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

UV and radiofrequency observations of Wolf-Rayet stars

Observations of W stars in the ultraviolet by OAO 2 and at 750 and 1400 MHz with the Green Bank telescopes are discussed. The emphasis is on the Green Bank observations of W stars with symmetric nebulae around them, their interpretation, and comparisons with other data. The implications regarding mass distribution, internal motion, flux density, ejected mass, velocity dispersion, and expanding envelopes are considered in detail

Ultraviolet investigations of cosmic X-ray sources and analogous objects

Data on the UV spectrum of the Crab nebula and on UV and radio frequency observations of Wolf-Rayet stars was analyzed. A description of TT Arietis is given. It is concluded that this object must be a double star, since it does not radiate like an ordinary photosphere or a single blackbody. Details of the spectrum are given

The UV spectrum of the Crab Nebula

Observations of the Crab nebula are described, which were made under the OAO 2/NASA guest-investigator program with WEP stellar photometers. The 10 foot-diameter focal plane diaphragm was ample enough to accept the 4 ft X 6 ft image. The logarithm of the integrated relative intensity per wavelength interval, corrected for sky background, and the rms error, from 11 passbands in the range 4250 to 1380 A, are given. No correction was given for polarization of light. The data were converted to logarithm of the flux density per frequency interval and plotted on scales of log nu (Hz) and of reciprocal microns with two adjustments

An unbiased X-ray sampling of stars within 25 parsecs of the Sun

A search of all of the Einstein Observatory IPC and HRI fields for untargeted stars in the Woolley, et al., Catalogue of the nearby stars is reported. Optical data and IPC coordinates, flux density F sub x, and luminosity L sub x, or upper limits, are tabulated for 126 single or blended systems, and HRI results for a few of them. IPC luminosity functions are derived for the systems, for 193 individual stars in the systems (with L sub x shared equally among blended components), and for 63 individual M dwarfs. These stars have relatively large X-ray flux densities that are free of interstellar extinction, because they are nearby, but they are otherwise unbiased with respect to the X-ray properties that are found in a defined small space around the Sun

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

IUE studies of X-ray K-M dwarfs

X-ray and ultraviolet data are presented with various optical data. Certain flare star and BY Draconis type variable star data are included. The results are discussed in terms of parameters of interest such as rotation and binary incidence. Deviations from correlations of properties that are found in the literature are noted. The fairly sizable number of red dwarfs that were observed inhance the value of the set of data. The coronae and the chromospheres of transition regions of the nearby stars are also considered

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

Magnetic Oscillations of a Fractional Hall Dot

We show that a quantum dot in the fractional Hall regime exhibits mesoscopic magnetic oscillations with a period which is a multiple of the period for free electrons. Our calculations are performed for parabolic quantum dots with hard-core electron-electron interactions and are exact in the strong field limit for $k_B T$ smaller than the fractional Hall gap. Explicit expressions are given for the temperature dependence of the amplitude of the oscillations.Comment: 11 pages, IUCM-004, plain te