A feedback model of visual attention

Feedback connections are a prominent feature of cortical anatomy and are likely to have significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research

Exploring the functional significance of dendritic inhibition in cortical pyramidal cells

Inhibitory synapses contacting the soma and axon initial segment are commonly presumed to participate in shaping the response properties of cortical pyramidal cells. Such an inhibitory mechanism has been explored in numerous computational models. However, the majority of inhibitory synapses target the dendrites of pyramidal cells, and recent physiological data suggests that this dendritic inhibition affects tuning properties. We describe a model that can be used to investigate the role of dendritic inhibition in the competition between neurons. With this model we demonstrate that dendritic inhibition significantly enhances the computational and representational properties of neural networks

Pre-integration lateral inhibition enhances unsupervised learning

A large and influential class of neural network architectures use post-integration lateral inhibition as a mechanism for competition. We argue that these algorithms are computationally deficient in that they fail to generate, or learn, appropriate perceptual representations under certain circumstances. An alternative neural network architecture is presented in which nodes compete for the right to receive inputs rather than for the right to generate outputs. This form of competition, implemented through pre-integration lateral inhibition, does provide appropriate coding properties and can be used to efficiently learn such representations. Furthermore, this architecture is consistent with both neuro-anatomical and neuro-physiological data. We thus argue that pre-integration lateral inhibition has computational advantages over conventional neural network architectures while remaining equally biologically plausible

A feedback model of perceptual learning and categorisation

Top-down, feedback, influences are known to have significant effects on visual information processing. Such influences are also likely to affect perceptual learning. This article employs a computational model of the cortical region interactions underlying visual perception to investigate possible influences of top-down information on learning. The results suggest that feedback could bias the way in which perceptual stimuli are categorised and could also facilitate the learning of sub-ordinate level representations suitable for object identification and perceptual expertise

Formation of Ti–Zr–Cu–Ni bulk metallic glasses

Formation of bulk metallic glass in quaternary Ti–Zr–Cu–Ni alloys by relatively slow cooling from the melt is reported. Thick strips of metallic glass were obtained by the method of metal mold casting. The glass forming ability of the quaternary alloys exceeds that of binary or ternary alloys containing the same elements due to the complexity of the system. The best glass forming alloys such as Ti34Zr11Cu47Ni8 can be cast to at least 4-mm-thick amorphous strips. The critical cooling rate for glass formation is of the order of 250 K/s or less, at least two orders of magnitude lower than that of the best ternary alloys. The glass transition, crystallization, and melting behavior of the alloys were studied by differential scanning calorimetry. The amorphous alloys exhibit a significant undercooled liquid region between the glass transition and first crystallization event. The glass forming ability of these alloys, as determined by the critical cooling rate, exceeds what is expected based on the reduced glass transition temperature. It is also found that the glass forming ability for alloys of similar reduced glass transition temperature can differ by two orders of magnitude as defined by critical cooling rates. The origins of the difference in glass forming ability of the alloys are discussed. It is found that when large composition redistribution accompanies crystallization, glass formation is enhanced. The excellent glass forming ability of alloys such as Ti34Zr11Cu47Ni8 is a result of simultaneously minimizing the nucleation rate of the competing crystalline phases. The ternary/quaternary Laves phase (MgZn2 type) shows the greatest ease of nucleation and plays a key role in determining the optimum compositions for glass formation

Hand-held self-maneuvering unit Patent

Hand-held maneuvering unit for propulsion and attitude control of astronauts in zero or reduced gravity environmen

A conceptual approach for noncontact calorimetry in space

A concept is developed and described which allows to measure the heat capacity and the effective thermal conductivity of stable and undercooled liquid metals and alloys in an electromagnetic levitation apparatus. We propose to use an ac pulse heating method which is used nowadays as a standard technique for precision measurement of low temperature heat capacities. The ideal process parameters including the drop diameter D, temperature T, and frequency of measurement ω can be optimized when the following relations hold for the external and internal relaxation time constants τ_1 and τ_2, respectively: ωτ_1≳10 and ωτ_2<0.1. Then heat capacity data can be obtained with an accuracy of better than 1% with D about 5 to 10 mm, T between 1200 and 1800 K and ω between 0.1 and 1 Hz for typical metals and alloys

Dendritic inhibition enhances neural coding properties.

The presence of a large number of inhibitory contacts at the soma and axon initial segment of cortical pyramidal cells has inspired a large and influential class of neural network model which use post-integration lateral inhibition as a mechanism for competition between nodes. However, inhibitory synapses also target the dendrites of pyramidal cells. The role of this dendritic inhibition in competition between neurons has not previously been addressed. We demonstrate, using a simple computational model, that such pre-integration lateral inhibition provides networks of neurons with useful representational and computational properties which are not provided by post-integration inhibition

Design analysis of ductile failure in dovetail connections

The static plastic collapse of ductile dovetail structures is investigated by three analysis methods: slip-line field (SLF) theory based on a sheet drawing model, finite element limit analysis, and linear elastic finite element analysis with adapted pressure vessel design stress linearization and categorization methods. A range of angles and heights are considered in the investigation. Three experimental test cases are also presented. The limit analysis results are found to give the best comparison with the limited experimental results, indicating similar collapse loads and modes of ductile collapse. The SLF solution is found to give conservative but useful failure loads for small dovetail angles but, at angles greater than 30°, the solution is not generally conservative. The pressure vessel design by the analysis stress categorization procedure was adapted for dovetail analysis and was found to give reasonably conservative collapse loads in most cases. However, the procedure requires the designer to consider a number of different stress classification lines to ensure that a conservative collapse load is identified. It is concluded that the finite element limit analysis approach provides the best and most direct route to calculating the allowable load for the joint and is the preferred method when appropriate finite element analysis facilities are available