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2016 Vol. 35, No. 1 Published: 2016-02-20 1 Dynamic Brain Connectivity Analysis Based on Autoregressive-Model and Phase Slope Index Huang Liang   Wu Chaohua   Gao Xiaorong#* DOI: 10.3969/j.issn.0258-8021.2016.01.001 Functional and effective connectivity are important branches in brain network research. Electroencephalogram (EEG) has sufficient temporal resolution to catch the fast brain dynamic changes, so it is suitable for effective connectivity analysis. We proposed a new method to estimate the effective connectivity base on EEG, namely autoregressive phase slope index (AR-PSI). Spectral estimation based on MVAR has high frequency resolution even on short time data. PSI is insensitive to linear mixture of noninteracting sources. AR-PSI combined advantages of the two methods. Compared with conventional Granger causality model, AR-PSI could eliminate the interference caused by volume conduction. Compared with conventional PSI, AR-PSI could get more accurate estimation of effective connectivity with short time data. Experimental data indicated that AR-PSI could exactly detect the effective connectivity between two signals and exclude the false detection. AR-PSI was also applied to dynamic brain connectivity analysis based on EEG recorded in Stroop paradigm. We found that brain connectivity density had significant difference under two conditions in 250～500 ms and 550～800 ms. The results indicated that the incongruent stimulus could make the density of brain network increase more quickly and expand the span of connectivity. 2016 Vol. 35 (1): 1-9 [Abstract] ( 539 ) HTML (1 KB)  PDF (5089 KB)  ( 1017 ) 10 Reconstruction of Intravascular Photoacoustic Images Based on Filtered Back-projection Algorithm Han Duoduo   Sun Zheng*   Yuan Yuan DOI: 10.3969/j.issn.0258-8021.2016.01.002 A simple and fast image reconstruction method based on filtered back-projection (FBP) that has been widely applied in photoacoustic tomography (PAT) was proposed for intravascular photoacoustic (IVPA) imaging. First, the raw photoacoustic signals generated by the tissues were preprocessed by filtering, deconvolution and first-order derivation in time domain. Then, according to the specificity of IVPA scanning in the closed vascular lumen, the pre-processed photoacoustic signal data were back-projected along arcs with a weighting method to obtain the initial photoacoustic pressure of each grid point in the imaging region outside the catheter. Finally, grayscale images displaying the morphological structure of vascular cross-sections were constructed. The experimental results with a computer-simulated vessel phantom show that the structural similarity (SSIM) of the reconstructed image reached 0.5717. The image quality was improved by setting a proper filter prototype, cut-off frequency and the number of measuring positions. The structural information of the vessel wall and plaque tissues can be effectively enhanced through first-order derivation performed to the raw photoacoustic signals. This method provides the foundation for subsequent optimization of image reconstruction algorithm. 2016 Vol. 35 (1): 10-19 [Abstract] ( 638 ) HTML (1 KB)  PDF (12123 KB)  ( 321 ) 20 Multimodal Fusion of EEG and EMG Signals for a Hybrid BCI Xie Ping  Chen Yingya  HaoYanbia  Chen Xiaoling  Du Yihao  Wu Xiaoguang* DOI: 10.3969/j.issn.0258-8021.2016.01.003 Pattern recognition is one of the hot researches in the braincomputer interface technology. In order to solve the problems in BCI, such as movement pattern singleness and low recognition rate, a hBCIbased strategy fusioning the features of EEG and EMG was proposed to realize the classification of different motor patterns with unilateral limb. In the present study, the eventrelated desynchronization features and intergrated electromyogram features were abstracted based on the EEG over brain scope and EMG from flexor carpi ulnaris and extensor carpi radialis longus under wrist flexion or extension in 9 healthy subjects. Secondly, the pattern recognition model fusioning the features of EEG and EMG, based on the theories of support vector machine and particle swarm optimization, was designed to classify optimally by adjusting the feature fusion coefficient. Furthermore, the proposed method was verified based on the EMG signals of patients or healthy subjects under fatigue state, which were simulated by descending the EMG amplitude of healthy subjects. Results showed that the recognition rate based on the fusion of EEG and EMG (98%) improved 25% compared to sole EEG feature under natural condition (73%); the recognition rate reached a stable level above 80% and improved 14% compared to sole EMG feature under fatigue state. It is revealed that the fusion of EEG and EMG feature contributed to improve the accuracy of pattern recognition and stability of movement, and provided the basis for the application of hybrid braincomputer interface. 