue detection in recent studies. It is noteworthy that most of the studies up to date focused on single-subject fatigue detection, scattered studies have attempted to develop feasible method for driving fatigue detection across different subjects. In the current work, we used critical functional connectivity (FC) as features to build both single-subject and cross-subject mental fatigue detection models. EEG data were recorded from 19 subjects during a 90-min simulated driving experiment. Multi-band FC matrices were established using Phase Lag Index. Three feature selection methods (including SVM-RFE, Sparse Regression, and PCA) were then used to determine the most contributing FC features for driving fatigue detection. We achieved a superior classification accuracy (99.02%) in single-subject driving fatigue detection using the discriminative connection features from 3 frequency bands (i.e., θ, α, and β) and a comparable accuracy of 97.34% in cross-subject driving fatigue detection. Our results demonstrated that critical connection is an efficient feature for cross-subject driving fatigue detection, and the feature selection results may help build a practical EEG-based driving fatigue detection system.

Objective To evaluate the feasibility of CT angiography (CTA) for assessing anterior choroidal artery (AChA) and posterior communicating artery (PComA) dilatation in patients with moyamoya syndrome (MMS). Methods Eighty-eight MMS patients who underwent digital subtraction angiography (DSA) and CTA within 1 month were enrolled. The AChA was graded using both DSA and CTA. Given the features of dual blood supply, DSA was firstly used for grading of the PComA. Then, the calibers of PComA, P1 or P2 segment of the posterior cerebral artery (PCA), were recorded from CTA. Taking DSA as a reference standard, the optimal cutoff values of the PComA/P1 or PComA/P2 were calculated to determine the dilatation of PComA. Both the AChA and PComA were classified as extreme dilatation (ED, grade 2) or non-extreme dilatation (NED, grade 0 or 1). Results The AChA was evaluated in 149 affected hemispheres of 88 patients while the PComA was evaluated in 70 affected hemispheres of 49 patients. The sensitivity and specificity of CTA in diagnosing AChA-ED were 92% and 93.5% respectively. Both the PComA/P1 ( p < 0.001) and PComA/P2 ( p = 0.4) ratios were increased in the PComA-ED group with the former yielding a better detecting performance than the latter (AUC = 0.92 vs 0.85, p = 0.046). When using 0.71 as a cutoff value, the sensitivity and specificity of the PComA/P1 ratio for diagnosis of PComA-ED cases were 91.3% and 83.3% respectively. Conclusions CTA could be used for the AChA classification in MMS patients, while a PComA/P1 ratio greater than 0.71 indicates the existence of PComA-ED. Key Points • CTA showed a high sensitivity, specificity, and accuracy in diagnosing AChA-ED in patients with MMS. • PComA/P1 ratio greater than 0.71 on CTA signified an extremely dilated PComA. • CTA could be used to assess the dilatation of AChA and PComA in MMS patients, especially for routine postoperative follow-up .

目的 针对目前传统文化意象和现代产品设计之间匹配关系模糊、意象风格难以统一的问题,通过识别传统纹样中表征意象的图像元素,将其应用并服务于现代设计行业.方法 以宋代牡丹纹样的描述词汇为样本,采用多维尺度法归纳出意象维度,根据语义差异法完成对纹样的意象分类;基于眼动跟踪技术得到各意象维度下的注视数据,采用均值漂移算法聚类出具有意象代表性的纹样元素并量化其表征度.结果 得到高雅、祥瑞、素雅、柔润、灵动和精致6个意象维度下的纹样意象元素,并计算得出代表该意象元素在牡丹纹样意象中的贡献程度指标——表征度.结论 实验表明该方法具有可重复性和可行性,识别结果表现出了一定的意象内涵和应用价值,可为传统文化再设计提供参考思路.