Studies of Mind and Brain

1. Front Matter

   Pages i-xvii

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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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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.

• attention
• brain
• cognition
• memory
• neural networks
• perception

• Department of Mathematics, Boston University, USA

  Stephen Grossberg

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