None of the above fit.
Abstract |
Frequently, a computer program requires input parameters to define a specific application prior to running it. For codes
that require few input parameters, the usual method to define these parameters is to store them in a ... |
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An enhanced neural network shell for application programs is disclosed. The user is prompted to enter in non-technical information about the specific problem type that the user wants solved by a neural network. The user also ... |
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An intelligent microsensor module (10, 100, 210, 300, 355, 410) is provided that can fuse data streams from a variety of sources and then locally determine the current state of the environment in which the intelligent ... |
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Introduction: This note describes some nonlinear networks which caD learn a spatial pattern, in "black and white," of arbitrary size and complexity. These networks are a special case of a collection of learning machines ~ ... |
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This note lists some psychological, physiological, and biochemical predictions that have been derived from simple psychological postu]ates. These psychological postulates have been used to derive a nev learning theory, 1-3 ... |
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1. Introduction. We study some systems of nonlinear functional-differential equations of the form(1)X(t)= A X(1) + B(Xi)X(t - r) + CO), t' 0,where X=(xi,, x„) is nonnegative, B(Xj) =jjB;j(t)jj is a matrixof nonlinear ... |
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Learning of patterns by neural networks obeying general rules of sensory transduction and of converting membrane potentials to spiking frequencies is considered. Any finite number of cellsA can sample a pattern playing on ... |
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This paper studies the variational systems of two closely related systemsof nonlinear difference-differential equations which arise in prediction- andlearning-theoretical applications ([1], [2], [31). The first system is ... |
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1. Introduction. This paper describes some networks 9R that can learn,simultaneously remember, and individually reproduce on demand any numberof spatiotemporal patterns (e.g., "motor sequences") of essentially arbitrary ... |
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1. Introduction. This note describes limiting and oscillatory fea-tures of some nonlinear functional-differential systems having appli-cations in learning and nonstationary prediction theory. The mainresults discuss systems ... |
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A mathematical model with both a psychological and neurophysiological interpretation is introduced to qualitatively explain data about serial learning of lists. Phenomenasuch as bowing, anchoring, chunking, backward ... |
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This paper makes some neurophysiological and biochemical predictionsconcerning transmitter production and release which are suggested bypsychological postulates. A main theme is the joint comrol of presynapticexcitatory ... |
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Many of our sensory and motor organs have linearly ordered components, for example the fingers on a hand, the tonotopic organization of the auditory system, the successivjeo ints on arms and legs,t he spine,e tc. This paper ... |
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Introduction: A previous note [l] introduced some systems of nonlinear functional-differential equations of the form X(t) = AX(t) + B(Xt)X(t - r) + C(t) i £ 0, where X~(xi, • - * , xn) is nonnegative, B(Xt) is a ... |
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1. INTRODUCTION: This paper considers various aspects of the global limiting and oscillatorybehavior of the following system of nonlinear differential equations.sx;(t) ... |
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A learning theory in continuous time is derived herein from simple psychologicalpostulates. The theory has an anatomical and neurophysiological interpretation interms of nerve cell bodies, axons, synaptic knobs, membrane ... |
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A real-time visual processing theory is used to analyze and explain a wide variety of perceptual grouping and segmentation phenomena, including the grouping of textured images, randomly defined images, and images built up ... |
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1. Introduction - This paper describes some networks ..lf that can learn, simultaneously remember,and perform individually upon demand any number of spatiotemporal patterns(e.g., "motor sequences" and "internal perceptual ... |
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Abstract |
Neural networks are introduced which can be taught by classical or instrumental conditioning to fire in response to arbitrary learned classes of patterns. The filters of output cells are biased by presetting cells whose ... |
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A real-time neural network model, called affective balance theory, is developed to explain many properties of decision making under risk that heretofore have been analyzed using formal algebraic models, notably prospect ... |
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A real-time visual processing theory is used to analyze real and illusory contour formation, contour and brightness interactions, neon color spreading, complementary color induction, and filling-in of discounted illuminants ... |
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Abstract |
Reeves and Sperling (1986) have developed an experimental paradigm and a model to explain how attention switching influences the, storage oftemporal-order information in short-term memory (STM), or working memory. The ... |
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Data and models about recognition and recall of words and non words are unified using a real-time network processing theory. Lexical decision and word frequency effect data are analyzed in terms of theoretical concepts that ... |
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A real-time neural network model is developed to explain data about the acquisition and extinction of conditioned excitors and inhibitors. Systematic computer simulations are described of a READ circuit, which joins together ... |
