Spatial-Frequency Characteristics of EEG Associated with the Mental Stress in Human-Machine Systems.

Accurate assessment of user mental stress in human-machine system plays a crucial role in ensuring task performance and system safety. However, the underlying neural mechanisms of stress in human-machine tasks and assessment methods based on physiological indicators remain fundamental challenges. In this paper, we employ a virtual unmanned aerial vehicle (UAV) control experiment to explore the reorganization of functional brain network patterns under stress conditions. The results indicate enhanced functional connectivity in the frontal theta band and central beta band, as well as reduced functional connectivity in the left parieto-occipital alpha band, which is associated with increased mental stress. Evaluation of network metrics reveals that decreased global efficiency in the theta and beta bands is linked to elevated stress levels. Subsequently, inspired by the frequency-specific patterns in the stress brain network, a cross-band graph convolutional network (CBGCN) model is constructed for mental stress brain state recognition. The proposed method captures the spatial-frequency topological relationships of cross-band brain networks through multiple branches, with the aim of integrating complex dynamic patterns hidden in the brain network and learning discriminative cognitive features. Experimental results demonstrate that the neuro-inspired CBGCN model improves classification performance and enhances model interpretability. The study suggests that the proposed approach provides a potentially viable solution for recognizing stress states in human-machine system by using EEG signals.

A rat brain MRI template with digital stereotaxic atlas of fine anatomical delineations in paxinos space and its automated application in voxel-wise analysis.

This study constructs a rat brain T2 -weighted magnetic resonance imaging template including olfactory bulb and a compatible digital atlas. The atlas contains 624 carefully delineated brain structures based on the newest (2005) edition of rat brain atlas by Paxinos and Watson. An automated procedure, as an SPM toolbox, was introduced for spatially normalizing individual rat brains, conducting statistical analysis and visually localizing the results in the Atlas coordinate space. The brain template/atlas and the procedure were evaluated using functional images between rats with the right side middle cerebral artery occlusion (MCAO) and normal controls. The result shows that the brain region with significant signal decline in the MCAO rats was consistent with the occlusion position.

Exploring EEG characteristics of multi-level mental stress based on human-machine system.

Objective.The understanding of cognitive states is important for the development of human-machine systems (HMSs), and one of the fundamental but challenging issues is the understanding and assessment of the operator's mental stress state in real task scenarios.Approach.In this paper, a virtual unmanned vehicle (UAV) driving task with multi-challenge-level was created to explore the operator's mental stress, and the human brain activity during the task was tracked in real time via electroencephalography (EEG). A mental stress analysis dataset for the virtual UAV task was then developed and used to explore the neural activation patterns associated with mental stress activity. Finally, a multiple attention-based convolutional neural network (MACN) was constructed for automatic stress assessment using the extracted stress-sensitive neural activation features.Main Results.The statistical results of EEG power spectral density (PSD) showed that frontal theta-PSD decreased with increasing task difficulty, and central beta-PSD increased with increasing task difficulty, indicating that neural patterns showed different trends under different levels of mental stress. The performance of the proposed MACN was evaluated based on the dimensional model, and results showed that average three-class classification accuracies of 89.49%/89.88% were respectively achieved for arousal/valence.Significance.The results of this paper suggest that objective assessment of mental stress in a HMS based on a virtual UAV scenario is feasible, and the proposed method provides a promising solution for cognitive computing and applications in human-machine tasks.

Task-independent auditory probes reveal changes in mental workload during simulated quadrotor UAV training.

