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Browsing Cognitive & Neural Systems by Title

OpenBU

Browsing Cognitive & Neural Systems by Title

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  • Asofur, Yousif R.; Carpenter, Gail A.; grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-02)
    This application illustrates how the fuzzy ARTMAP neural network can be used to monitor environmental changes. A benchmark problem seeks to classify regions of a Landsat image into six soil and crop classes based on images ...
  • Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009-06)
    — Consideration of how people respond to the question What is this? has suggested new problem frontiers for pattern recognition and information fusion, as well as neural systems that embody the cognitive transformation of ...
  • Fischl, Bruce; Schwartz, Eric L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-12-22)
    Multi-scale image enhancement and representation is an important part of biological and machine early vision systems. The process of constructing this representation must be both rapid and insensitive to noise, while ...
  • Rhodes, Bradley; Bullock, Daniel; Verwey, Willem; Averbeck, Bruno; Page, Michael (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-12)
    A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was ...
  • Banquet, Jean-Paul; Contreras-Vidal, Jose L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    The system presented here is based on neurophysiological and electrophysiological data. It computes three types of increasingly integrated temporal and probability contexts, in a bottom-up mode. To each of these contexts ...
  • Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-10)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-02)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-10)
    The processes whereby our brains continue to learn about a changing world in a stable fashion throughout life are proposed to lead to conscious experiences. These processes include the learning of top-down expectations, ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-04)
    The concept of attention has been used in many senses, often without clarifying how or why attention works as it does. Attention, like consciousness, is often described in a disembodied way. The present article summarizes ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-02)
    In order to understand schizophrenia, a linking hypothesis is needed that shows how brain mechanisms lead to behavioral functions in normals, and also how breakdown in these mechanisms lead to behavioral symptoms in ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
  • Grossberg, Stephen (Boston University Computer Science Department, 2001-03)
    A detailed neural model is being developed of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention, and develop and learn in a ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-02)
    Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach, rather than one consistent with the "objective ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-10)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-12)
  • Tan, Can Ozan; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-04)
    Before choosing, it helps to know both the expected value signaled by a predictive cue and the associated uncertainty that the reward will be forthcoming. Recently, Fiorillo et al. (2003) found the dopamine (DA) neurons ...
  • Fishl, Bruce; Schwartz, Eric L.; Cohen, Michael A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-08)
    Local image structure is widely used in theories of both machine and biological vision. The form of the differential operators describing this structure for space-invariant images has been well documented (e.g. Koenderink, ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-11)
    A number of examples are given of how localist models may incorporate distributed representations, without the types of non-local interactions that often render distributed models implausible. The need to analyze the ...
  • Pinna, Baingio; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2005-03)
    Cognitive and gestalt visions theories consider incompleteness to be a necessmy and sufficient factor for inducing illusory figures. The role of incompleteness is studied herein by defining the inner logic subtended by use ...
  • Przybyszcwski, A.W.; Clarke, A.H. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-12)
    Eye and head movement data, were recorded under head fixed and head-free conditions, and compared with theoretical results obtained using a nonlinear model of eye-head coordination. The model explains slow, or pursuit ...

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