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Summary. A computational theory of how an observer parses a speech stream into context-sensitive language representations is described. It is shown how temporal lists of events can be chunked into unitized repre~ntations, ... |
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Possible dependencies of serial learning data on physiological parameters such as spiking thresholds, arousal level, and decay rate of potentials are considered in a rigorous learning model. Influence of these parameters on ... |
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The transformation of spatial patterns and their storage in short term memory by shunting neural networks are studied herein. Various mechanisms are described for real-time regulation of the amount of contrast with which a ... |
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Abstract |
Certain visual illusion occur in neural networks that are capable of storing partially contrasted enhanced spatial patterns in short term memory (STM), and whose feature detectors are interconnected by nontrivial ... |
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Abstract |
Simple psychological postulates are presented which are used to derivepossible anatomical and physiological substrates of operant conditioning.These substrates are compatible with much psychological data aboutoperants. A ... |
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This note describes laws for the anatomy, potentials, spiking rules, and transmitters of some networks of formal neurons that enable them to learn spatial patterns by Pavlovian conditioning. Applications to spacetime pattern ... |
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A theory is presented of how global visual interactions between depth, length, lightness, and form percepts can occur. The theory suggests how quantized activity patterns which reflect these visual properties can coherently ... |
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Some recent formal models of Pavlovian and instrumental conditioning contain internal paradoxes that restrict their predictive power. These paradoxes can be traced to an inadequate formulation of how mechanisms of ... |
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This paper studies the global dynamics of neurons, or neuron populations,in a recurrent on-center off-surround anatomy undergoing nonlinearshunting interactions. In such an anatomy, a given population excitesitself and ... |
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Some possible neural mechanisms of pattern discrimination are discussed, leading to neural networks which can discriminate any number of essentially arbitrarily complicated space-time patterns and activate cells which can ... |
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This paper describes new properties of competitive systems which arise in population biology, ecology, psychophysiology, and developmental biology. These properties yield a global method for analyzing the geometric design ... |
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This paper describes mechanisms of intracellular and intercellular adaptation that are due to spatial or temporal factors. The spatial mechanisms support self-regulating pattern formation that is capable of directing ... |
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This article reviews results on a learning theory that can be derived from simple psychological postulates and given a suggestive neurophysiological, anatomical, and biochemical interpretation. The neural networks described ... |
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Developmental mechanisms for tuning of visual cortex are derived from adult learning mechanisms: an adaptational property of shunting on-center off-surround networks that prevents saturation of parallel processed patterns at ... |
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A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations ... |
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Abstract |
The process whereby input patterns are transformed and stored by competitive cellular networks is considered. This process arises in such diverse subjects as the short-tenD storage of visual or language patterns by neural ... |
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Competition solves a universal problem about pattern processing by cellular systems. Competition allows cells to automatically retune their sensitivity to avoid noise and saturation effects. All competitive systems induce ... |
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A well-known process for adaptation and gain normalization is compared with the process described by S. Ullman and G. Schechtman (Proc. R. Soc. Lond. B 216, 299-313 (1982)). A neural interpretation of this process in terms ... |
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Abstract |
The following problem, in one form or another, has intrigued philosophers and scientists for hundreds of years: How do arbitrarily many individuals, populations, or states, each obeying unique and personal laws, ever succeed ... |
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Three experiments were conducted to evaluate the P300 component of the human evoked response as an index of bisensory information processing. On different blocks of trials, subjects were presented with auditory stimuli ... |
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The hypothesis has been advanced thatcertain schizophrenic patients are in acontinual state of overarousal, leading topoor attention, and perhaps to schizophrenicpunning (Kornetsky and Eliasson, 1969;Maher, 1968). ... |
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Abstract |
Neural networks are derived from psychological postulates about punishment and avoidance. The classical notion that drive reduction is reinforcing is replaced by a precise physiological alternative akin to Miller s ""Go"" ... |
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This paper develops a model wherein STM primacy as well as recency effects can occur. The STM primacy effects can be used to generate correct immediate recall of short lists that have not been coded in LTM. The properties of ... |
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Abstract |
