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Motor imagery training (MIT) has been widely used to improve hemiplegic upper limb function in stroke rehabilitation. The effectiveness of MIT is associated with the functional neuroplasticity of the motor network. Currently, brain activation and connectivity changes related to the motor recovery process after MIT are not well understood.We aimed to investigate the neural mechanisms of MIT in stroke rehabilitation through a longitudinal intervention study design with task-based functional magnetic resonance imaging (fMRI) analysis.We recruited 39 stroke patients with moderate to severe upper limb motor impairment and randomly assigned them to either the MIT or control groups. Patients in the MIT group received 4 weeks of MIT therapy plus conventional rehabilitation, while the control group only received conventional rehabilitation. The assessment of Fugl-Meyer Upper Limb Scale (FM-UL) and Barthel Index (BI), and fMRI scanning using a passive hand movement task were conducted on all patients before and after treatment. The changes in brain activation and functional connectivity (FC) were analyzed. Pearson's correlation analysis was conducted to evaluate the association between neural functional changes and motor improvement.The MIT group achieved higher improvements in FM-UL and BI relative to the control group after the treatment. Passive movement of the affected hand evoked an abnormal bilateral activation pattern in both groups before intervention. A significant Group × Time interaction was found in the contralesional S1 and ipsilesional M1, showing a decrease of activation after intervention specifically in the MIT group, which was negatively correlated with the FM-UL improvement. FC analysis of the ipsilesional M1 displayed the motor network reorganization within the ipsilesional hemisphere, which correlated with the motor score changes.MIT could help decrease the compensatory activation at both hemispheres and reshape the FC within the ipsilesional hemisphere along with functional recovery in stroke patients.

Quadcopter is an important way for the human to explore the physical world. The brain-computer interface (BCI) technology is used to control the quadcopter flight in order to help disabled persons communicate with the external world freely. In this study, a quadcopter control system using a hybrid BCI based on off-line optimization and enhanced human-machine interaction was designed to control the quadcopter flight in 3D physical space. The proposed system implemented the control of quadcopter moving up/down, forward/backward, left/right by six different SSVEP, and turning left/right by left-hand and right-hand motor imagery. Meanwhile, the optimization of the control system and the human-machine interaction enhancement improved practicability in real-time use. Five subjects participated in an on-line experiment to control the quadcopter flight in real-time. The average classification accuracy of EEG-based commands in the on-line experiment was 87.09±2.82% and information transfer rate (ITR) was 0.857±0.085 bits/min. The results demonstrated the feasibility of multidirectional control of quadcopter flight in 3D space by using hybrid BCI technology and revealed the practicality and operability of the hybrid BCI control system based on off-line optimization and human-machine interaction enhancement.

Electroencephalogram (EEG) microstate analysis is a promising and effective spatio-temporal method that can segment signals into several quasi-stable classes, providing a great opportunity to investigate short-range and long-range neural dynamics. However, there are still many controversies in terms of reproducibility and reliability when selecting different parameters or datatypes. In this study, five electrode configurations (91, 64, 32, 19, and 8 channels) were used to measure the reliability of microstate analysis at different electrode densities during propofol-induced sedation. First, the microstate topography and parameters at five different electrode densities were compared in the baseline (BS) condition and the moderate sedation (MD) condition, respectively. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were introduced to quantify the consistency of the microstate parameters. Second, statistical analysis and classification between BS and MD were performed to determine whether the microstate differences between different conditions remained stable at different electrode densities, and ICC was also calculated between the different conditions to measure the consistency of the results in a single condition. The results showed that in both the BS or MD condition, respectively, there were few significant differences in the microstate parameters among the 91-, 64-, and 32-channel configurations, with most of the differences observed between the 19- or 8-channel configurations and the other configurations. The ICC and CV data also showed that the consistency among the 91-, 64-, and 32-channel configurations was better than that among all five electrode configurations after including the 19- and 8-channel configurations. Furthermore, the significant differences between the conditions in the 91-channel configuration remained stable at the 64- and 32-channel resolutions, but disappeared at the 19- and 8-channel resolutions. In addition, the classification and ICC results showed that the microstate analysis became unreliable with fewer than 20 electrodes. The findings of this study support the hypothesis that microstate analysis of different brain states is more reliable with higher electrode densities; the use of a small number of channels is not recommended. usc Refereed/Peer-reviewed

In the current study, the morphology including tortuosity, and the permeability of 50-mm thick commercially available 30, 40, 50, and 80 pores per inch (PPI) alumina ceramic foam filters (CFFs) have been investigated. Measurements have been taken of cell (pore), window, and strut sizes, porosity, tortuosity, and liquid permeability. Water velocities from ~0.015 to 0.77 m/s have been used to derive both first-order (Darcy) and second-order (Non-Darcy) terms for being used with the Forchheimer equation. Measurements were made using 49-mm “straight through” and 101-mm diameter “expanding flow field” designs. Results from the two designs are compared with calculations made using COMSOL 4.2a® 2D axial symmetric finite element modeling (FEM), as a function of velocity and filter PPI. Permeability results are correlated using directly measurable parameters and compared with the previously published results. Development of improved wall sealing (49 mm) and elimination of wall effects (101 mm) have led to a high level of agreement between experimental, analytic, and FEM methods (±0 to 7 pct on predicted pressure drop) for both types of experiments. Tortuosity has been determined by two inductive methods, one using cold-solidified samples at 60 kHz and the other using liquid metal at 50 Hz, giving comparable results.

This paper proposes a solution to establish a biomedical technology analysis platform to laying foundation for an expert knowledge-based biomedical system, which aims to give intelligent medical decision in the end. It curates 23.44 million biomedical articles since 1970 for serving as repository to supporting as knowledge base. Based on the platform, trend prediction in biomedical technology has been made by semantic analysis.

The metabolic flux balance model of L-Try synthesis by Corynebacterium glutamicum was constructed in this paper. Using this model, the metabolic flux distribution during the middle and late period were determined and the optimal flux distribution were calculated by linear program of MATLAB software. The analysis results indicate that 24.85% metabolic flux entered the HMP pathway and 75.15% entered the EMP cycle. But comparing to the optimal flux distributions, the production of L-Try should be improved from the genetic manipulation and fermentation control through reducing byproduct of amino acid and decreasing the metabolic flux of TCA and EMP.