Objective: The event-related potential (ERP) methods based on laboratory control scenes have been widely used to measure the level of mental workload during operational tasks. In this study, both task difficulty and test time were considered. Auditory probes (ignored task-irrelevant background sounds) were used to explore the changes in mental workload of unmanned aerial vehicle (UAV) operators during task execution and their ERP representations. Approach: 51 students participated in a 10-day training and test of simulated quadrotor UAV. During the experiment, background sound was played to induce ERP according to the requirements of oddball paradigm, and the relationship between mental workload and the amplitudes of N200 and P300 in ERP was explored. Main results: Our study shows that the mental workload during operational task training is multi-dimensional, and its changes are affected by bottom-up perception and top-down cognition. The N200 component of the ERP evoked by the auditory probe corresponds to the bottom-up perceptual part; while the P300 component corresponds to the top-down cognitive part, which is positively correlated with the improvement of skill level. Significance: This paper describes the relationship between ERP induced by auditory probes and mental workload from the perspective of multi-resource theory and human information processing. This suggests that the auditory probe can be used to reveal the mental workload during the training of operational tasks, which not only provides a possible reference for measuring the mental workload, but also provides a possibility for identifying the development of the operator's skill level and evaluating the training effect.

Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema.

The study of mental workload has attracted much interest in neuroergonomics, a frontier field of research. However, there appears no consensus on how to measure mental workload effectively because the mental workload is not only regulated by task difficulty but also affected by individual skill level reflected as mental schema. In this study, we investigated the alterations in the functional brain network induced by a 10-day simulated piloting task with different difficulty levels. Topological features quantifying global and local information communication and network organization were analyzed. It was found that during different tests, the global efficiency did not change, but the gravity center of the local efficiency of the network moved from the frontal to the posterior area; the small-worldness of the functional brain network became stronger. These results demonstrate the reconfiguration of the brain network during the development of mental schema. Furthermore, for the first two tests, the global and local efficiency did not have a consistent change trend under different difficulty levels, but after forming the developed mental schema, both of them decreased with the increase in task difficulty, showing sensitivity to the increase in mental workload. Our results demonstrate brain network reconfiguration during the motor learning process and reveal the importance of the developed mental schema for the accurate assessment of mental workload. We concluded that the efficiency of the brain network was associated with mental workload with developed mental schema.

Cortical theta-gamma coupling tracks the mental workload as an indicator of mental schema development during simulated quadrotor UAV operation.

Objective. In the emerging field of neuroergonomics, mental workload assessment is one of the most important problems. Previous studies have made some progress on the relationship between task difficulties and mental workload, but how the mental schema, a reflection of the understanding and mastery degree of a task, affects mental workload has not been clearly discussed.Approach. There is emerging appreciation for the role of theta-gamma coupling (TGC) in high-level cognitive functions. Here, we attempt to further our understanding of how mental schema development and task difficulty had an impact on mental workload from the perspective of TGC. Specifically, the variation of TGC coupling strength and coupling pattern was estimated with different test orders and task difficulties performed by 51 students in a ten-day simulated quadrotor unmanned aerial vehicle flight training and test tasks.Main results. During the training, TGC increased with mental schema development. For the test tasks, TGC did not change with increasing task difficulty before the operator formed a mental schema but decreased with the increasing mental workload after the formation of the mental schema.Significance. Our results suggest that TGC was a robust indicator of mental schema development and could be biased by task difficulty. In conclusion, TGC can be a promising measure of mental workload, but only for experienced operators.

The effect of mental schema evolution on mental workload measurement: an EEG study with simulated quadrotor UAV operation.

Objective. Mental workload is the result of the interactions between the demands of an operation task, the environment in which the task is performed, and the skills, behavior and perception of the performer. Working under a high mental workload can significantly affect an operator's ability to choose optimal decisions, judgments and motor actions while operating an unmanned aerial vehicle (UAV). However, the effect of mental schema, which reflects the level of expertise of an operator, on mental workload remains unclear. Here, we propose a theoretical framework for describing how the evolution of mental schema affects mental workload from the perspective of cognitive processing.Approach. We recruited 51 students to participate in a 10-day simulated quadrotor UAV flight training exercise. The EEG power spectral density (PSD)-based metrics were used to investigate the changes in neural responses caused by variations in the mental workload at different stages of mental schema evolution.Main results. It was found that the mental schema evolution influenced the direction and change trends of the frontal theta PSD, parietal alpha PSD, and central beta PSD, which are EEG indicators of mental workload. Initially, before the mental schema was formed, only the frontal theta PSD increased with increasing task difficulty; when the mental schema was initially being developed, the frontal theta PSD and the parietal alpha PSD decreased with increasing task difficulty, while the central beta PSD increased with increasing task difficulty. Finally, as the mental schema gradually matured, the trend of the three indicators did not change with increasing task difficulty. However, differences in the frontal PSD became more pronounced across task difficulty levels, while differences in the parietal PSD narrowed.Significance. Our results describe the relationship between the EEG PSD and the mental workload of UAV operators as the mental schema evolved. This suggests that EEG activity can be used to identify the mental schema and mental workload experienced by operators while performing a task, which can not only provide more accurate measurements of mental workload but also provide insights into the development of an operator's skill level.

