Statistical Properties of Single and Competing Non-Linear Fast-Slow Oscillators in Noise

Statistical properties offast-slow Ellias-Grossberg oscillators are studied in response to deterministic and noisy inputs. Oscillatory responses remain stable in noise due to the slow inhibitory variable, which establishes an adaptation level that centers the oscillatory responses of the fast excitatory variable to deterministic and noisy inputs. Competitive interactions between oscillators improve the stability in noise. Although individual oscillation amplitudes decrease with input amplitude, the average to'tal activity increases with input amplitude, thereby suggesting that oscillator output is evaluated by a slow process at downstream network sites.Air Force Office of Scientific Research (F49620-92-J-0225); Defense Advanced Research Projects Agency (ONR N00014-92-J-4015); National Science Foundation (IRI-90-24877); Office of Naval Researc

Binding of Object Representations by Synchronous Cortical Dynamics Explains Temporal Order and Spatial Pooling Data

A key problem in cognitive science concerns how the brain binds together parts of an object into a coherent visual object representation. One difficulty that this binding process needs to overcome is that different parts of an object may be processed by the brain at different rates and may thus become desynchronized. Perceptual framing is a mechanism that resynchronizes cortical activities corresponding to the same retinal object. A neural network model based on cooperation between oscillators via feedback from a subsequent processing stage is presented that is able to rapidly resynchronize desynchronized featural activities. Model properties help to explain perceptual framing data, including psychophysical data about temporal order judgments. These cooperative model interactions also simulate data concerning the reduction of threshold contrast as a function of stimulus length. The model hereby provides a unified explanation of temporal order and threshold contrast data as manifestations of a cortical binding process that can rapidly resynchronize image parts which belong together in visual object representations.Air Force Office of Scientific Research (F49620-92-J-0225, F49620-92-J-0334, F49620-92-J-0499); Office of Naval Research (N00014-92- J-4015, N00014-91-J-4100

Temporal Dynamics of Binocular Disparity Processing with Corticogeniculate Interactions

A neural model is developed to probe how corticogeniculate feedback may contribute to the dynamics of binocular vision. Feedforward and feedback interactions among retinal, lateral geniculate, and cortical simple and complex cells are used to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing, including correct registration of disparity in response to dynamically changing stimuli, binocular summation of weak stimuli, and fusion of anticorrelated stimuli when they are delayed, but not when they are simultaneous. The model exploits dynamic rebounds between opponent ON and OFF cells that are due to imbalances in habituative transmitter gates. It shows how corticogeniculate feedback can carry out a top-down matching process that inhibits incorrect disparity response and reduces persistence of previously correct responses to dynamically changing displays.Air Force Office of scientific Research (F49620-92-J-0499, F49620-92-J-0334, F49620-92-J-0225); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409, N00014-92-J-4015); Natioanl Science Foundation (IRI-97-20333); Office of Naval Research (N00014-95-0657

Cortical Synchronization and Perceptual Framing

How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. Perceptual framing is a process that resynchronizes cortical activities corresponding to the same retinal object. A neural network model is presented that is able to rapidly resynchronize clesynchronized neural activities. The model provides a link between perceptual and brain data. Model properties quantitatively simulate perceptual framing data, including psychophysical data about temporal order judgments and the reduction of threshold contrast as a function of stimulus length. Such a model has earlier been used to explain data about illusory contour formation, texture segregation, shape-from-shading, 3-D vision, and cortical receptive fields. The model hereby shows how many data may be understood as manifestations of a cortical grouping process that can rapidly resynchronize image parts which belong together in visual object representations. The model exhibits better synchronization in the presence of noise than without noise, a type of stochastic resonance, and synchronizes robustly when cells that represent different stimulus orientations compete. These properties arise when fast long-range cooperation and slow short-range competition interact via nonlinear feedback interactions with cells that obey shunting equations.Office of Naval Research (N00014-92-J-1309, N00014-95-I-0409, N00014-95-I-0657, N00014-92-J-4015); Air Force Office of Scientific Research (F49620-92-J-0334, F49620-92-J-0225)

