967 resultados para estrous synchronization


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Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP.

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We present evidence that large-scale spatial coherence of 40 Hz oscillations can emerge dynamically in a cortical mean field theory. The simulated synchronization time scale is about 150 ms, which compares well with experimental data on large-scale integration during cognitive tasks. The same model has previously provided consistent descriptions of the human EEG at rest, with tranquilizers, under anesthesia, and during anesthetic-induced epileptic seizures. The emergence of coherent gamma band activity is brought about by changing just one physiological parameter until cortex becomes marginally unstable for a small range of wavelengths. This suggests for future study a model of dynamic computation at the edge of cortical stability.

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We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.

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Anticipating synchronization has been recently proposed as a mechanism of interaction in dynamical systems which are able to bring about predictions of future states of a driver system. We suggest that an interesting insight into the anticipating synchronization can be obtained by the renormalization of the time scale in the driven system. Our approach directly links the feedback delay of the driven system with the renormalized time scale of the driven system, identifying the main component in the anticipating synchronization paradigm and suggesting an alternative method to generate the anticipating and the lagging synchronization.

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In the pregnant mouse uterus, small leucine-rich proteoglycans (SLRPs) are drastically remodeled within a few hours after fertilization, suggesting that ovarian hormone levels modulate their synthesis and degradation. In this study, we followed by immunoperoxidase approach, the presence of four members of the SLRP family (decorin, lumican, biglycan, and fibromodulin) in the uterine tissues along the estrous cycle of the mouse. All molecules except fibromodulin, which predominates in the myometrium, showed a striking modulation in their distribution in the endometrial stroma, following the rise in the level of estrogen. Moreover, notable differences in the distribution of SLRPs were observed between superficial and deep stroma, as well as between the internal and external layers of the myometrium. Only biglycan and fibromodulin were expressed in the luminal and glandular epithelia. All four SLRPs were found in cytoplasmic granules of mononucleated cells. The pattern of distribution of the immunoreaction for these molecules in the uterine tissues was found to be estrous cycle-stage dependent, suggesting that these molecules undergo ovarian hormonal control and probably participate in the preparation of the uterus for decidualization and embryo implantation. In addition, this and previous results from our laboratory suggest the existence of two subpopulations of endometrial fibroblasts that may be related to the centrifugal development of the decidua. Anat Rec, 292:138-153, 2009. (c) 2008 Wiley-Liss, Inc.

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In this series of papers, we study issues related to the synchronization of two coupled chaotic discrete systems arising from secured communication. The first part deals with uniform dissipativeness with respect to parameter variation via the Liapunov direct method. We obtain uniform estimates of the global attractor for a general discrete nonautonomous system, that yields a uniform invariance principle in the autonomous case. The Liapunov function is allowed to have positive derivative along solutions of the system inside a bounded set, and this reduces substantially the difficulty of constructing a Liapunov function for a given system. In particular, we develop an approach that incorporates the classical Lagrange multiplier into the Liapunov function method to naturally extend those Liapunov functions from continuous dynamical system to their discretizations, so that the corresponding uniform dispativeness results are valid when the step size of the discretization is small. Applications to the discretized Lorenz system and the discretization of a time-periodic chaotic system are given to illustrate the general results. We also show how to obtain uniform estimation of attractors for parametrized linear stable systems with nonlinear perturbation.

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Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial Visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.

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Chaotic synchronization has been discovered to be an important property of neural activities, which in turn has encouraged many researchers to develop chaotic neural networks for scene and data analysis. In this paper, we study the synchronization role of coupled chaotic oscillators in networks of general topology. Specifically, a rigorous proof is presented to show that a large number of oscillators with arbitrary geometrical connections can be synchronized by providing a sufficiently strong coupling strength. Moreover, the results presented in this paper not only are valid to a wide class of chaotic oscillators, but also cover the parameter mismatch case. Finally, we show how the obtained result can be applied to construct an oscillatory network for scene segmentation.

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Synchronization and chaos play important roles in neural activities and have been applied in oscillatory correlation modeling for scene and data analysis. Although it is an extensively studied topic, there are still few results regarding synchrony in locally coupled systems. In this paper we give a rigorous proof to show that large numbers of coupled chaotic oscillators with parameter mismatch in a 2D lattice can be synchronized by providing a sufficiently large coupling strength. We demonstrate how the obtained result can be applied to construct an oscillatory network for scene segmentation. (C) 2007 Elsevier B.V. All rights reserved.

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Apesar de diversos modelos assumirem que os preços não se ajustam sincronizadamente, tanto a evidência empírica quanto a teórica são ambíguas. Este trabalho tem por objetivo identificar o comportamento dos reajustes de preço, analisando uma extensa base de dados brasileira. Foi encontrada uma evidência de escalonamento, mas quanto mais agregado são os dados, mais perto da sincronização perfeita eles estão. A economia brasileira também mostrou um alto grau de heterogeneidade, tanto na frequência quanto na sincronização dos ajustes de preço entre os produtos, as quais ainda variam com a taxa de inflação.

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The elevated T-maze is an animal anxiety model which can discriminate between anxiety-like and fear-like behaviors. The estrous cycle is an important variable of the response in animal anxiety tests and is known to affect other models. The aim of the present study was to investigate the influence of the estrous cycle on behavior displayed in the elevated T-maze test. Seventeen male and 60 female rats were submitted to one session in this test, with the females being screened for the estrous cycle and divided into groups according to the various phases. The elevated T-maze had three arms of equal dimensions (50 cm x 10 cm), one enclosed by 40-cm high walls and perpendicular to the others, the apparatus being elevated 50cm above the floor. Each rat was placed in the end of the enclosed arm and the latency for it to leave this arm was recorded. These measurements were repeated three times separated by 30-s intervals (passive avoidance). After trial 3, each rat was placed at the distal end of the right open arm and the latency to exit this arm was recorded. Whenever latencies were greater than 300 s the trial was finished. The results demonstrated females in diestrus exhibited anxiety-like behaviors while females in metaestrus behaved in a similar way as the males. There were no differences between groups in fear-like behaviors. The results also indicate the elevated T-maze to be a sensitive test to measure anxiety. (C) 2004 Elsevier B.V. All rights reserved.