Investigation of additives for improvement of adhesive and elastomer performance Final report

Improvement additives for adhesive and elastomer performanc

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

Computations in the deep vs superficial layers of the cerebral cortex

A fundamental question is how the cerebral neocortex operates functionally, computationally. The cerebral neocortex with its superficial and deep layers and highly developed recurrent collateral systems that provide a basis for memory-related processing might perform somewhat different computations in the superficial and deep layers. Here we take into account the quantitative connectivity within and between laminae. Using integrate-and-fire neuronal network simulations that incorporate this connectivity, we first show that attractor networks implemented in the deep layers that are activated by the superficial layers could be partly independent in that the deep layers might have a different time course, which might because of adaptation be more transient and useful for outputs from the neocortex. In contrast the superficial layers could implement more prolonged firing, useful for slow learning and for short-term memory. Second, we show that a different type of computation could in principle be performed in the superficial and deep layers, by showing that the superficial layers could operate as a discrete attractor network useful for categorisation and feeding information forward up a cortical hierarchy, whereas the deep layers could operate as a continuous attractor network useful for providing a spatially and temporally smooth output to output systems in the brain. A key advance is that we draw attention to the functions of the recurrent collateral connections between cortical pyramidal cells, often omitted in canonical models of the neocortex, and address principles of operation of the neocortex by which the superficial and deep layers might be specialized for different types of attractor-related memory functions implemented by the recurrent collaterals. [Abstract copyright: Copyright © 2017 Elsevier Inc. All rights reserved.

An Investigation of the Drag Characteristics of a Tailless Delta-Wing Airplane in Flight, Including Comparison with Wind-Tunnel Data

A series of flight tests were conducted to determine the lift and drag characteristics of an F4D-1 airplane over a Mach number range of 0.80 to 1.10 at an altitude of 40,000 feet. Apparently satisfactory agreement was obtained between the flight data and results from wind-tunnel tests of an 0.055-scale model of the airplane. Further tests show the apparent agreement was a consequence of the altitude at which the first tests were made

An evaluation of two cooling-air ejectors in flight at transonic speeds

Flight tests conducted on the YF-93 airplane afforded an opportunity to evaluate two cooling-air ejectors of widely different geometry. One ejector had a diameter ratio (fuselage-exit diameter divided by tail-pipe diameter) of 1.58 and a spacing ratio (distance from tail-pipe exit to fuselage exit divided by tail-pipe diameter) of 0.73 while the other ejector had a diameter ratio of 1.33 and a spacing ratio of 0.30. The larger tail exhibited poor net thrust performance due to excessive quantity of secondary air flow. The second engine-ejector combination had superior characteristics; however, an undesirable characteristic existed in that a region of reversed flow was present in the exit. This reversed flow caused a decrease in the performance of the ejector. Correlation of the flight data with cold-jet-model ejector data has demonstrated to what extent the model tests can be used as a design tool. When comparing the ejector with reversed flow with the model tests, it was necessary to consider the effect the reversed flow had on reducing the effective diameter ratio. Airplane drag measurements as determined for the widely different configurations indicated a good over-all precision for the method used in this investigation

A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks

Understanding how the dynamics of a neural network is shaped by the network structure, and consequently how the network structure facilitates the functions implemented by the neural system, is at the core of using mathematical models to elucidate brain functions. This study investigates the tracking dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of neuronal recurrent interactions, CANNs can hold a continuous family of stationary states. They form a continuous manifold in which the neural system is neutrally stable. We systematically explore how this property facilitates the tracking performance of a CANN, which is believed to have clear correspondence with brain functions. By using the wave functions of the quantum harmonic oscillator as the basis, we demonstrate how the dynamics of a CANN is decomposed into different motion modes, corresponding to distortions in the amplitude, position, width or skewness of the network state. We then develop a perturbative approach that utilizes the dominating movement of the network's stationary states in the state space. This method allows us to approximate the network dynamics up to an arbitrary accuracy depending on the order of perturbation used. We quantify the distortions of a Gaussian bump during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable and the reaction time for the network to catch up with an abrupt change in the stimulus.Comment: 43 pages, 10 figure