2016 Vol. 35 (1): 20-30 [Abstract] ( 573 ) HTML (1 KB)  PDF (6415 KB)  ( 1131 ) 31 On the Semi-Automatic Processing Characteristic of MMN Liu Rong1*  Lin Shaofei1  Wang Yongxuan2   Sun Yutong1 DOI: 10.3969/j.issn.0258-8021.2016.01.004 Whether MMN is regulated by attention has been a debate in the MMN research field. There are few experimental paradigms which could control the attention allocation between the attended and unattended channels. Moreover, there is no index to reflect the subtle fluctuation of attention resource of the subjects. The diffusion model is one kind of cognitive process models,  to reveal the potential neural processing mechanism based on the behavior data such as reaction time and accuracy of the task. Therefore, this paper developed a new crossmodal and delayed response experimental paradigm to better control subjects′ attention resources. Then the parameters fitted by the diffusion model were used to establish the relationship between the MMN and the attention. Experimental results showed that the parameters fitted by the diffusion model using behavior data could explain the underlying decision processes under different conditions on the subjects′ attention. As a result, the method could quantitatively determine the subjects′ attention. Meanwhile, we also found that the variation of the MMN peak latency was affected by variations in task difficulty and had a significant correlation with attentionrelated parameters of diffusion model: the correlation coefficient r between the MMN peak latency and b, v and tERwere 0.63, 0.63 and 0.58 respectively. This proves that the parameters of the diffusion model can be used as an index of the subjects′ attention resource allocation, and MMN peak latency is positively correlated with intensity of attention. Therefore, we consider that the MMN reflects a semiautomatic process. 2016 Vol. 35 (1): 31-37 [Abstract] ( 488 ) HTML (1 KB)  PDF (2391 KB)  ( 545 ) 38 A Fast Sparse Representation Classification Method for Human Activity-Recognition Based on Random Projection Wu Jianning*Xu Haidong   Wang Jiajing   Ling Yun DOI: 10.3969/j.issn.0258-8021.2016.01.005 In this paper, a fast sparse representation classification method for human activity recognition based on random projection was proposed, in order to minimize the energy consumption and accurately recognize human activities from wireless body sensor networksbased telemonitoring system of human daily activity. The basic idea of the proposed method is that the random projection way of compressed sensing theory is used to reduce the amount of sampling on sensor nodes within body sensor network, and then the smaller number of nearest neighbor training samples within the neighbor classes of testing sample, which can optimally liner reconstruction testing sample, are obtained to construct the training sample set of the sparse representation of testing sample. Thus, a fast sparse representation classification algorithm with superior performance of generalization can be developed for capturing valuable features of human activity and improving the recognition rate on the basis of the lower energy consumption and computation complexity of algorithm. The multi-class activity data from international open wearable sensor action recognition database WRAD was selected to evaluate the effectiveness of our method. The experimental results showed that, when the data compression rate was 50%, the proposed algorithm could obtain the highest average recognition rate (92.78%), which was increased by approximately 5% compared with that of the traditional sparse representation classification algorithms. Meanwhile, the operating time of our proposed algorithm was significantly reduced compared with the above traditional methods.We believed that the proposed algorithm could not only effectively reduce the computational complexity and its running time but also significantly enhance the human activity recognition accuracy, providing a new idea and method for developing the fast sparse representation classification algorithm for activity recognition. 