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At least 1,711 records · Page 95

Does vector-free gravity simulate microgravity? Functional and morphologic attributes of clinorotated nerve and muscle grown in cell culture

Cocultured Xenopus neurons and myocytes were subjected to nonvectorial gravity by clinostat rotation to determine the effects of microgravity on cell development and communications. Observed effects included increases in the myocyte and its nuclear area, fragmentation of nucleoli, the appearance of neuritic aneurysms, decreased growth in the presence of trophic factors, and decreased yolk utilization. These effects were most notable at 1-10 rpm and depended on the onset and duration of rotation. It is found that, in microgravity, cell differentiation is altered by interference with cytoskeleton-related mechanisms. It is suggested that the alteration of the distribution of acetylcholine receptor aggregates on myocytes which occurs might indicate that microgravity affects brain development.

Gruener, Raphael↗

Simulation tests of the optimization method of Hopfield and Tank using neural networks

The method proposed by Hopfield and Tank for using the Hopfield neural network with continuous valued neurons to solve the traveling salesman problem is tested by simulation. Several researchers have apparently been unable to successfully repeat the numerical simulation documented by Hopfield and Tank. However, as suggested to the author by Adams, it appears that the reason for those difficulties is that a key parameter value is reported erroneously (by four orders of magnitude) in the original paper. When a reasonable value is used for that parameter, the network performs generally as claimed. Additionally, a new method of using feedback to control the input bias currents to the amplifiers is proposed and successfully tested. This eliminates the need to set the input currents by trial and error.

Paielli, Russell A.↗

Ionic mechanisms subserving mechanosensory transduction and neural integration in statocyst hair cells of Hermissenda

The neural processing of gravitational-produced sensory stimulation of statocyst hair cells in the nudibranch mollusk Hermissenda was studied. The goal in these studies was to understand how: gravireceptor neurons sense or transduce gravitational forces, gravitational stimulation is integrated so as to produce a graded receptor potential, and ultimately the generation of an action potential, and various neural adaptation phenomena which hair cells exhibit arise. The approach to these problems was primarily electrophysical.

Farley, Joseph↗

Feedforward, high density, programmable read only neural network based memory system

Neural network-inspired, nonvolatile, programmable associative memory using thin-film technology is demonstrated. The details of the architecture, which uses programmable resistive connection matrices in synaptic arrays and current summing and thresholding amplifiers as neurons, are described. Several synapse configurations for a high-density array of a binary connection matrix are also described. Test circuits are evaluated for operational feasibility and to demonstrate the speed of the read operation. The results are discussed to highlight the potential for a read data rate exceeding 10 megabits/sec.

Daud, Taher↗

Direct and indirect pathways to lamina I in the medulla oblongata and spinal cord of the cat

The pathways to lamina I in the medulla oblongata and spinal cord of the cat were traced using horse-radish-peroxidase (HRP) and autoradiographic techniques. The HRP results indicated that several neuronal cell groups in the brain stem and hypothalamus project to the spinal cord throughout its total length. The autoradiographic tracing results demonstrated that the strongest projections to lamina I are derived from the following four areas: the caudal nucleus raphe magnus (NRM), the ventral part of the caudal pontine and NRM, the contralaterally projecting lateral pontine or paralemniscal tegmentum, and the paraventricular nucleus of the hypothalamus. In addition, a limited, especially at lumbosacral levels, distinct projection to lamina I was found to originate in the most caudal part of the medullary tegmentum.

Holstege, Gert↗

Supervised learning of probability distributions by neural networks

Supervised learning algorithms for feedforward neural networks are investigated analytically. The back-propagation algorithm described by Werbos (1974), Parker (1985), and Rumelhart et al. (1986) is generalized by redefining the values of the input and output neurons as probabilities. The synaptic weights are then varied to follow gradients in the logarithm of likelihood rather than in the error. This modification is shown to provide a more rigorous theoretical basis for the algorithm and to permit more accurate predictions. A typical application involving a medical-diagnosis expert system is discussed.

Baum, Eric B.↗

Machine parts recognition using a trinary associative memory

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Awwal, Abdul Ahad S.↗

Chaos as a part of logical structure in neurodynamics

It is proposed that chaotic attractors incorporated in neural net models can represent classes of patterns in the same way in which a set of static attractors represent unrelated patterns. Therefore, chaotic states of neuron activity are associated with higher level cognitive processes such as generalization and abstraction.

Zak, Michail↗

Spike train generation and current-to-frequency conversion in silicon diodes

A device physics model is developed to analyze spontaneous neuron-like spike train generation in current driven silicon p(+)-n-n(+) devices in cryogenic environments. The model is shown to explain the very high dynamic range (0 to the 7th) current-to-frequency conversion and experimental features of the spike train frequency as a function of input current. The devices are interesting components for implementation of parallel asynchronous processing adjacent to cryogenically cooled focal planes because of their extremely low current and power requirements, their electronic simplicity, and their pulse coding capability, and could be used to form the hardware basis for neural networks which employ biologically plausible means of information coding.

