The sleep-wake cycle in adult rats following pilocarpine-induced temporal lobe epilepsy

The relationship between sleep and epilepsy is both complex and clinically significant. Temporal lobe epilepsy (TLE) influences sleep architecture, while sleep plays an important role in facilitating and/or inhibiting possible epileptic seizures. The pilocarpine experimental model reproduces several features of human temporal lobe epilepsy and is one of the most widely used models in basic research. The aim of the present study was to characterize, behaviorally and electrophysiologically, the phases of sleep-wake cycles (SWC) in male rats with pilocarpine-induced epilepsy. Epileptic rats presented spikes in all phases of the SWC as well as atypical cortical synchronization during attentive wakefulness and paradoxical sleep. The architecture of the sleep-wake phases was altered in epileptic rats, as was the integrity of the SWC. Because our findings reproduce many relevant features observed in patients with epilepsy, this model is suitable to study sleep dysfunction in epilepsy. (C) 2009 Elsevier Inc. All rights reserved.

5-HT(1B) receptor in the suprachiasmatic nucleus of the common marmoset (Callithrix jacchus)

Serotonin (5-HT) is involved in the fine adjustments at several brain centers including the core of the mammal circadian timing system (CTS) and the hypothalamic suprachiasmatic nucleus (SCN). The SCN receives massive serotonergic projections from the midbrain raphe nuclei, whose inputs are described in rats as ramifying at its ventral portion overlapping the retinohypothalamic and geniculohypothalamic fibers. In the SCN, the 5-HT actions are reported as being primarily mediated by the 5-HT1 type receptor with noted emphasis for 5-HT(1B) subtype, supposedly modulating the retinal input in a presynaptic way. In this study in a New World primate species, the common marmoset (Callithrix jacchus), we showed the 5-HT(1B) receptor distribution at the dorsal SCN concurrent with a distinctive location of 5-HT-immunoreactive fibers. This finding addresses to a new discussion on the regulation and synchronization of the circadian rhythms in recent primates. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Watch-and-Comment as a Paradigm toward Ubiquitous Interactive Video Editing

The literature reports research efforts allowing the editing of interactive TV multimedia documents by end-users. In this article we propose complementary contributions relative to end-user generated interactive video, video tagging, and collaboration. In earlier work we proposed the watch-and-comment (WaC) paradigm as the seamless capture of an individual`s comments so that corresponding annotated interactive videos be automatically generated. As a proof of concept, we implemented a prototype application, the WACTOOL, that supports the capture of digital ink and voice comments over individual frames and segments of the video, producing a declarative document that specifies both: different media stream structure and synchronization. In this article, we extend the WaC paradigm in two ways. First, user-video interactions are associated with edit commands and digital ink operations. Second, focusing on collaboration and distribution issues, we employ annotations as simple containers for context information by using them as tags in order to organize, store and distribute information in a P2P-based multimedia capture platform. We highlight the design principles of the watch-and-comment paradigm, and demonstrate related results including the current version of the WACTOOL and its architecture. We also illustrate how an interactive video produced by the WACTOOL can be rendered in an interactive video environment, the Ginga-NCL player, and include results from a preliminary evaluation.

A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.

Blowout bifurcation and spatial mode excitation in the bubbling transition to turbulence

The transition to turbulence (spatio-temporal chaos) in a wide class of spatially extended dynamical system is due to the loss of transversal stability of a chaotic attractor lying on a homogeneous manifold (in the Fourier phase space of the system) causing spatial mode excitation Since the latter manifests as intermittent spikes this has been called a bubbling transition We present numerical evidences that this transition occurs due to the so called blowout bifurcation whereby the attractor as a whole loses transversal stability and becomes a chaotic saddle We used a nonlinear three-wave interacting model with spatial diffusion as an example of this transition (C) 2010 Elsevier B V All rights reserved

Bubbling transition to spatial mode excitation in an extended dynamical system

We investigated the transition to spatio-temporal chaos in spatially extended nonlinear dynamical systems possessing an invariant subspace with a low-dimensional attractor. When the latter is chaotic and the subspace is transversely stable we have a spatially homogeneous state only. The onset of spatio-temporal chaos, i.e. the excitation of spatially inhomogeneous modes, occur through the loss of transversal stability of some unstable periodic orbit embedded in the chaotic attractor lying in the invariant subspace. This is a bubbling transition, since there is a switching between spatially homogeneous and nonhomogeneous states with statistical properties of on-off intermittency. Hence the onset of spatio-temporal chaos depends critically both on the existence of a chaotic attractor in the invariant subspace and its being transversely stable or unstable. (C) 2008 Elsevier B.V. All rights reserved.

How complex a dynamical network can be?

Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen: (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes. (C) 2011 Elsevier B.V. All rights reserved.

The Schenberg data acquisition and analysis: results from its first commissioning run

The Mario Schenberg gravitational wave detector has started its commissioning phase at the Physics Institute of the University of Sao Paulo. We have collected almost 200 h of data from the instrument in order to check out its behavior and performance. We have also been developing a data acquisition system for it under a VXI System. Such a system is composed of an analog-to-digital converter and a GPS receiver for time synchronization. We have been building the software that controls and sets up the data acquisition. Here we present an overview of the Mario Schenberg detector and its data acquisition system, some results from the first commissioning run and solutions for some problems we have identified.

FAST, PARALLEL AND SECURE CRYPTOGRAPHY ALGORITHM USING LORENZ`S ATTRACTOR

A novel cryptography method based on the Lorenz`s attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if the nature of the chaotic system is known. The algorithm has been implemented in two versions: one sequential and slow and the other, parallel and fast. Our algorithm assures the integrity of the ciphertext (we know if it has been altered, which is not assured by traditional algorithms) and consequently its authenticity. Numerical experiments are presented, discussed and show the behavior of the method in terms of security and performance. The fast version of the algorithm has a performance comparable to AES, a popular cryptography program used commercially nowadays, but it is more secure, which makes it immediately suitable for general purpose cryptography applications. An internet page has been set up, which enables the readers to test the algorithm and also to try to break into the cipher.

Seeking for simplicity in complex networks

Complex networks can be understood as graphs whose connectivity properties deviate from those of regular or near-regular graphs, which are understood as being ""simple"". While a great deal of the attention so far dedicated to complex networks has been duly driven by the ""complex"" nature of these structures, in this work we address the identification of their simplicity. The basic idea is to seek for subgraphs whose nodes exhibit similar measurements. This approach paves the way for complementing the characterization of networks, including results suggesting that the protein-protein interaction networks, and to a lesser extent also the Internet, may be getting simpler over time. Copyright (C) EPLA, 2009