Selective information processing in neural networks is studied through computer simulations of Pavlovian conditioning data. The model reproduces properties of blocking, inverted-U in learning as a function of interstimulus ... |
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Abstract |
Quantitative neural networks are derived from psychological postulates about punishment and avoidance. The classical notion that drive reduction is reinforcing is replaced by a precise physiological altetAative akin to ... |
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Abstract |
Data reporting correlated changes, due to learning, in the amplitudes and chronometry of several eventrelated potentials (ERPs) are compared to neural explanations and predictions of the adaptive resonance theory. The ERP ... |
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Abstract |
A real-time visual processing theory is developed to explain how three-dimensional form, color, and brightness perceptsa re coherently synthesized. The theory describeEhJo w several undamental uncertainty principles which ... |
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Abstract |
A real-time visual processing theory is developed to explain how three-dimensional form, color, and brightness percept. aJ re coherently synthesized. The theory describesh ow several fundamental uncertainty principles which ... |
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Abstract |
Functional and mechanistic comparisons are made between several network models of cognitive processing: competitive learning, interactive activation, adaptive resonance, and back propagation. The starting point of this ... |
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Abstract |
A massively parallel neural network architecture, called a masking field, is characterized through systematic computer simulations. A masking field is a multiple-scale self-similar automatically gain-controlled ... |
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Abstract |
Computer simulations of neural network processes fill an important methodological niche, permitting the investigation of questions not resolvable by physiological, behavioral, or formal approaches alone. Two types of network ... |
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Abstract |
A neural network model that controls behavioral timing is described and simulated. This model, called the Spectral Timing Model, controls a type of timing whereby an animal or robot can learn to wait for an expectedg oal by ... |
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Abstract |
neural network model ormotion segmentation by visual cortex is described. The model s properties are illustrated by simulating on the computer data concerning group and element apparent motion, including the tendency for ... |
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Abstract |
1. Introduction: The Inadequacy of Visual Modules This article discusses some implications for understanding vision of recent theoretical results concerning the neural architectures that subserve visual perception in humans ... |
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Abstract |
A real-time neural network model. called the vector-integration-to-endpoint( VITE) model is developed and used to simulate quantitatively behavioral and neural data about planned and passive arm movements.I nvariants of arm ... |
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Abstract |
Recent results towards development of a neural network architecture for general-purpose preattentive vision are summarized. The architecture contains two parallel subsystems, the boundary contour system (BCS) and the feature ... |
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Abstract |
A large body of data is reviewed to support a new theory of motion perception described by S. Grossberg and M. E. Rudd (1989). The Motion Boundary Contour System is used to explain classical and recent data about motion ... |
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Abstract |
A neural network model is described for adaptive control of arm movement trajectories during visually guided reaching. The model clarifies how a child, or infant robot, can learn to reach for objects that it sees. Piaget has ... |
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Abstract |
Working memory neural networks, called Sustained Temporal Order REcurrent (STORE) models, encode the invariant temporal order of sequential events in short-term memory (STM). Inputs to the networks may be presented with ... |
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Abstract |
This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This ... |
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Abstract |
A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to ... |
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Abstract |
A neural network model of global motion segmentation by visual cortex is described. Called the motion boundary contour system (BCS), the model clarifies how ambiguous local movements on a complex moving shape are actively ... |
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Abstract |
This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models ... |
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This article analyzes computational properties that clarify why the parallel cortical systems V1----V2, V1----MT, and V1----V2----MT exist for the perceptual processing of static visual forms and moving visual forms. The ... |
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Abstract |
The origin of the tri-phasic burst pattern, observed in the EMGs of opponent muscles during rapid self-terminated movements, has benn controversial. Here we show by computer simulation that the pattern emerges from ... |
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Abstract |
A neural network model of 3-D visual perception and figure-ground separation by visual cortex is intro¬duced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from ... |
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Abstract |
This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-1ntegration-To-Endpoint ... |
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Abstract |
A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal ... |
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Abstract |
This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to ... |
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Abstract |
