998 resultados para Hippocampus erectus complex


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Learned association between drugs of abuse and context is essential for the formation of drug conditioned place preference (CPP), which is believed to engage many brain regions including hippocampus, and nucleus accumbens (NAc). The underlying mechanisms

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Long term potentiation in hippocampus, evoked by high-frequency stimulation, is mediated by two major glutamate receptor subtypes, alpha-amino-3-hydroxyl-5-methyl-4-isoxazole propionate receptors and N-methyl-D-aspartate receptors. Receptor subunit compos

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Healthy siblings of schizophrenia patients have an almost 9-fold higher risk for developing the illness than the general population. Disruption of white matter (WM) integrity as indicated by reduced fractional anisotropy (FA) derived from diffusion tensor

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Chronic exposure to morphine can induce drug addiction and neural injury, but the exact mechanism is not fully understood. Here we show that morphine induces autophagy in neuroblastoma SH-SY5Y cells and in the rat hippocampus. Pharmacological approach shows that this effect appears to be mediated by PTX-sensitive G protein-coupled receptors signaling cascade. Morphine increases Beclin 1 expression and reduces the interaction between Beclin 1 and Bcl-2, thus releasing Beclin 1 for its pro-autophagic activity. Bcl-2 overexpression inhibits morphine-induced autophagy, whereas knockdown of Beclin 1 or knockout of ATG5 prevents morphine-induced autophagy. In addition, chronic treatment with morphine induces cell death, which is increased by autophagy inhibition through Beclin 1 RNAi. Our data are the first to reveal that Beclin 1 and ATG5 play key roles in morphine-induced autophagy, which may contribute to morphine-induced neuronal injury.

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Although Southeast Asia is a global biodiversity hotspot, the tempo and mode of avian diversification there has not been well studied. We investigated the history of the diversification of an endemic Asian tropical bird, the Black-browed Barbet Megalaima

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A novel method for modelling the statistics of 2D photographic images useful in image restoration is defined. The new method is based on the Dual Tree Complex Wavelet Transform (DT-CWT) but a phase rotation is applied to the coefficients to create complex coefficients whose phase is shift-invariant at multiscale edge and ridge features. This is in addition to the magnitude shift invariance achieved by the DT-CWT. The increased correlation between coefficients adjacent in space and scale provides an improved mechanism for signal estimation. © 2006 IEEE.

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In this paper a novel visualisation method for diffusion tensor MRI datasets is introduced. This is based on the use of Complex Wavelets in order to produce "stripy" textures which depict the anisotropic component of the diffusion tensors. Grey-scale pixel intensity is used to show the isotropic component. This paper also discusses enhancements of the technique for 3D visualisation. © 2004 IEEE.

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In this paper, we propose a watermarking algorithm in the complex wavelet domain. We then model watermarking as a communication process and show that the complex wavelet domain has relatively high capacity and is a potentially good domain for watermarking. Finally, a technique for registering geometrically distorted images, which is based on motion estimation in the wavelet domain, is described. The registration process can assist watermark detection in a watermarked image attacked by Stirmark, for example.

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Recently we have developed a new form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. This introduces limited redundancy (2 m:1 for m-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. In this paper we analyse why the new transform can be designed to be shift invariant, and describe how to estimate the accuracy of this approximation and design suitable filters to achieve this.

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A parametric study of spark ignition in a uniform monodisperse turbulent spray is performed with complex chemistry three-dimensional Direct Numerical Simulations in order to improve the understanding of the structure of the ignition kernel. The heat produced by the kernel increases with the amount of fuel evaporated inside the spark volume. Moreover, the heat sink by evaporation is initially higher than the heat release and can have a negative effect on ignition. With the sprays investigated, heat release occurs over a large range of mixture fractions, being high within the nominal flammability limits and finite but low below the lean flammability limit. The burning of very lean regions is attributed to the diffusion of heat and species from regions of high heat release, and from the spark, to lean regions. Two modes of spray ignition are reported. With a relatively dilute spray, nominally flammable material exists only near the droplets. Reaction zones are created locally near the droplets and have a non-premixed character. They spread from droplet to droplet through a very lean interdroplet spacing. With a dense spray, the hot spark region is rich due to substantial evaporation but the cold region remains lean. In between, a large surface of flammable material is generated by evaporation. Ignition occurs there and a large reaction zone propagates from the rich burned region to the cold lean region. This flame is wrinkled due to the stratified mixture fraction field and evaporative cooling. In the dilute spray, the reaction front curvature pdf contains high values associated with single droplet combustion, while in the dense spray, the curvature is lower and closer to the curvature associated with gaseous fuel ignition kernels. © 2011 The Combustion Institute.

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In this paper, a novel cortex-inspired feed-forward hierarchical object recognition system based on complex wavelets is proposed and tested. Complex wavelets contain three key properties for object representation: shift invariance, which enables the extraction of stable local features; good directional selectivity, which simplifies the determination of image orientations; and limited redundancy, which allows for efficient signal analysis using the multi-resolution decomposition offered by complex wavelets. In this paper, we propose a complete cortex-inspired object recognition system based on complex wavelets. We find that the implementation of the HMAX model for object recognition in [1, 2] is rather over-complete and includes too much redundant information and processing. We have optimized the structure of the model to make it more efficient. Specifically, we have used the Caltech 5 standard dataset to compare with Serre's model in [2] (which employs Gabor filter bands). Results demonstrate that the complex wavelet model achieves a speed improvement of about 4 times over the Serre model and gives comparable recognition performance. © 2011 IEEE.