Temporal Dynamics of Binocular Display Processing with Corticogeniculate Interactions

A neural model of binocular vision is developed to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing. The model shows how feedforward and feedback interactions among LGN ON and OFF cells and cortical simple, complex, and hypercomplex cells can simulate binocular summation, the Pulfrich effect, and the fusion of delayed anticorrelated stereograms. Model retinal ON and OFF cells are linked by an opponent process capable of generating antagonistic rebounds from OFF cells after offset of an ON cell input. Spatially displaced ON and OFF cells excite simple cells. Opposite polarity simple cells compete before their half-wave rectified outputs excite complex cells. Complex cells binocularly match like-polarity simple cell outputs before pooling half-wave rectified signals frorn opposite polarities. Competitive feedback among complex cells leads to sharpening of disparity selectivity and normalizes cell activity. Slow inhibitory interneurons help to reset complex cells after input offset. The Pulfrich effect occurs because the delayed input from the one eye fuses with the present input from the other eye to create a disparity. Binocular summation occurs for stimuli of brief duration or of low contrast because competitive normalization takes time, and cannot occur for very brief or weak stimuli. At brief SOAs, anticorrelatecd stereograms can be fused because the rebound mechanism ensures that the present image to one eye can fuse with the afterimage from a previous image to the other eye. Corticogeniculate feedback embodies a matching process that enhances the speed and temporal accuracy of complex cell disparity tuning. Model mechanisms interact to control the stable development of sharp disparity tuning.Air Force Office of Scientific Research (F19620-92-J-0499, F49620-92-J-0334, F49620-92-J-0225); Office of Naval Research (N00014-95-1-0409, N00014-95-l-0657, N00014-92-J-1015, N00014-91-J-4100

An Evaluation of Touch and Pressure-Based Scrolling and Haptic Feedback for In-car Touchscreens

An in-car study was conducted to examine different input techniques for list-based scrolling tasks and the effectiveness of haptic feedback for in-car touchscreens. The use of physical switchgear on centre consoles is decreasing which allows designers to develop new ways to interact with in-car applications. However, these new methods need to be evaluated to ensure they are usable. Therefore, three input techniques were tested: direct scrolling, pressure-based scrolling and scrolling using onscreen buttons on a touchscreen. The results showed that direct scrolling was less accurate than using onscreen buttons and pressure input, but took almost half the time when compared to the onscreen buttons and was almost three times quicker than pressure input. Vibrotactile feedback did not improve input performance but was preferred by the users. Understanding the speed vs. accuracy trade-off between these input techniques will allow better decisions when designing safer in-car interfaces for scrolling applications

Synchronized Neural Activities: A Mechanism for Perceptual Framing

Variability in retinal and geniculate processing rate that is dependent on stimulus properties suggests that some later process can put parts corresponding to the same retinal image back into register. This resynchronization process is called perceptual framing. Here a neural network model of emergent boundary segmentation is used to show that synchronized cortical activities can subserve this role. Psychophysical results about the minimum delay between two visual stimuli that leads to the perception of temporal order can be explained and replicated with this model.Air Force Office of Scientific Research (F49620-92-J-0499, F49620-92-J-0225, F49620-92-J-0334); Office of Naval Research (N00014-92-J-4015, N00014-91-J-4100

Strategic trading and manipulation with spot market power

When a spot market monopolist has a position in a corresponding futures market, he has an incentive to deviate from the spot market optimum to make this position more profitable. Rational futures market makers take this into account when setting prices. We show that the monopolist, by randomizing his futures market position, can strategically exploit his market power at the expense of other futures market participants. Furthermore, traders without market power can manipulate futures prices by hiding their orders behind the monopolist's strategic trades. The moral hazard problem stemming from spot market power thus provides a venue for strategic trading and manipulation that parallels the adverse selection problem stemming from inside information. Klassifikation: D82, G1