URI: http://hdl.handle.net/2144/1897

Recently Added

  • A laminar cortical model of stereopsis and 3D surface perception: Closure and da Vinci stereopsis 

    Cao, Yongqiang; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-09)
    A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface ...
  • Contrast-sensitive perceptual grouping and object-based attention in the laminar circuits of primary visual cortex 

    Grossberg, Stephen; Raizada, Rajeev D.S. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-03)
    Recent neurophysiological studies have shown that primary visual cortex, or Vl, does more than passively process image features using the feedforward filters suggested by Hubel and Wiesel. It also uses horizontal interactions ...
  • PointMap: A real-time memory-based learning system with on-line and post-training pruning 

    Kopco, Norbert; Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-12)
    A memory-based learning system called PointMap is a simple and computationally efficient extension of Condensed Nearest Neighbor that allows the user to limit the number of exemplars stored during incremental learning. ...
  • A Vector-Integration-to-Endpoint Model for Performance of Viapoint Movements 

    Bullock, D.; Bongers, R. M.; Lankhorst, M.; Beek, P. J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-08)
    Viapoint (VP) movements are movements to a desired point that are constrained to pass through an intermediate point. Studies have shown that VP movements possess properties, such as smooth curvature around the VP, that are ...
  • Dopaminergic and Non-Dopaminergic Value Systems in Conditioning and Outcome-Specific Revaluation 

    Dranias, Mark R.; Grossberg, Stephen; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-12)
    Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal Values Triggers Option Revaluations) ...
  • A neural network model of adaptively timed reinforcement learning and hippocampal dynamics 

    Grossberg, Stephen; Merrill, John W. L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1992-01)
    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 ...
  • A Self-Organizing Neural System for Learning to Recognize Textured Scenes 

    Grossberg, Stephen; Williamson, James (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-01)
    A self-organizing ARTEX model is developed to categorize and classify textured image regions. ARTEX specializes the FACADE model of how the visual cortex sees, and the ART model of how temporal and prefrontal cortices ...
  • A Nonlinear Model of Spatiotemporal Retinal Processing: Simulations of X and Y Retinal Ganglion Cell Behavior 

    Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-07)
    This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown ...
  • Normal and Amnesic Learning, Recognition, and Memory by a Neural Model of Cortico-Hippocampal Interactions 

    Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection ...
  • A Fuzzy ARTMAP Nonparametric Probability Estimator For Nonstationary Pattern Recognition Problems 

    Carpenter, Gail A.; Grossberg, Stephen; Reynolds, John H. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-10)
    An incremental, nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is introduced. In slow-learning mode, fuzzy ARTMAP searches for patterns of data on which to build ever more accurate ...
  • Working memory networks for learning multiple groupings of temporally ordered events: applications to 3-D visual object recognition 

    Bradski, Gary; Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    Working memory neural networks are characterized which encode the invariant temporal order of sequential events that may be presented at widely differing speeds, durations, and interstimulus intervals. This temporal order ...
  • Variable Rate Working Memories for Phonetic Categorization and Invariant Speech Perception 

    Boardman, Ian; Cohen, Michael; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    Speech can be understood at widely varying production rates. A working memory is described for short-term storage of temporal lists of input items. The working memory is a cooperative-competitive neural network that ...
  • Context-sensitive spatio-temporal memory 

    Rinkus, Gerard J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    The proposed model, called the combinatorial and competitive spatio-temporal memory or CCSTM, provides an elegant solution to the general problem of having to store and recall spatio-temporal patterns in which states or ...
  • The Hippocampus and Cerebellum in Adaptively Timed Learning, Recognition, and Movement 

    Grossberg, Stephen; Merrill, John W.L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-02)
    The concepts of declarative memory and procedural memory have been used to distinguish two basic types of learning. A neural network model suggests how such memory processes work together as recognition learning, reinforcement ...
  • Cortical Synchronization and Perceptual Framing 

    Grossberg, Stephen; Gruenwald, Alexander (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-05)
    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. ...
  • An Unsupervised Neural Network for Real-Time Low-Level Control of a Mobile Robot: Noise Resistance, Stability, and Hardware Implementation 

    Gaudiano, Paolo; Zalama, Eduardo; Coronado, Juan Lopez (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-07)
    We have recently introduced a neural network mobile robot controller (NETMORC). The controller is based on earlier neural network models of biological sensory-motor control. We have shown that NETMORC is able to guide a ...
  • Neural Control of Interlimb Oscillations I: Human Bimanual Coordination 

    Grossberg, Stephen; Pribe, Christopher; Cohen, Michael A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-08)
    How do humans and other animals accomplish coordinated movements? How are novel combinations of limb joints rapidly assembled into new behavioral units that rnove together in in-phase or anti-phase movement patterns during ...
  • TEMCOR: An Associative, Spatio-Temporal Pattern Memory for Complex State Sequences 

    Rinkus, Gerard J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-04)
    The problem of representing large sets of complex state sequences (CSSs)-i.e. sequences in which states can recur multiple times--has thus far resisted solution. This paper describes a novel neural network model, TEMECOR, ...
  • How Listing's Law May Emerge from Neural Control of Reactive Saccades 

    Pribe, Christopher A.; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-09)
    We hypothesize that Listing's Law emerges as a result of two key properties of the saccadic sensory-motor system: 1) The visual sensory apparatus has a 2-D topology and 2) motor synergists are synchronized. The theory is ...
  • Motivation 

    Dorman, Clark; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-07)
    The ability of humans and animals to survive in a constantly changing environment is a testament to the power of biological processes. At any given instant in our lives, we are faced with an enormous number of sensory ...

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