2016 Vol. 35 (1): 38-46 [Abstract] ( 3270 ) HTML (1 KB)  PDF (1483 KB)  ( 604 ) 47 Error Analysis on the Assessment of Cardiovascular Function Based on Integration of Clinical Data and Cardiovascular Model Li Yi1   Yin Zhaofang2   Liang Fuyou1#* DOI: 10.3969/j.issn.0258-8021.2016.01.006 The purpose of this study is to identify the key factors that affect the accuracy of patient-specific assessment of cardiovascular function (by means of integration of clinical data and cardiovascular model) and quantify their effects so as to provide theoretical evidence for guiding the clinical application of the assessment method. Parameter sensitivity analysis was performed in combination with parameter subset selection to identify the secondary main parameters that are related closely to the modelbased prediction of hemodynamic variables and the assessment of the main parameters (corresponding to the assessed cardiovascular function). Numerical experiments were carried out based on a series of virtual clinical data to quantify the changes in assessment results induced by measurement errors (in a range of 5%) of clinical data and variations in the secondary main parameters (rate of change being 30%). Measurement errors of clinical data were found to induce pronounced changes in assessment results (up to 16.6%), relatively, variations in the secondary main parameters had less influence on the assessment (rates of changes being within 10%). Accurate clinical data measurement is a key step to guaranteeing the reliability of cardiovascular function assessment. The secondary main parameters only have limited influence on the assessment although they may vary significantly among patients. 2016 Vol. 35 (1): 47-54 [Abstract] ( 516 ) HTML (1 KB)  PDF (5719 KB)  ( 599 ) 55 Establishment of a Four Layer Complicated Ellipsoid Brain Model Ke Li1  Gao Yanzhao1  Du Qiang1  Han Ling2 DOI: 10.3969/j.issn.0258-8021.2016.01.007 The study of brain model establishment is the basis of intracranial imaging, and it is also the necessary condition for the calculation of forward problem solution in the magnetic induction tomography (MIT) system. According to the brain structure, a four layers complicated ellipsoid brain model was established through a finite element simulation software Comsol Multiphysics. Firstly, the brain parenchyma model was constructed according to the brain volume and the skull inner diameter. Secondly, the skull model was constructed according to the human anatomy structureand the contour, occipital, frontal and orbit of the model were corrected. Thirdly, the head cortex, skull and spinal fluid layer were constituted by scale model of the skull, and the four layers brain model were constituted together with the brain parenchyma layer. Finally, put the model into alternating current magnetic field of 10 MHz, and gave the induced current distribution of scalp layer, skull layer, spinal fluid layer and parenchymal layer. The induced current was strongest in the spinal fluid layer and weaker in the skin layer and the parenchymal layer, while was the weakest in the skull layer. The ratio of the induced current density values in each layer was 32:1:190:21, closed to the ratio of electrical conductivity. The simulation experimental results showed that the model could display the difference of the electromagnetic characteristics of human head tissues, providing reliable data for MIT system. 2016 Vol. 35 (1): 55-62 [Abstract] ( 706 ) HTML (1 KB)  PDF (5719 KB)  ( 674 ) 63 Biomechanical Study of the Facial Impact on Pedestrian Yang Bin1,2,3  Cao Libo1  Li Peng2  Hu Min2  Xiao Feng2  Yuan Yunkang2Mei Yongcun2  DOI: 10.3969/j.issn.0258-8021.2016.01.008 The aim of this work is to predict and evaluate the injury mechanism and biomechanical response of the facial impact on pedestrian traumatic brain injury. With the combination of computed tomography (CT) and magnetic resonance imaging (MRI), both geometric and finite element (FE) models for human headneck were developed based on Chinese headneck anatomic structure. Both the skull and the brain interface were modeled as a contact pair with a tangential sliding boundary condition with the coefficient of friction of 0.2. Five typical cases of facial traffic accidents were simulated, including frontal oblique impact on the nasal bone, frontal impact on lateral cartilage on the nasal tip, frontal impact on teeth, base impact on mandible and lateral oblique