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Connectionist Models of Learning, Development and Evolution

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Cover of 'Connectionist Models of Learning, Development and Evolution'

Table of Contents

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    Book Overview
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    Chapter 1 Applying Neuroanatomical Distinctions to Connectionist Cognitive Modelling
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    Chapter 2 Pseudopatterns and dual-network memory models: Advantages and shortcomings
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    Chapter 3 A Learning Algorithm for Synfire Chains
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    Chapter 4 Towards a Spatio-Temporal Analysis Tool for fMRI Data: An Application to Depth-from-Motion Processing in Humans
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    Chapter 5 A Simple Model Exhibiting Scalar Timing
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    Chapter 6 Modularity and Specialized Learning in the Organization of Behaviour
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    Chapter 7 Modeling Modulatory Aspects in Association Processes
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    Chapter 8 Recognition of Novelty Made Easy: Constraints of Channel Capacity on Generative Networks
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    Chapter 9 A Biologically Plausible Maturation of an ART Network
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    Chapter 10 Developing Knowledge about Living Things: A Connectionist Investigation
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    Chapter 11 Paying Attention to Relevant Dimensions: A Localist Approach
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    Chapter 12 Coordinating Multiple Sensory Modalities While Learning to Reach
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    Chapter 13 Modelling Cognitive Development with Constructivist Neural Networks
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    Chapter 14 Learning Action Affordances and Action Schemas
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    Chapter 15 A Three-Layer Configural Cue Model of Category Learning Rates
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    Chapter 16 A Revival of Turing’s Forgotten Connectionist Ideas: Exploring Unorganized Machines
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    Chapter 17 Visual Crowding and Category-Specific Deficits: a Neural Network Model
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    Chapter 18 Implicit Learning of Regularities in Western Tonal Music by Self-Organization
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    Chapter 19 Rules vs. Statistics in Implicit Learning of Biconditional Grammars
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    Chapter 20 Hidden Markov Model Interpretations of Neural Networks
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    Chapter 21 A Connectionist Model of Person Perception and Stereotype Formation
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    Chapter 22 Learning about an Absent Cause: Discounting and Augmentation of Positively and Independently Related Causes
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    Chapter 23 Exploring the Baldwin Effect in Evolving Adaptable Control Systems
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    Chapter 24 Borrowing Dynamics from Evolution: Association using Catalytic Network Models
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    Chapter 25 Evolving Modular Architectures for Neural Networks
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    Chapter 26 Evolution, Development and Learning — a Nested Hierarchy?
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    Chapter 27 Learning Lexical Properties from Word Usage Patterns: Which Context Words Should be Used?
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    Chapter 28 Associative Computation and Associative Prediction
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    Chapter 29 The Development of Small-world Semantic Networks
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    Chapter 30 What is the Dimensionality of Human Semantic Space?
Attention for Chapter 18: Implicit Learning of Regularities in Western Tonal Music by Self-Organization
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Chapter title
Implicit Learning of Regularities in Western Tonal Music by Self-Organization
Chapter number 18
Book title
Connectionist Models of Learning, Development and Evolution
Published by
Springer, London, January 2001
DOI 10.1007/978-1-4471-0281-6_18
Book ISBNs
978-1-85233-354-6, 978-1-4471-0281-6
Authors

Barbara Tillmann, Jamshed J. Bharucha, Emmanuel Bigand

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Turkey 1 3%
France 1 3%
South Africa 1 3%
Israel 1 3%
United Kingdom 1 3%
Unknown 26 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Researcher 7 23%
Student > Bachelor 3 10%
Professor 2 6%
Student > Master 2 6%
Other 6 19%
Unknown 1 3%
Readers by discipline Count As %
Psychology 14 45%
Arts and Humanities 5 16%
Neuroscience 4 13%
Computer Science 3 10%
Sports and Recreations 1 3%
Other 3 10%
Unknown 1 3%