Flight experience with the Ogee wing at low speed

Flight test of ogee wing at low speeds - flight characteristics and landing approach speed evaluatio

The texture and taste of food in the brain

Oral texture is represented in the brain areas that represent taste, including the primary taste cortex, the orbitofrontal cortex, and the amygdala. Some neurons represent viscosity, and their responses correlate with the subjective thickness of a food. Other neurons represent fat in the mouth, and represent it by its texture not by its chemical composition, in that they also respond to paraffin oil and silicone in the mouth. The discovery has been made that these fat-responsive neurons encode the coefficient of sliding friction and not viscosity, and this opens the way for the development of new foods with the pleasant mouth feel of fat and with health-promoting designed nutritional properties. A few other neurons respond to free fatty acids (such as linoleic acid), do not respond to fat in the mouth, and may contribute to some 'off' tastes in the mouth. Some other neurons code for astringency. Others neurons respond to other aspects of texture such as the crisp fresh texture of a slice of apple vs the same apple after blending. Different neurons respond to different combinations of these texture properties, oral temperature, taste, and in the orbitofrontal cortex to olfactory and visual properties of food. In the orbitofrontal cortex, the pleasantness and reward value of the food is represented, but the primary taste cortex represents taste and texture independently of value. These discoveries were made in macaques that have similar cortical brain areas for taste and texture processing as humans, and complementary human functional neuroimaging studies are described. This article is protected by copyright. All rights reserved. [Abstract copyright: This article is protected by copyright. All rights reserved.

Representational capacity of a set of independent neurons

The capacity with which a system of independent neuron-like units represents a given set of stimuli is studied by calculating the mutual information between the stimuli and the neural responses. Both discrete noiseless and continuous noisy neurons are analyzed. In both cases, the information grows monotonically with the number of neurons considered. Under the assumption that neurons are independent, the mutual information rises linearly from zero, and approaches exponentially its maximum value. We find the dependence of the initial slope on the number of stimuli and on the sparseness of the representation.Comment: 19 pages, 6 figures, Phys. Rev. E, vol 63, 11910 - 11924 (2000

A theoretical model of neuronal population coding of stimuli with both continuous and discrete dimensions

In a recent study the initial rise of the mutual information between the firing rates of N neurons and a set of p discrete stimuli has been analytically evaluated, under the assumption that neurons fire independently of one another to each stimulus and that each conditional distribution of firing rates is gaussian. Yet real stimuli or behavioural correlates are high-dimensional, with both discrete and continuously varying features.Moreover, the gaussian approximation implies negative firing rates, which is biologically implausible. Here, we generalize the analysis to the case where the stimulus or behavioural correlate has both a discrete and a continuous dimension. In the case of large noise we evaluate the mutual information up to the quadratic approximation as a function of population size. Then we consider a more realistic distribution of firing rates, truncated at zero, and we prove that the resulting correction, with respect to the gaussian firing rates, can be expressed simply as a renormalization of the noise parameter. Finally, we demonstrate the effect of averaging the distribution across the discrete dimension, evaluating the mutual information only with respect to the continuously varying correlate.Comment: 20 pages, 10 figure

The Relative Attenuation of Self-stimulation, Eating and Drinking Produced by Dopamine-Receptor Blockade

Spiroperidol, which blocks dopamine (DA) receptors, attenuated self-stimulation of the nucleus accumbens, septal area, hippocampus, anterior hypothalamus and ventral tegmental area. Dopamine is thus involved in self-stimulation of many sites (in addition to the lateral hypothalamus). The attenuation was not a simple motor impairment of the speed of bar-pressing in that the nucleus accumbens and septal self-stimulation rates were lower than those in treated animals self-stimulating at other sites (Experiment 1). Feeding was partly attenuated, and drinking was much less attenuated by the spiroperidol. Since the rats bar-pressed for brain- stimulation reward, chewed pellets to eat, and licked a tube to drink, dopamine-receptor blockade may attenuate complex motor responses most. Alternatively, the blockade could affect brain- stimulation reward more than the controls of eating, and these latter more than the controls of drinking (Experiment 2). In Experiment 3, feeding and drinking were equally and severely attenuated when rats had to bar-press to obtain food or water. The attenuation was to a level similar to that found for self-stimulation. These experiments suggest that dopamine receptor blockade impairs eating, drinking and self-stimulation by interfering with complex motor responses