impact on zygomatic bone. Also, investigation of the association of the TBI with its mechanisms following facial trauma was conducted, with the individual stress wave propagation paths to the intracranial contents through the facial and cranial skeleton being discussed thoroughly. Intracranial pressure, von Mises stress and shear stress distribution were achieved. It was indicated that the frontal oblique impact on the nasal bone was the most severe with peak pressure of 236.7 kPa and maximum von Mises stress of 25.97 kPa comparable to the brain tolerance threshold. It was shown that the lateral oblique impact on zygomaticomaxillary bone produces the highest shear stresses of 14.56 kPa and -18.07 kPa in leftright direction while the base impacts on the mandible cause the brain tissues to shear tremendously, which indicates a risk of severe TBI. It was proved the site and direction of facial impact played a key role in determining the severity of facial fracture and location of facial bone fracture, which in turns influence those of TBI, facial fracture has a certain degree of traumatic brain injury. The facial structure dissipated the impact energy to protect the brain in its most natural way and reduce the risk of TBI. 2016 Vol. 35 (1): 63-70 [Abstract] ( 516 ) HTML (1 KB)  PDF (9404 KB)  ( 262 ) 71 髋臼骨折内固定的置钉安全研究 Jiang Yuchen1  Wang Dongmei1* Bi Chun2  Ji Xiaoxi2  Wang Fang2  Wang Qiugen2 DOI: 10.3969/j.issn.0258-8021.2016.01.009 探讨髋臼骨折内固定危险区域安全置钉的方法，降低螺钉穿入髋关节的风险。取得173例正常成人完整骨盆CT断层扫描数据, 由此建立清晰完整的三维数字化骨盆模型，对其进行由耻骨联合到骶髂关节方向的曲线拟合，并在髋臼区域等分此曲线，获得垂直曲线的5个截面。以过进钉点并垂直于骨表面的截面曲线法向面作为参考平面，测量不同截面的进钉角度范围（α～γ）及对应的进钉深度d1、d2、d0；比较男性、女性之间存在的差异，综合手术入路的可行性，对髋臼区螺钉植入进行安全规划。结果表明，截面2的d0，截面3的β、γ 以及截面4的β，在男性和女性之间的差异具有统计学意义（P＜0.05）；安全进钉角度范围与手术入路可行范围存在部分交集。临床髋臼区域下缘置钉时要考虑到男、女性别不同所产生的差异；截面1和截面5置钉方向比较自由；截面4安全置钉角度接近可操作临界角度，临床上置钉应避开截面2和截面3。 2016 Vol. 35 (1): 71-78 [Abstract] ( 343 ) HTML (1 KB)  PDF (3169 KB)  ( 558 ) 79 Mechanism of Suppression of Epileptiform Burst by Closed-Loop Electrical Stimulation Cao Jiayue  Feng Zhouyan*  Guo Zheshan  Hu Zhenhua  Hu Na DOI: 10.3969/j.issn.0258-8021.2016.01.010 Deep brain stimulation (DBS) is an attractive alternative strategy to surgical excision of the seizure focuses for epilepsy treatments in clinic. However, epilepsy can be generated by various mechanisms, and this highlights a need in designing pertinent DBS patterns with customized parameters for the effective therapy. In the present study, high-frequency stimulation (HFS) pulse trains with short durations were used against the epileptic form activity induced by picrotoxin, an antagonist of GABAergic receptors, in the hippocampal CA1 region of anaesthetized rats. In a closedloop manner, the HFS train was applied during each period of epileptic form bursts to the afferent axon tracts (i.e. the Schaffer collaterals) of CA1 region. The experiment results from 9 rats show that HFS trains with a frequency over 100 Hz and duration of 0.3 s during bursts suppressed 60-70% of the spikes in the bursts. Meanwhile, during the periods of HFS against bursts, the neurons of CA1 region failed to respond to the excitation of antidromic stimulation applied to the efferent axon tracts (i.e. the alveus), indicating that the neurons temporarily lost their ability to generate action potentials. Therefore, presumably, the mechanism of spike suppression by HFS might be a depolarization block generated within neuronal membranes. The finding of the study provides important insight into the development of novel closedloop stimulation patterns of DBS in treating epilepsy. 2016 Vol. 35 (1): 79-87 [Abstract] ( 473 ) HTML (1 KB)  PDF (2369 KB)  ( 566 ) 88 Study on the in vivo Degradation  and in vitro Biocompatibility of Spider Silk Protein Composite Material Small Diameter Vascular Scaffold Zhao Liang1,2 Chen Hongli1 Wang Mian1 Xie Liqin1  Xu Yanli1 He Meng1 Feng Zhiwei1 Li Min1* DOI: 10.3969/j.issn.0258-8021.2016.01.011 The in vivo degradation performance and in vitro biocompatibility of small diameter vascular scaffold made of spider silk protein composite material was evaluated for clinical application. RGDrecombinant spider silk protein (pNSR16), polycaprolactone (PCL), chitosan (CS) and gelatin (Gt) were blended to prepare spider silk protein composite material (pNSR16/PCL/CS)/(pNSR16/PCL/Gt) that was used for the fabrication of small diameter vascular scaffold using electrospinning technique. The scaffold was implanted into the muscle tissue of SD rat leg. The degradation property