[Functional connectivity analysis of super acute cerebral ischemia in rats: a resting-state functional MRI empirical study].

OBJECTIVE: To investigate the change of low-frequency blood-oxygenation-level-dependent fluctuation (LFBF) after cerebral ischemia by functional connectivity analysis in the resting state. METHODS: Super acute stroke rat-models with middle cerebral artery occlusion (MCAO) were employed in this study. Spontaneous fluctuations were recorded using a series of gradient-recalled echo-planar imaging (EPI) images before creation of the MCAO, and the same scan protocols were duplicated at the time of 60 min, 2 h after creation of the MCAO. FMRI signal time series from the different ROIs of ischemic cortex and normal cortex were preprocessed and low pass filtered. After preprocessing, the serial fMRI data was obtained by fast Fourier transformation to calculate the amplitude of the low-frequency fluctuations. Meanwhile, time course signal changes from a seed voxel of normal cortex were correlated with every voxel in the brain. Statistical analysis was performed across all rats to determine the extent of spatial correlation between regions. RESULTS: The amplitude of LFBF in the ischemic cortex between 0.01 and 0.1 Hz was lightly decreased during the super acute ischemic stroke. Howerever, the amplitude of LFBF in contralateral cortex was increased after 2 hours. Spatial distribution of LFBF, from cross-correlation analysis, indicates that the substantial inter-hemispheric synchrony of ischemic region was decreased and of contralateral cortex was enhanced during the super acute ischemic stroke. CONCLUSION: The contrast behavior of the resting state BOLD signal fluctuations and a intra-hemispheric symmetry in the LFBF with similar phase characteristics in most other regions during super acute ischemic stroke can be implied a new approach to detect the physiological activity functions and the distinct resting neural networks after the acute ischemic stroke takes place.

[A study of ischemic penumbra by perfusion and diffusion-weighted imaging at high-field MRI (7.0 T)].

OBJECTIVE: To approach the value of perfusion-weighed and diffusion-weighted imaging at high field intensity (7.0 T) MR in research of the ischemic penumbra in acute cerebral infarction of rats. METHODS: Acute cerebral infarction of rat was induced by occluding middle cerebral artery (MCAO) with suture. Sixty SD rats were divided into six groups randomly of ten including sham operation group, and groups of MCAO for 0.5, 1.5, 3, 6, 24 h. Then all rats were examined by PWI, DWI, T1WI, T2WI and MRA at corresponding time point. Regional cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), mean transit time (MTT) topographical maps were reconstructed and the relative values of rCBV, rCBF, MTT, DWI-derived (rVD) and PWI-derived (rVP) lesion volume were calculated. The outcomes of serial MRI were compared with TTC stain and pathological findings. RESULTS: Neither abnormal signal of MRI nor TTC stain or pathological changes were found in sham operation group. The rCBV, rCBF was significantly decreased but rMTT obviously extended of the area of middle cerebral artery blood-supply of each group of MCAO. The core of infarction was more serious than the edge of infarction. Abnormal signals were found in the MCA-supplying regions in the DWI and PWI of all of the groups of MCAO. The size of rVD became bigger with the time going on but no significant difference of rVP. The size of rVP was larger than rVD before MCAO of 6 h (P < 0.05). There was no significant difference between PWI and DWI after 6 h (P > 0.05) and also between TTC at 24 h and DWI after 3 h (P > 0.05). CONCLUSION: Perfusion-weighed and diffusion-weighted imaging at high field intensity (7.0 T) MR dynamic displaying the existence and the process of ischemic penumbra in acute cerebral infarction of rats provides a basis for further study.