This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other ... |
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Abstract |
A neural network model of synchronized oscillations in visual cortex is presented to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these ... |
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Abstract |
A model of pitch perception, called the spatial pitch network or SPINET model, is developed and analyzed. The model neurally instantiates ideas from the spectral pitch modeling literature and joins them to basic neural ... |
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Abstract |
Three computational rules are sufficient to generate model cortical maps that simulate the interrelated structure of cortical ocular dominance and orientation columns: a noise input. a spatial band passfilter. and ... |
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Abstract |
A neural model is developed of the neural circuitry in the reticular formation that is used to generate saccadic eye movements. The model simulates the behavior of identified cell types - such as long-lead burst neurons, ... |
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Abstract |
This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This ... |
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Abstract |
This article develops a neural model of how sharp disparity tuning can arise through experience-dependent development of cortical complex cells. This learning process clarifies how complex cells can binocularly match left ... |
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Abstract |
Our ability to see the world in depth is a major accomplishment of the brain. Previous models of how positionally disparate cues to the two eyes are binocularly matched limit possible matches by invoking uniqueness and ... |
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Abstract |
An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset ... |
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Abstract |
The recognition of three-dimensional (3-D) objects from sequences of their two-dimensional (2-D) views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With ... |
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Abstract |
A model of cortico-spinal trajectory generation for voluntary reaching movements is developed to functionally interpret a broad range of behavioral, physiological, and anatomical data. The model simulates how arm movements ... |
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Abstract |
Prenatal development of the primary visual cortex leads to simple cells with spatially distinct and oriented ON and OFF subregions. These simple cells are organized into spatial maps of orientation and ocular dominance that ... |
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Abstract |
Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and ... |
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Abstract |
A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the ... |
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Abstract |
This article describes a self-organizing neural network architecture that transforms optic flow and eye position information into representations of heading, scene depth, and moving object locations. These representations ... |
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Abstract |
Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar ... |
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Abstract |
Figure-ground perception enables us to perceive objects that are distinct from one another and from their scenic background. The remarkable nature of figure-ground perception may be better appreciated when we reflect that ... |
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Abstract |
Multiple brain learning sites are needed to calibrate the accuracy of saccadic eye movements. This is true because saccades can be made reactively to visual cues, attentively to visual or auditory cues, or planned in ... |
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Abstract |
How does the visual cortex combine information from both eyes to generate perceptual representations of object surfaces? Important clues about this process may be derived from data about the perceived brightness of surface ... |
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Abstract |
A neural model of motion perception simulates psychophysical data concerning first-order and second-order motion stimuli, including the reversal of perceived motion direction with distance from the stimulus (Γ display), and ... |
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Abstract |
Smooth pursuit eye movements (SPEMs) are eye rotations that are used to maintain fixation on a moving target. Such rotations complicate the interpretation of the retinal image, because they nullify the retinal motion of the ... |
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Abstract |
Experiments by Markram and Tsodyks (Nature, 382 (1996) 807?810) have suggested that Hebbian pairing in cortical pyramidal neurons potentiates or depresses the transmission of a subsequent pre-synaptic spike train at ... |
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Abstract |
This article outlines a methodology for investigating the coordinate systems by which movement variables are encoded in the firing rates of individual motor cortical neurons. Recent neurophysiological experiments have probed ... |
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Abstract |
This article suggests how brain mechanisms of learning, attention, and volition may give rise to hallucinations during schizophrenia and other mental disorders. The article suggests that normal learning and memory are ... |
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Abstract |
A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific ... |
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Abstract |
How are our brains functionally organized to achieve adaptive behavior in a changing world? This article presents one alternative to the computer analogy that suggests brains are organized into independent modules. Evidence ... |
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Description |
KInNeSS is an open source neural simulation software package that allows to design, simulate and analyze the behavior of networks of hundreds to thousands of branched multi-compartmental neurons with biophysical properties ... |
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