in vivo was evaluated by HE staining. The effect of scaffold extract on the mesenchymal stem cell colony formation, mitotic index, trypan blue dye exclusion rate, cytotoxicity and cell cycle were analyzed to evaluate the biocompatibility of the scaffold. During the implantation period the scaffold degraded continually, showing obvious fiber broken. The weight loss rate was 20.3% after 12 weeks of implantation, and the degradation rate was significantly higher than that of (PCL/CS)/(PCL/Gt) scaffold that degraded 13.2% after 12 weeks of implantation. When cultivated with of the extract of (pNSR16/PCL/CS)/(pNSR16/PCL/Gt) scaffold, the colony formation rate, average colony area and mitotic index of rat bone marrow MSC were significantly higher than that with the extract of (PCL/CS)/(PCL/Gt) scaffold. The toxicity level of scaffold was less than level 1. The trypan blue dye exclusion rate for MSCs was greater than 95% in the extract of the composite scaffold,. After 48 h incubation with the extract, G0/1 phase ratio of cells was reduced, S and G2/M phase ratio was increased. The in vivo degradation and in vitro biocompatibility of scaffold made of spider silk protein composite material were acceptable, showing certain feasibility in clinical application. 2016 Vol. 35 (1): 88-95 [Abstract] ( 502 ) HTML (1 KB)  PDF (3270 KB)  ( 691 ) 96 A Review of Experimental Paradigms in Visual Event-Related Potential-Based Brain Computer Interfaces Ma Zheng  Qiu Tianshuang* DOI: 10.3969/j.issn.0258-8021.2016.01.012 A brain computer interface (BCI) makes a pathway between the human brain and the ambient environment, making it possible to control external devices directly by brain. The experimental paradigm is an important aspect for the BCI research, through which the brain signal features required for the classification of the BCI are elicited. In recent years, numerous studies on experimental paradigms have been carried out to improve the performance of BCI. This article reviewed the current status of studies on experimental paradigms of the visual event-related potential based BCI, including paradigm configuration, pattern of stimulus presentation, stimulus type, language model, and hybrid BCI. The challenges and future directions were discussed as well. 2016 Vol. 35 (1): 96-102 [Abstract] ( 761 ) HTML (1 KB)  PDF (3031 KB)  ( 1416 ) 105 Recent Advances of Nanozymes in Glucose Detection Luo Cheng1  Li Yan1  Long Qiwen2Long Jiangang3* DOI: 10.3969/j.issn.0258-8021.2016.01.013 Instant and accurate detection of glucose level in blood and urine is of great significance to the early diagnosis and glucose monitoring of diabetes. Since gold nanocluster was found to have intrinsic phosphotransferaselike catalytic activity in 2004, various enzymelike activities were reported in nanomaterials (nanozymes), such as peroxidase, catalase, superoxide dismutase and oxidase. Compared with natural enzymes, nanozymes are of low cost, easy to be prepared, stored and transported, resistant to harsh conditions. Application of nanozymes in glucose detection will prospectively reduce the costs and improve the stability. The recent advances of various nanozymes including nanoparticles of metal, metal oxides, metal sulfides, carbon based materials and composite materials were introduced with emphasis on their advantages over natural enzymes, limits in the detection and linear working range in glucose detection. Challenges and prospects regarding the nanozyme research were also outlined in this review. 2016 Vol. 35 (1): 105-113 [Abstract] ( 541 ) HTML (1 KB)  PDF (1222 KB)  ( 1190 ) 114 Multi-Layer Adjusted Similarity Coefficient Algorithm Based on Photometric- Method in Microbial Identification Zhang Shaokang   Lin Yong* DOI: 10.3969/j.issn.0258-8021.2016.01.014 2016 Vol. 35 (1): 114-118 [Abstract] ( 323 ) HTML (1 KB)  PDF (1077 KB)  ( 369 ) 119 The Analysis of Stress on Knee Cartilage in Different Flexion Angles During Riding Ma Xuemei1  Zhang Chunqiu1*Gao Lilan1  Ye Jinduo1  Zhang Xizheng2 DOI: 10.3969/j.issn.0258-8021.2016.01.015 2016 Vol. 35 (1): 119-123 [Abstract] ( 478 ) HTML (1 KB)  PDF (8217 KB)  ( 510 ) 124 A Feasibility Study of Low Frequency Rotating Magnetic Field in the Treatment of High Altitude Polycythemia Guo Dalong1  Yang Jun1  Luo Yongchang1  Yu Jie2  Luo Chenyu3  Cao Zhengtao1#* DOI: 10.3969/j.issn.0258-8021.2016.01.016 2016 Vol. 35 (1): 124-127 [Abstract] ( 337 ) HTML (1 KB)  PDF (2064 KB)  ( 598 )

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