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Studies of Mind and Brain

Neural Principles of Learning, Perception, Development, Cognition, and Motor Control

  • Book
  • © 1982

Overview

Authors:
  1. Stephen Grossberg

    1. Department of Mathematics, Boston University, USA

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Part of the book series: Boston Studies in the Philosophy and History of Science (BSPS, volume 70)

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About this book

the mass of experimental data from current research in psychology and physiology, Grossberg proposes and develops a non-linear mathematics as a model for specific functions of mind and brain. He finds the classic approach to the mathematical modelling of mind and brain systematically inadequate. This inadequacy, he holds, arises from the attempt to describe adaptive systems in the mathematical language of 9 physics developed to describe "stationary", i. e. non-adaptive and non-evolving systems. In place of this linear mathematics, Grossberg develops his non-linear approach. His method is at once imaginative, rigorous, and philosophically significant: it is the thought experiment. It is here that the richness of his interdisciplinary mastery, and the power of his methods, constructions and proofs, reveal themselves. The method is what C. S. Peirce characterized as the method of abduction, or of hypothetical inference in theory construction: given the output of the system as a psychological phenomenon (e. g.

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. How Does a Brain Build a Cognitive Code?

    • Stephen Grossberg
    Pages 1-52

  3. Some Physiological and Biochemical Consequences of Psychological Postulates

    • Stephen Grossberg
    Pages 53-64

  4. Classical and Instrumental Learning by Neural Networks

    • Stephen Grossberg
    Pages 65-156

  5. Pattern Learning by Functional-Differential Neural Networks with Arbitrary Path Weights

    • Stephen Grossberg
    Pages 157-193

  6. A Neural Theory of Punishment and Avoidance, II: Quantitative Theory

    • Stephen Grossberg
    Pages 194-228

  7. A Neural Model of Attention, Reinforcement and Discrimination Learning

    • Stephen Grossberg
    Pages 229-295

  8. Neural Expectation: Cerebellar and Retinal Analogs of Cells Fired by Learnable or Unlearned Pattern Classes

    • Stephen Grossberg
    Pages 296-331

  9. Contour Enhancement, Short Term Memory, and Constancies in Reverberating Neural Networks

    • Stephen Grossberg
    Pages 332-378

  10. Biological Competition: Decision Rules, Pattern Formation, and Oscillations

    • Stephen Grossberg
    Pages 379-398

  11. Competition, Decision, and Consensus

    • Stephen Grossberg
    Pages 399-424

  12. Behavioral Contrast in Short Term Memory: Serial Binary Memory Models or Parallel Continuous Memory Models?

    • Stephen Grossberg
    Pages 425-447

  13. Adaptive Pattern Classification and Universal Recoding I: Parallel Development and Coding of Neural Feature Detectors

    • Stephen Grossberg
    Pages 448-497

  14. A Theory of Human Memory: Self-Organization and Performance of Sensory-Motor Codes, Maps, and Plans

    • Stephen Grossberg
    Pages 498-639

  15. Back Matter

    Pages 640-662
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Authors and Affiliations

  • Department of Mathematics, Boston University, USA

    Stephen Grossberg

Bibliographic Information

  • Book Title: Studies of Mind and Brain

  • Book Subtitle: Neural Principles of Learning, Perception, Development, Cognition, and Motor Control

  • Authors: Stephen Grossberg

  • Series Title: Boston Studies in the Philosophy and History of Science

  • DOI: https://doi.org/10.1007/978-94-009-7758-7

  • Publisher: Springer Dordrecht

  • eBook Packages: Springer Book Archive

  • Copyright Information: D. Reidel Publishing Company, Dordrecht, Holland 1982

  • Hardcover ISBN: 978-90-277-1359-9Published: 30 June 1982

  • Softcover ISBN: 978-90-277-1360-5Published: 30 June 1982

  • eBook ISBN: 978-94-009-7758-7Published: 06 December 2012

  • Series ISSN: 0068-0346

  • Series E-ISSN: 2214-7942

  • Edition Number: 1

  • Number of Pages: XVII, 662

  • Topics: Philosophy of Science, Neurosciences

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