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Browsing Cognitive & Neural Systems by Title

OpenBU

Browsing Cognitive & Neural Systems by Title

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  • Bradski, Gary; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-01)
    The recognition of 3-D objects from sequences of their 2-D views is modeled by a neural architecture, called VIEWNET that uses View Information Encoded With NETworks. VIEWNET illustrates how several types of noise and ...
  • Worth, Andrew J.; Lehar, Steve; Kennedy, David N. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-10)
    The Grey-White Decision Network is introduced as an application of an on-center, off-surround recurrent cooperative/competitive network for segmentation of magnetic resonance imaging (MRI) brain images. The three layer ...
  • Carpenter, Gail; Milenova, Boriana (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-07)
    Markram and Tsodyks, by showing that the elevated synaptic efficacy observed with single-pulse LTP measurements disappears with higher-frequency test pulses, have critically challenged the conventional assumption that LTP ...
  • Guenther, Frank; Nieto-Castanon, Alfonso; Ghosh, Satrajit; Tourville, Jason (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-09)
    We used functional magnetic resonance imaging (fMRI) to investigate the representation of sound categories in human auditory cortex. Experiment 1 investigated the representation of prototypical and non-prototypical examples ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-11)
    The author's model "Chorus embodies an attempt to find out how far a mostly bottom-up approach to representation can be taken" (p. 22). Models which embody both bottom-up and top-down learning have stronger computational ...
  • Grossberg, Stephen; Myers, Christopher (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-01)
    How do listeners integrate temporally distributed phonemic information into coherent representations of syllables and words? During fluent speech perception, variations in the durations of speech sounds and silent pauses ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-09)
    What is the neural representation of a speech code as it evolves in time? How do listeners integrate temporally distributed phonemic information across hundreds of milliseconds, even backwards in time, into coherent ...
  • Nieto-Castanon, Alfonso; Ghosh, Satrajit; Tourville, Jason; Guenther, Frank (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-09)
    In this technical report, we present fMRI analysis techniques that test functional hypotheses at the region of interest (ROI) level. An SPM-compatible Matlab toolbox has been developed which allows the creation of ...
  • Lesher, Gregory W.; Mingolla, Ennio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-06)
    Illusory contours can be induced along direction approximately collinear to edges or approximately perpendicular to the ends of lines. Using a rating scale procedure we explored the relation between the two types of inducers ...
  • Lesher, Gregory W.; Mingolla, Ennio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-04)
    Illusory contours can be induced along directions approximately collinear to edges or approximately perpendicular to the ends of lines. Using a rating scale procedure we explored the relation between the two types of ...
  • Rubin, Mark (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-06)
    We describe the ARTEX 2 neural network for recognition of visual textures at arbitrary orientations. ARTEX 2 recognizes visual textures by first passing them through a preprocessing stage which rotates them to a canonical ...
  • Carpenter, Gail A.; Tan, Ah-Hwee (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those ...
  • Carpenter, Gail A.; Tan, Ah-Hwee (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-02)
    This paper shows how knowledge, in the form of fuzzy rules, can be derived from a supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning, that simplifies the network structure ...
  • Grossberg, Stephen; Olsen, Stephen J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-02)
    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 pass filter, and competitive ...
  • Campos, Marcos; Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    This paper introduces S-TREE (Self-Organizing Tree), a family of models that use unsupervised learning to construct hierarchical representations of data and online tree-structured vector quantizers. The S-TREE1 model, which ...
  • Rhodes, Bradley; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    From the dawn of modern neural network theory, the mammalian cerebellum has been a favored object of mathematical modeling studies. Early studies focused on the fan-out, convergence, thresholding, and learned weighting of ...
  • Carpenter, Gail A.; Ravindran, Arun K. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009)
    SyNAPSE program of the Defense Advanced Projects Research Agency (HRL Laboratories LLC, subcontract #801881-BS under DARPA prime contract HR0011-09-C-0001); CELEST, a National Science Foundation Science of Learning Center ...
  • Carpenter, Gail A.; Wilson, Frank D. M. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    The Segmentation ATIT (Adaptive Resonance Theory) network for word recognition from a continuous speech stream is introduced. An input sequeuce represents phonemes detected at a preproccesing stage. Segmentation ATIT is ...
  • Grunewald, Alexander; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-10)
    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 ...
  • Williamson, James R. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-10)
    This paper proposes a biologically-motivated neural network model of supervised learning. The model possesses two novel learning mechanisms. The first is a network for learning topographic mixtures. The network's internal ...

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