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

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

by Roberto Moreno-Diaz, Jose Mira-Mira
     
 

ISBN-10: 0262631709

ISBN-13: 9780262631709

Pub. Date: 11/09/1995

Publisher: MIT Press

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…  See more details below

Overview

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.

Contributors:

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:
11/09/1995
Edition description:
First Edition
Pages:
578
Product dimensions:
7.17(w) x 8.83(h) x 1.06(d)

Table of Contents

Preface
1Metaphysics of Experimental Epistemology3
2Schema Theory: From Kant to McCulloch and Beyond11
3Logic and Neural Nets: Variations on Themes by W. S. McCulloch24
4Reverse Neurophysiology: The "Embodiments of Mind" Revisited37
5On the Epistemology of Representation50
6Putting the Mind Inside the Head54
7Some Neural Network Theorizing before McCulloch: Nicolas Rashevsky's Mathematical Biophysics64
8On Thoughts about the Brain71
9Functional Gradients in Cerebral Dynamics: The J. Gonzalo Theories of the Sensorial Cortex78
10Complexity of the Brain: Structure, Function, and Dynamics88
11Seating Conscious Sensation in a Materially Instantiated Data Structure98
12The Brain as a Computer107
13From Discrete to Continuous and Back Again115
14A Global Inhibitory Model for Deciding Modes of Attention: Functions of the Nucleus Reticularis Thalami125
15PATON: A Model of Context Dependent Memory Access with an Attention Mechanism134
16An Analysis and Study of Wave-like Propagation of Neuron Activity of Hippocampus for a Neurocomputer Design144
17A Formal Representation of Thalamus and Cortex Computation154
18A Temporal Learning Rule and Associative Memory164
19Cognitive Processes - Representation of Events and Operations from the Viewpoint of Dendritic Computations173
20Analogic Gating in the Developing Mammalian Hippocampus184
21Psychological Human Behaviour: A System Approach194
22Neural Bidirectional Convergence: A Method for Concept Learning in Neural Networks and Symbolic AI204
23Hierarchical Team Learning Using Fuzzy Perceptron Algorithms214
24Data Fields Transforms by Polynomic Systems: Neuron-like Structures223
25Neural Nets: Classical Results and Current Problems235
26Cooperative Processes at the Symbolic Level in Cerebral Dynamics: Reliability and Fault Tolerance244
27Pulse Sequence Transmission in the BVP Neuron Model256
28Compartmental Modeling of Dendrites for Artificial Neurons264
29Information Representation in a Randomly and Symmetrically Connected Recurrent Neural Network274
30A Quantitative Model of Primate Auditory-Evoked Orienting in Two Dimensions284
31Dynamic Linking in Stochastic Networks294
32Kalman Neural-Gas Network for Time Series Prediction300
33Population Coding and Hebbian Learning310
34Theoretical Framework for Analysis and Synthesis of Networks of Neurones320
35A Class of Recursive Artificial Neural Networks Based on Analytic Geometry330
36Are Artificial Neural Nets Able to Provide Internal Representation of External Learning Patterns? A Question, Still Remaining Open340
37Long Cycle Generation by McCulloch-Pitts Networks (MCP-Nets) with Dense and Sparse Weighth Matrices350
38Retrograde Neural Messenger in the Brain: Preliminary Study on the Implications in the Artificial Neural Networks360
39Probabilistic Interpretation of the Behaviour of a Binary Neuron370
40Neural Signals as Indicators of Spatial and Temporal Segmentation Coding in the Visual System381
41A Model of Spatial Filtering by Visual Cortical Simple Cells391
42Scanning Alpha Wave in Visual Cortex and Recognition of Images and Motion401
43Modeling Object Processing: Converging Evidence from Human Experimental and Computational Modeling Perspectives411
44Building Visual Correspondence Maps - From Neuronal Dynamics to a Face Recognition System420
45On Structure, Function, and Time in Retinae430
46Binding of Form and Motion by Selective Attention: A Neural Network Model436
47The Top-Down Contribution of Will to the Modulation of Bottom-Up Inputs in the Reversible Perception Phenomenon446
48Description of Images by Subcortical Levels of the Visual System and Properties of Gamma-Oscillations Accompanying This Process456
49On the Neural Mechanisms of Auditory and Visual Invariance Perception468
50Image Compression Based on Competitive Hebbian Learning Neural Networks478
51The Penultimate Obstacle to Artificial Intelligence: The Fulguratio485
52On the Abstraction Process495
53Neocortical Dynamics in Sensorimotor Control503
54Hysteresis and Asymmetric Sensitivity to Change in Pacemaker Responses to Inhibitory Input Transients513
55Use of Efferent Neural Pathways to Regulate an Artificial Heart to the Physiological Demands of the Body523
56Robotic Systems with Perceptual Feedback and Anticipatory Behavior532
57A Model of Adaptive Robotic Manipulator Control Inspired by Human Motor Programs541
58The CONNET Language and the McCulloch and Pitts Network Synthesis551
Author Index561

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