用于选择视觉的数据和智能控制神经网络系统(英文)

在这篇论文中,我们提出了用于选择视觉的数据和智能控制的动态网络系统的神经实现过程。模型由数个相互作用的子系统构成,用于不同的处理。所有的神经子系统与信息和控制流程的倒序和顺序紧密相关。     

Visuomotor control within a distributed parieto-frontal network

The aim of this functional magnetic resonance imaging study was to investigate differences in visuomotor control with increasing task complexity. Twelve right-handed volunteers were asked to perform their signature under different degrees of visual control: internally generated movement with closed eyes, signing with open eyes, tracking the line of the projected signature forwards, and tracking the line of the projected signature backwards. There was a gradual onset and disappearance of activation within a distributed network. Parietal, lateral and medial frontal brain areas were activated during all conditions, confirming the involvement of a parieto-frontal system. The weight of activation shifted with increasing task complexity. Internally generated movements activated predominantly the inferior parietal lobule and the ventral premotor cortex, as well as the rostral cingulate area, pre-supplementary motor area (pre-SMA) and SMA proper. Opening the eyes reduced SMA and cingulate activation and activated increasingly the occipito-parietal areas with higher task complexity. Visually guided movements produced an activation predominantly in the superior parietal lobule and dorsal premotor cortex. This study bridges human activation studies with the results of neurophysiological studies with monkeys. It confirms a gradual transition of visuomotor control with increasing task complexity within a distributed parieto-frontal network.     

基于自适应小波神经网络的心电图检测法

自适应小波神经网络检测法就是利用小波函数取代通常神经网络中隐层的作用函数来实现的，通过网络的学习自适应地调整尺度参数和时移因子，提高了特征提取能力，因此，该网络可提高心电信号的检测率和可靠性。     

基于边界特征的乳腺肿瘤超声图像识别

通过对乳腺肿瘤边界特征的分析，得到边界的特征量似圆度，面积比率，长宽比组成的特征矢量，最后用反向传播人工神经网络（BP）的算法对经病理证实的119幅乳腺良、恶性肿块超声图像进行分类识别。BP神经网络对良、恶性肿瘤正确识别率分别为89．7％、73．5N。量化后的乳腺超声图像肿瘤轮廓特征结合BP神经网络可以比较有效的用于肿瘤的良、恶性识别。     

Normal aging decreases regional homogeneity of the motor areas in the resting state

Our knowledge about aging modulation of the central motor system remains sparse and contradictory. In the current study, we used functional MRI (fMRI) to study the aging influence on regional homogeneity of the motor-related brain areas in the resting state. We found that regional homogeneity in extensive motor regions, like the cingulate motor area, cerebellum, primary motor cortex, premotor area, supplementary motor area, thalamus, globus pallidus and putamen was significantly decreased in aged subjects. Our study indicates that normal aging process may disrupt the function of motor areas in the resting state, which may contribute to the declined motor ability in aged population.     

Detection of ophthalmic arterial doppler signals with Behcet disease using multilayer perceptron neural network

Doppler ultrasound is known as a reliable technique, which demonstrates the flow characteristics and resistance of ophthalmic arteries. In this study, ophthalmic arterial Doppler signals were obtained from 106 subjects, 54 of whom suffered from ocular Behcet disease while the rest were healthy subjects. Multilayer perceptron neural network (MLPNN) employing delta-bar-delta training algorithm was used to detect the presence of ocular Behcet disease. Spectral analysis of the ophthalmic arterial Doppler signals was performed by least squares (LS) autoregressive (AR) method for determining the MLPNN inputs. The MLPNN was trained with training set, cross validated with cross validation set and tested with testing set. All these data sets were obtained from ophthalmic arteries of healthy subjects and subjects suffering from ocular Behcet disease. Performance indicators and statistical measures were used for evaluating the MLPNN. The correct classification rate was 96.43% for healthy subjects and 93.75% for unhealthy subjects suffering from ocular Behcet disease. The classification results showed that the MLPNN employing delta-bar-delta training algorithm was effective to detect the ophthalmic arterial Doppler signals with Behcet disease.     

