Brain Processes, Theories, and Models: An International Conference in Honor of W. S. McCulloch 25 Years After His Death / Edition 1

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W. S. McCulloch, a professor of psychiatry at Illinois, later a scientist at the Research Laboratory of Electronics at MIT and author of the groundbreaking book, Embodiments of Mind (reissued in paperback in 1988), was one of the founding fathers of "Cybernetics." Along with Norbert Wiener, John von Neumann, and H. von Foerster, he sought to integrate the disciplines of neurophysiology, mathematics, and engineering in a rigorous investigation into what brains do and how they do it. A magnetic personality, McCulloch set thoughts into motion (for instance neural nets as parallel computers) that have sparked research and controversy for decades.

These 55 contributions celebrate the lasting impact that McCulloch had on the study of the brain and the formal modeling of human intelligence. They cover a number of varied topics in the general area of neural modeling and are divided into five sections: Essays and General Brain Theory, Mathematical Tools and Global Models, Neurons and Neural Nets, Vision, and AI and Engineering related topics.


H. von Foerster, Michael Arbib, James A. Anderson, Shun-Ichi Amari, Kunihiko Fukushima, Shunsuke Sato, Paul Cull, and Gregory Mulhauser.

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Product Details

  • ISBN-13: 9780262631709
  • Publisher: MIT Press
  • Publication date: 11/9/1995
  • Edition description: First Edition
  • Edition number: 1
  • Pages: 578
  • Product dimensions: 7.17 (w) x 8.83 (h) x 1.06 (d)

Table of Contents

1 Metaphysics of Experimental Epistemology 3
2 Schema Theory: From Kant to McCulloch and Beyond 11
3 Logic and Neural Nets: Variations on Themes by W. S. McCulloch 24
4 Reverse Neurophysiology: The "Embodiments of Mind" Revisited 37
5 On the Epistemology of Representation 50
6 Putting the Mind Inside the Head 54
7 Some Neural Network Theorizing before McCulloch: Nicolas Rashevsky's Mathematical Biophysics 64
8 On Thoughts about the Brain 71
9 Functional Gradients in Cerebral Dynamics: The J. Gonzalo Theories of the Sensorial Cortex 78
10 Complexity of the Brain: Structure, Function, and Dynamics 88
11 Seating Conscious Sensation in a Materially Instantiated Data Structure 98
12 The Brain as a Computer 107
13 From Discrete to Continuous and Back Again 115
14 A Global Inhibitory Model for Deciding Modes of Attention: Functions of the Nucleus Reticularis Thalami 125
15 PATON: A Model of Context Dependent Memory Access with an Attention Mechanism 134
16 An Analysis and Study of Wave-like Propagation of Neuron Activity of Hippocampus for a Neurocomputer Design 144
17 A Formal Representation of Thalamus and Cortex Computation 154
18 A Temporal Learning Rule and Associative Memory 164
19 Cognitive Processes - Representation of Events and Operations from the Viewpoint of Dendritic Computations 173
20 Analogic Gating in the Developing Mammalian Hippocampus 184
21 Psychological Human Behaviour: A System Approach 194
22 Neural Bidirectional Convergence: A Method for Concept Learning in Neural Networks and Symbolic AI 204
23 Hierarchical Team Learning Using Fuzzy Perceptron Algorithms 214
24 Data Fields Transforms by Polynomic Systems: Neuron-like Structures 223
25 Neural Nets: Classical Results and Current Problems 235
26 Cooperative Processes at the Symbolic Level in Cerebral Dynamics: Reliability and Fault Tolerance 244
27 Pulse Sequence Transmission in the BVP Neuron Model 256
28 Compartmental Modeling of Dendrites for Artificial Neurons 264
29 Information Representation in a Randomly and Symmetrically Connected Recurrent Neural Network 274
30 A Quantitative Model of Primate Auditory-Evoked Orienting in Two Dimensions 284
31 Dynamic Linking in Stochastic Networks 294
32 Kalman Neural-Gas Network for Time Series Prediction 300
33 Population Coding and Hebbian Learning 310
34 Theoretical Framework for Analysis and Synthesis of Networks of Neurones 320
35 A Class of Recursive Artificial Neural Networks Based on Analytic Geometry 330
36 Are Artificial Neural Nets Able to Provide Internal Representation of External Learning Patterns? A Question, Still Remaining Open 340
37 Long Cycle Generation by McCulloch-Pitts Networks (MCP-Nets) with Dense and Sparse Weighth Matrices 350
38 Retrograde Neural Messenger in the Brain: Preliminary Study on the Implications in the Artificial Neural Networks 360
39 Probabilistic Interpretation of the Behaviour of a Binary Neuron 370
40 Neural Signals as Indicators of Spatial and Temporal Segmentation Coding in the Visual System 381
41 A Model of Spatial Filtering by Visual Cortical Simple Cells 391
42 Scanning Alpha Wave in Visual Cortex and Recognition of Images and Motion 401
43 Modeling Object Processing: Converging Evidence from Human Experimental and Computational Modeling Perspectives 411
44 Building Visual Correspondence Maps - From Neuronal Dynamics to a Face Recognition System 420
45 On Structure, Function, and Time in Retinae 430
46 Binding of Form and Motion by Selective Attention: A Neural Network Model 436
47 The Top-Down Contribution of Will to the Modulation of Bottom-Up Inputs in the Reversible Perception Phenomenon 446
48 Description of Images by Subcortical Levels of the Visual System and Properties of Gamma-Oscillations Accompanying This Process 456
49 On the Neural Mechanisms of Auditory and Visual Invariance Perception 468
50 Image Compression Based on Competitive Hebbian Learning Neural Networks 478
51 The Penultimate Obstacle to Artificial Intelligence: The Fulguratio 485
52 On the Abstraction Process 495
53 Neocortical Dynamics in Sensorimotor Control 503
54 Hysteresis and Asymmetric Sensitivity to Change in Pacemaker Responses to Inhibitory Input Transients 513
55 Use of Efferent Neural Pathways to Regulate an Artificial Heart to the Physiological Demands of the Body 523
56 Robotic Systems with Perceptual Feedback and Anticipatory Behavior 532
57 A Model of Adaptive Robotic Manipulator Control Inspired by Human Motor Programs 541
58 The CONNET Language and the McCulloch and Pitts Network Synthesis 551
Author Index 561
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