Coon, D. D.↗

Analog Delta-Back-Propagation Neural-Network Circuitry

Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.

Eberhart, Silvio↗

Neural-Network Computer Transforms Coordinates

Numerical simulation demonstrated ability of conceptual neural-network computer to generalize what it has "learned" from few examples. Ability to generalize achieved with even simple neural network (relatively few neurons) and after exposure of network to only few "training" examples. Ability to obtain fairly accurate mappings after only few training examples used to provide solutions to otherwise intractable mapping problems.

Josin, Gary M.↗

Neural Network Development Tool (NETS)

Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

Baffes, Paul T.↗

Ground-state coding in partially connected neural networks

Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.

Baram, Yoram↗

Effect of contrast on the perception of direction of a moving pattern

A series of experiments examining the effect of contrast on the perception of moving plaids was performed to test the hypothesis that the human visual system determines the direction of a moving plaid in a two-staged process: decomposition into component motion followed by application of the intersection-of-contraints rule. Although there is recent evidence that the first tenet of the hypothesis is correct, i.e., that plaid motion is initially decomposed into the motion of the individual grating components, the nature of the second-stage combination rule has not yet been established. It was found that when the gratings within the plaid are of different contrast the preceived direction is not predicted by the intersection-of-constraints rule. There is a strong (up to 20 deg) bias in the direction of the higher-constrast grating. A revised model, which incorporates a contrast-dependent weighting of perceived grating speed as observed for one-dimensional patterns, can quantitatively predict most of the results. The results are then discussed in the context of various models of human visual motion processing and of physiological responses of neurons in the primate visual system.

Stone, L. S.↗

High compression image and image sequence coding

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Kunt, Murat↗

Parallel asynchronous hardware implementation of image processing algorithms

Research is being carried out on hardware for a new approach to focal plane processing. The hardware involves silicon injection mode devices. These devices provide a natural basis for parallel asynchronous focal plane image preprocessing. The simplicity and novel properties of the devices would permit an independent analog processing channel to be dedicated to every pixel. A laminar architecture built from arrays of the devices would form a two-dimensional (2-D) array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuron-like asynchronous pulse-coded form through the laminar processor. No multiplexing, digitization, or serial processing would occur in the preprocessing state. High performance is expected, based on pulse coding of input currents down to one picoampere with noise referred to input of about 10 femtoamperes. Linear pulse coding has been observed for input currents ranging up to seven orders of magnitude. Low power requirements suggest utility in space and in conjunction with very large arrays. Very low dark current and multispectral capability are possible because of hardware compatibility with the cryogenic environment of high performance detector arrays. The aforementioned hardware development effort is aimed at systems which would integrate image acquisition and image processing.

Coon, Darryl D.↗

Sensory conflict in motion sickness: An observer theory approach

Motion sickness is the general term describing a group of common nausea syndromes originally attributed to motion-induced cerebral ischemia, stimulation of abdominal organ afferent, or overstimulation of the vestibular organs of the inner ear. Sea-, car-, and airsicknesses are the most commonly experienced examples. However, the discovery of other variants such as Cinerama-, flight simulator-, spectacle-, and space sickness in which the physical motion of the head and body is normal or absent has led to a succession of sensory conflict theories which offer a more comprehensive etiologic perspective. Implicit in the conflict theory is the hypothesis that neutral and/or humoral signals originate in regions of the brain subversing spatial orientation, and that these signals somehow traverse to other centers mediating sickness symptoms. Unfortunately, the present understanding of the neurophysiological basis of motion sickness is far from complete. No sensory conflict neuron or process has yet been physiologically identified. To what extent can the existing theory be reconciled with current knowledge of the physiology and pharmacology of nausea and vomiting. The stimuli which causes sickness, synthesizes a contemporary Observer Theory view of the Sensory Conflict hypothesis are reviewed, and a revised model for the dynamic coupling between the putative conflict signals and nausea magnitude estimates is presented. The use of quantitative models for sensory conflict offers a possible new approach to improving the design of visual and motion systems for flight simulators and other virtual environment display systems.

Oman, Charles M.↗

In vitro differentiation of quail neural crest cells into sensory-like neuroblasts

Data are presented that demonstrate the ability of quail neural-crest embrionic cells grown as primary culture to differentiate in vitro into sensorylike neuroblasts. After 7-14 days of growth as primary culture, many of the putative sensory neuroblasts displayed substance P (SP)-like immunoreactivity and some exhibited histochemical carbonic anhydrase activity. Double staining experiments showed that the SP-like immunoreactive neuroblasts did not contain detectable levels of tyrosine hydroxylase or dopamine-beta-hydroxylase. The neuronal nature of the cultured sensorylike neuroblasts was further documented by double labeling for antibodies against the 68 kDa neurofilament polypeptide and substance P.

Sieber-Blum, Maya↗