9 resultados para utilization behavior, automatic action, ecological perception, violence, delusions

em National Center for Biotechnology Information - NCBI


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Leptin is a circulating protein involved in the long-term regulation of food intake and body weight. Cholecystokinin (CCK) is released postprandially and elicits satiety signals. We investigated the interaction between leptin and CCK-8 in the short-term regulation of food intake induced by 24-hr fasting in lean mice. Leptin, injected intraperitoneally (i.p.) at low doses (4–120 μg/kg), which did not influence feeding behavior for the first 3 hr postinjection, decreased food intake dose dependently by 47–83% during the first hour when coinjected with a subthreshold dose of CCK. Such an interaction was not observed between leptin and bombesin. The food-reducing effect of leptin injected with CCK was not associated with alterations in gastric emptying or locomotor behavior. Leptin–CCK action was blocked by systemic capsaicin at a dose inducing functional ablation of sensory afferent fibers and by devazepide, a CCK-A receptor antagonist but not by the CCK-B receptor antagonist, L-365,260. The decrease in food intake which occurs 5 hr after i.p. injection of leptin alone was also blunted by devazepide. Coinjection of leptin and CCK enhanced the number of Fos-positive cells in the hypothalamic paraventricular nucleus by 60%, whereas leptin or CCK alone did not modify Fos expression. These results indicate the existence of a functional synergistic interaction between leptin and CCK leading to early suppression of food intake which involves CCK-A receptors and capsaicin-sensitive afferent fibers.

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Postmitotic hair-cell regeneration in the inner ear of birds provides an opportunity to study the effect of renewed auditory input on auditory perception, vocal production, and vocal learning in a vertebrate. We used behavioral conditioning to test both perception and vocal production in a small Australian parrot, the budgerigar. Results show that both auditory perception and vocal production are disrupted when hair cells are damaged or lost but that these behaviors return to near normal over time. Precision in vocal production completely recovers well before recovery of full auditory function. These results may have particular relevance for understanding the relation between hearing loss and human speech production especially where there is consideration of an auditory prosthetic device. The present results show, at least for a bird, that even limited recovery of auditory input soon after deafening can support full recovery of vocal precision.

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Visual classification is the way we relate to different images in our environment as if they were the same, while relating differently to other collections of stimuli (e.g., human vs. animal faces). It is still not clear, however, how the brain forms such classes, especially when introduced with new or changing environments. To isolate a perception-based mechanism underlying class representation, we studied unsupervised classification of an incoming stream of simple images. Classification patterns were clearly affected by stimulus frequency distribution, although subjects were unaware of this distribution. There was a common bias to locate class centers near the most frequent stimuli and their boundaries near the least frequent stimuli. Responses were also faster for more frequent stimuli. Using a minimal, biologically based neural-network model, we demonstrate that a simple, self-organizing representation mechanism based on overlapping tuning curves and slow Hebbian learning suffices to ensure classification. Combined behavioral and theoretical results predict large tuning overlap, implicating posterior infero-temporal cortex as a possible site of classification.

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Ecological inference is the process of drawing conclusions about individual-level behavior from aggregate-level data. Recent advances involve the combination of statistical and deterministic means to produce such inferences.

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Studies on natural populations and harvesting biological resources have led to the view, commonly held, that (i) populations exhibiting chaotic oscillations run a high risk of extinction; and (ii) a decrease in emigration/exploitation may reduce the risk of extinction. Here we describe a simple ecological model with emigration/depletion that shows behavior in contrast to this. This model displays unusual dynamics of extinction and survival, where populations growing beyond a critical rate can persist within a band of high depletion rates, whereas extinction occurs for lower depletion rates. Though prior to extinction at lower depletion rates the population exhibits chaotic dynamics with large amplitudes of variation and very low minima, at higher depletion rates the population persists at chaos but with reduced variation and increased minima. For still higher values, within the band of persistence, the dynamics show period reversal leading to stability. These results illustrate that chaos does not necessarily lead to population extinction. In addition, the persistence of populations at high depletion rates has important implications in the considerations of strategies for the management of biological resources.

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The primate visual system offers unprecedented opportunities for investigating the neural basis of cognition. Even the simplest visual discrimination task requires processing of sensory signals, formation of a decision, and orchestration of a motor response. With our extensive knowledge of the primate visual and oculomotor systems as a base, it is now possible to investigate the neural basis of simple visual decisions that link sensation to action. Here we describe an initial study of neural responses in the lateral intraparietal area (LIP) of the cerebral cortex while alert monkeys discriminated the direction of motion in a visual display. A subset of LIP neurons carried high-level signals that may comprise a neural correlate of the decision process in our task. These signals are neither sensory nor motor in the strictest sense; rather they appear to reflect integration of sensory signals toward a decision appropriate for guiding movement. If this ultimately proves to be the case, several fascinating issues in cognitive neuroscience will be brought under rigorous physiological scrutiny.

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The collective behavior of interconnected spiking nerve cells is investigated. It is shown that a variety of model systems exhibit the same short-time behavior and rapidly converge to (approximately) periodic firing patterns with locally synchronized action potentials. The dynamics of one model can be described by a downhill motion on an abstract energy landscape. Since an energy landscape makes it possible to understand and program computation done by an attractor network, the results will extend our understanding of collective computation from models based on a firing-rate description to biologically more realistic systems with integrate-and-fire neurons.

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The primate visual motion system performs numerous functions essential for survival in a dynamic visual world. Prominent among these functions is the ability to recover and represent the trajectories of objects in a form that facilitates behavioral responses to those movements. The first step toward this goal, which consists of detecting the displacement of retinal image features, has been studied for many years in both psychophysical and neurobiological experiments. Evidence indicates that achievement of this step is computationally straightforward and occurs at the earliest cortical stage. The second step involves the selective integration of retinal motion signals according to the object of origin. Realization of this step is computationally demanding, as the solution is formally underconstrained. It must rely--by definition--upon utilization of retinal cues that are indicative of the spatial relationships within and between objects in the visual scene. Psychophysical experiments have documented this dependence and suggested mechanisms by which it may be achieved. Neurophysiological experiments have provided evidence for a neural substrate that may underlie this selective motion signal integration. Together they paint a coherent portrait of the means by which retinal image motion gives rise to our perceptual experience of moving objects.

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Irregularities in observed population densities have traditionally been attributed to discretization of the underlying dynamics. We propose an alternative explanation by demonstrating the evolution of spatiotemporal chaos in reaction-diffusion models for predator-prey interactions. The chaos is generated naturally in the wake of invasive waves of predators. We discuss in detail the mechanism by which the chaos is generated. By considering a mathematical caricature of the predator-prey models, we go on to explain the dynamical origin of the irregular behavior and to justify our assertion that the behavior we present is a genuine example of spatiotemporal chaos.