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  1. Cognitive neurobiology: A computational hypothesis for laminar cortex. [REVIEW]Paul M. Churchland - 1986 - Biology and Philosophy 1 (1):25-51.
    This paper outlines the functional capacities of a novel scheme for cognitive representation and computation, and it explores the possible implementation of this scheme in the massively parallel organization of the empirical brain. The suggestion is that the brain represents reality by means of positions in suitably constitutes phase spaces; and the brain performs computations on these representations by means of coordinate transformations from one phase space to another. This scheme may be implemented in the brain in two distinct forms: (...)
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  • Parameter nets.Dana H. Ballard - 1984 - Artificial Intelligence 22 (3):235-267.
  • GE Hinton, and T. J. Sejnowski," A learning machine for Boltzman Machines,".D. H. Ackley - 1985 - Cognitive Science 9 (1):147-169.
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  • A learning algorithm for boltzmann machines.David H. Ackley, Geoffrey E. Hinton & Terrence J. Sejnowski - 1985 - Cognitive Science 9 (1):147-169.
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  • What is life? the physical aspect of the living cell & Mind and matter.Erwin Schrödinger - 1967 - Cambridge,: University P..
  • What is Life?A. Cornelius Benjamin - 1948 - Philosophy and Phenomenological Research 8 (3):481-483.
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  • Ecological constraints on internal representation: Resonant kinematics of perceiving, imagining, thinking, and dreaming.Roger N. Shepard - 1984 - Psychological Review 91 (4):417-447.
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  • Vision: Variations on Some Berkeleian Themes.Robert Schwartz & David Marr - 1985 - Philosophical Review 94 (3):411.
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  • Feature discovery by competitive learning.David E. Rumelhart & David Zipser - 1985 - Cognitive Science 9 (1):75-112.
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  • The perceptron: A probabilistic model for information storage and organization in the brain.F. Rosenblatt - 1958 - Psychological Review 65 (6):386-408.
    If we are eventually to understand the capability of higher organisms for perceptual recognition, generalization, recall, and thinking, we must first have answers to three fundamental questions: 1. How is information about the physical world sensed, or detected, by the biological system? 2. In what form is information stored, or remembered? 3. How does information contained in storage, or in memory, influence recognition and behavior? The first of these questions is in the.
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  • Difficulties with a direct theory of perception.Irvin Rock - 1980 - Behavioral and Brain Sciences 3 (3):398-399.
  • Shading into texture.Alex P. Pentland - 1986 - Artificial Intelligence 29 (2):147-170.
  • Perceptual organization and the representation of natural form.Alex P. Pentland - 1986 - Artificial Intelligence 28 (3):293-331.
  • The cell assembly: Mark II.P. M. Milner - 1957 - Psychological Review 64 (4):242-252.
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  • Putting knowledge in its place: A scheme for programming parallel processing structures on the fly.James L. McClelland - 1985 - Cognitive Science 9 (1):113-146.
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  • A logical calculus of the ideas immanent in nervous activity.Warren S. McCulloch & Walter Pitts - 1943 - The Bulletin of Mathematical Biophysics 5 (4):115-133.
    Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions (...)
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  • An interactive activation model of context effects in letter perception: I. An account of basic findings.James L. McClelland & David E. Rumelhart - 1981 - Psychological Review 88 (5):375-407.
  • The Perception of the Visual World.Norman Malcolm - 1951 - Philosophical Review 60 (4):594.
  • The functional organization of posterior parietal association cortex.James C. Lynch - 1980 - Behavioral and Brain Sciences 3 (4):485-499.
    Posterior parietal cortex has traditionally been considered to be a sensory association area in which higher-order processing and intermodal integration of incoming sensory information occurs. In this paper, evidence from clinical reports and from lesion and behavioral-electrophysiological experiments using monkeys is reviewed and discussed in relation to the overall functional organization of posterior parietal association cortex, and particularly with respect to a proposed posterior parietal mechanism concerned with the initiation and control of certain classes of eye and limb movements. Preliminary (...)
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  • Cognitive coordinate systems: Accounts of mental rotation and individual differences in spatial ability.Marcel A. Just & Patricia A. Carpenter - 1985 - Psychological Review 92 (2):137-172.
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  • Determining optical flow.Berthold K. P. Horn & Brian G. Schunck - 1981 - Artificial Intelligence 17 (1-3):185-203.
  • Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading.Stephen Grossberg & Ennio Mingolla - 1985 - Psychological Review 92 (2):173-211.
  • Four frames do not suffice.Stephen Grossberg - 1985 - Behavioral and Brain Sciences 8 (2):294-295.
  • The Perception Of The Visual World.James J. Gibson - 1950 - Boston: Houghton Mifflin.
  • Four frames suffice: A provisional model of vision and space.Jerome A. Feldman - 1985 - Behavioral and Brain Sciences 8 (2):265-289.
    This paper presents a general computational treatment of how mammals are able to deal with visual objects and environments. The model tries to cover the entire range from behavior and phenomenological experience to detailed neural encodings in crude but computationally plausible reductive steps. The problems addressed include perceptual constancies, eye movements and the stable visual world, object descriptions, perceptual generalizations, and the representation of extrapersonal space.The entire development is based on an action-oriented notion of perception. The observer is assumed to (...)
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  • Connectionist Models and Their Properties.J. A. Feldman & D. H. Ballard - 1982 - Cognitive Science 6 (3):205-254.
    Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...)
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  • The Computer And The Brain.John Von Neumann - 1958 - New Haven: Yale University Press.
    This book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain.
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  • Image and Mind.Stephen Michael Kosslyn - 1980 - Harvard University Press.
    The book also introduces a host of new experimental techniques and major hypotheses to guide future research.
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  • Vision.David Marr - 1982 - W. H. Freeman.
  • Invariant manifolds.M. W. Hirsch, C. C. Pugh & M. Shub - unknown
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