MRI assessment of amplitude of low-frequency fluctuation in rat brains with acute cerebral ischemic stroke.

To investigate fluctuations in the amplitude of low-frequency blood oxygenation level-dependent (BOLD) fMRI during acute brain ischemia, and to evaluate the use of amplitude of low-frequency fluctuations (ALFFs) in resting state fMRI for assessing super-acute focal cerebral ischemic stroke. A super-acute stroke model with middle cerebral artery occlusion (MCAO) in the rat was employed. Spontaneous fluctuations were recorded using a series of gradient echo-planar imaging (EPI) images before and 30 min, 60 min, 2 h, 6 h, 12 h, and 24 h after MCAO. After preprocessing, serial fMRI data were obtained by fast Fourier transformation to calculate the ALFFs. Statistical parametric mapping software was used for the statistical analysis of ALFFs. T2-weighted images and diffusion weighted images (DWI) were also performed to detect the ischemic lesion. The signal intensities of abnormal ALFFs increased and migrated from the core of the ischemic lesion areas to the edge of lesion following MCAO. The dynamic changes in the ALFF maps demonstrated that the sizes of the ALFF regions exceeded beyond the borderline of the DWI lesions during the super-acute ischemic stroke stage. There was a significant difference in the ALFFs maps between the ischemic stroke group and the control group (P<0.005; cluster size>10 voxels), which mainly occurred in the periphery of the ischemic region in the cortex. These data suggest that ALFF maps provide hemodynamic BOLD information on neural activity, and have potential for predicting survival and prognosis of acute ischemic brain tissues.

Efficient nano iron particle-labeling and noninvasive MR imaging of mouse bone marrow-derived endothelial progenitor cells.

In this study, we sought to label mouse bone marrow-derived endothelial progenitor cells (EPCs) with Resovist(®) in vitro and to image them using 7.0 Tesla (T) magnetic resonance imaging (MRI). Mouse bone marrow-derived EPCs were cultured in endothelial basal medium with endothelial growth supplement. They were then characterized by immunocytochemistry, flow cytometry, and fluorescence quantitative polymerase chain reaction. Their functions were evaluated by measuring their uptake of 1,1-dioctadecyl-3,3,3,3-tetramethylindocarbocyanine-labeled acetylated low-density lipoprotein (Dil-Ac-LDL), binding of fluorine isothiocyanate (FITC)-labeled Ulex europaeus agglutinin (UEA), and formation of capillary-like networks. EPCs were labeled with superparamagnetic iron oxide (SPIO) and their proliferation was then assessed in a water-soluble tetrazolium (WST-8)-based cell proliferation assay. Spin echo sequence (multislice, multiecho [MSME]) and gradient echo sequence (2D-FLASH) were used to detect differences in the numbers of labeled cells by 7.0 T MRI. The results showed that the cultured cells were of "cobblestone"-like shape and positive for CD133, CD34, CD31, von Willebrand factor, kinase domain receptor, and CD45, but negative for F4/80. They could take up Dil-Ac-LDL, bind FITC-UEA, and form capillary-like networks on Matrigel in vitro. Prussian-blue staining demonstrated that the cells were efficiently labeled with SPIO. The single-cell T2* effect was more obvious in the 2D-FLASH sequence than in the MSME sequence. Further, there were almost no adverse effects on cell vitality and proliferation. In conclusion, mouse bone marrow-derived EPCs can be efficiently labeled with SPIO and imaged with 7.0-T MRI. They may thus be traced by MRI following transplantation for blood vessel disorders and cancer treatment.