Intracellular localisation of Fv1

Retroviral resistance mediated by the murine Fv1 gene is believed to result from a direct interaction between the Fv1 gene product and the viral capsid protein. To study the mechanism of Fv1 action, the expression and intracellular localisation of the Fv1 protein were examined. Only very low levels of protein expression seem necessary for virus restriction but the site of expression appears crucial. Active Fv1 was found in association with tubules of the trans-Golgi network, whereas an inactive form was localised in the endoplasmic reticulum. We hypothesize that Fv1 is compartmentalised in the cell on the pathway taken by virus en route to the nucleus, suggesting that incoming virus must pass the trans-Golgi network during its transit to the nucleus.     

Comprehensive analysis of key lncRNAs in HCV-positive hepatocellular carcinoma

IntroductionHepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Despite the therapeutic advances in HCC in the past few decades, the mortality rate of HCC is still high. Hepatitis C (HCV) infection is one of the major etiological risk factors of HCCs. However, the underlying mechanisms of HCV-induced hepatocarcinogenesis remain largely unclear.Material and methodsOur study represented the comprehensive analysis of differentially expressed lncRNAs in HCV-positive HCC for the first time by analyzing the public dataset {"type":"entrez-geo","attrs":{"text":"GSE17856","term_id":"17856"}}GSE17856. Co-expression network and gene ontology (GO) analysis revealed the functions of those differentially expressed lncRNAs.ResultsWe identified 256 upregulated lncRNAs and 198 downregulated lncRNAs in HCV- positive HCC compared to the normal liver tissues. Co-expression network and GO analysis showed that these lncRNAs were involved in regulating metabolism, energy pathways, proliferation and the immune response. Seven lncRNAs (LOC341056, CCT6P1, PTTG3P, LOC643387, LOC100133920, C3P1 and C22orf45) were identified as key lncRNAs and co-expressed with more than 100 differentially expressed genes (DEGs) in HCV-related HCC. Kaplan-Meier analysis showed that higher expression levels of LOC643387, PTTG3P, LOC341056, CCT6P1 and lower expression levels of C3P1 and C22orf45 were associated with shorter survival time in the TCGA dataset.ConclusionsWe believe that this study can provide novel potential therapeutic and prognostic biomarkers for HCV-positive HCC.     

Microvasculature of the buffalo epididymis

The microvasculature of the water buffalo (Bubalus bubalis) epididymis was investigated using light (LM), scanning electron (SEM), and transmission electron (TEM) microscopy techniques. SEM analysis of the buffalo epididymis showed fenestrations that occupied ovoid inside the endothelium of the postcapillary venules located in the caput, corpus, and cauda. They varied in shape and dimension, but more importantly, they connected the venules of the blood vascular system to the capillaries of the peripheral lymphatic vascular system. Morphofunctional analysis of these connections suggests that the microvasculature of the buffalo epididymis plays a role in facilitating the circulation of biologically active substances, and the absorption and secretion processes necessary for the survival and maturation of spermatozoa. The lymphatic capillaries at the connection points formed a network of variously sized polygonal links. These capillaries then converged to form the precollector lymphatic vessels, which in turn converged with the larger vessels originating from the testis. It was further noted that in the capillary endothelium there were no fenestrations, and in the large veins there were many diverticula. These diverticula appear to play a role in the regulation of the seasonal variations of the blood reflux. In general, the microvascular architecture of the buffalo epididymis, particularly its connection to the lymphatic vascular system, appears to play an important role in the absorption and secretion processes of the epididymal epithelium. Anat Rec 266:58–68, 2002. © 2002 Wiley‐Liss, Inc.     

Nonlinearity identified by neural network models inP CO 2 control system in humans

The nonlinearity included in the P_{CO 2} control system in humans is evaluated using the degree of nonlinearity based on a difference of residuals. An autoregressive moving average (ARMA) model and neural networks (linear and nonlinear) are employed to model the system, and three types of network (Jordan, Elman and fully interconnected) are compared. As the Jordan-type linear network cannot approximate respiratory data accurately, the other two types and the ARMA model are used for the evaluation of the nonlinearity. The results of the evaluation indicate that the linear assumption for the P_{CO 2} control system is invalid for three subjects out of seven. In particular, strong nonlinearity was observed for two subjects.