978 resultados para Neural stimulation.


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Four types of neural networks which have previously been established for speech recognition and tested on a small, seven-speaker, 100-sentence database are applied to the TIMIT database. The networks are a recurrent network phoneme recognizer, a modified Kanerva model morph recognizer, a compositional representation phoneme-to-word recognizer, and a modified Kanerva model morph-to-word recognizer. The major result is for the recurrent net, giving a phoneme recognition accuracy of 57% from the si and sx sentences. The Kanerva morph recognizer achieves 66.2% accuracy for a small subset of the sa and sx sentences. The results for the word recognizers are incomplete.

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Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

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In this paper, we derive an EM algorithm for nonlinear state space models. We use it to estimate jointly the neural network weights, the model uncertainty and the noise in the data. In the E-step we apply a forwardbackward Rauch-Tung-Striebel smoother to compute the network weights. For the M-step, we derive expressions to compute the model uncertainty and the measurement noise. We find that the method is intrinsically very powerful, simple and stable.

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A self-produced tactile stimulus is perceived as less ticklish than the same stimulus generated externally. We used fMRI to examine neural responses when subjects experienced a tactile stimulus that was either self-produced or externally produced. More activity was found in somatosensory cortex when the stimulus was externally produced. In the cerebellum, less activity was associated with a movement that generated a tactile stimulus than with a movement that did not. This difference suggests that the cerebellum is involved in predicting the specific sensory consequences of movements, providing the signal that is used to cancel the sensory response to self-generated stimulation.

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This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.

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神经管闭合缺陷(NTDs)是一种严重的先天畸形疾病,在新生儿中有千分之一的发病率.神经管融合前后,多种组织参与形态发生运动.神经管一经融合,神经嵴细胞就会向背侧中线方向产生单极突出并向此方向迁移形成神经管的顶部.与此同时,神经管从腹侧开始发生辐射状切入以实现单层化.在此,我们在非洲爪蟾的移植体中机械阻断神经管的闭合以检测其细胞运动及随后的图式形成.结果显示神经管闭合缺陷的移植体不能形成单层化的神经管,并且神经嵴细胞滞留在侧面区域不能向背侧中线迁移,而对神经前体标记基因的检测显示神经管的背腹图式形成并未受到影响.以上结果表明神经管的融合对于辐射状切入和神经嵴细胞向背侧中线方向的迁移过程是必需的,而对于神经管的沿背腹轴方向的图式形成是非必需的.

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Regulation of neuronal gene expression is critical to nervous system development. REST (RE1-silencing transcription factor) regulates neuronal gene expression through interacting with a group of corepressor proteins including REST corepressors (RCOR). Here we show that Xenopus RCOR2 is predominantly expressed in the developing nervous system. Through a yeast two-hybrid screen, we isolated Xenopus ZMYND8 (Zinc finger and MYND domain containing 8) as an XRCOR2 interacting factor. XRCOR2 and XZMYND8 bind each other in co-immunoprecipitation assays and both of them can function as transcriptional repressors. XZMYND8 is co-expressed with XRCOR2 in the nervous system and overexpression of XZMYND8 inhibits neural differentiation in Xenopus embryos. These data reveal a RCOR2/ZMYND8 complex which might be involved in the regulation of neural differentiation. (C) 2010 Elsevier Inc. All rights reserved.

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The effect of AC and DC electric stimulations on the heart-rate and the entire body of Heteropneustis fossillis, Tilapia mossambica and Macrobrachium rosenbergii were studied and presented in kymograph tracings. The reaction of spinal cord in Puntius ticto, Heteropneustis fossilis and Tilapia mossambica to D. C. field was observed to find out its role in electric shocks. A test-check of the electrical resistance of a few species was also conducted. The effect of D. C. and A.C. on the body muscle was found to be the same as that in the case of frog. Different degrees of cardiac slowing were observed in AC and DC. Unbalanced galvanotropic movements were also noticed in spinal fishes.

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Cell-based therapies using embryonic stem cells (ESCs) in the treatment of neural disease will require the generation of homogenous donor neural progenitor (NP) populations. Here we describe an efficient culture system containing hepatocyte growth factor (HGF) and G5 supplement for the production of highly enriched (88.3% +/- 8.1%)populations of NPs from rhesus monkey ESCs. Additional purification resulted in NP preparations that were 98% nestin positive. Moreover, NPs, as monolayers or neurospheres, could be maintained for prolonged periods of time in media containing HGF+G5 or G5 alone. In vitro differentiation and in vivo transplantation assays showed that NPs could differentiate into neurons, astrocytes, and oligodendrocytes. The kinds and quantities of differentiated cells derived from NPs were closely correlated with their niches in vivo. Glial differentiation was predominant in periventricular areas, whereas cells migrating into the cortex were mostly neurons. Cell counts showed that 2 months after transplantation, approximately 25% of transplanted NPs survived and 65% - 80% of the surviving transplanted cells migrated along the ventricular wall or in a radial fashion. Subcloning demonstrated that several clonal lines derived from NPs expressed nestin and differentiated into three neural lineages in vitro and in rat brains in vivo. In contrast, some subcloned lines showed restricted differentiation both in vitro and in vivo in rat brains. These observations set the stage for obtaining highly enriched NPs and evaluating the efficacy of NP-based transplantation therapy in the nonhuman primate and will provide a platform for probing the molecular mechanisms that control neural induction.