This book contains edited chapters on current work concerning connectionist or neural network models of human development. A starting point of the approach is that the brain comprises millions of nerve cells (neurons) that share a myriad of connections. Human development in these systems is typically characterized as adaptive changes to the stregnths of these connections. Many examples are provided of how researchers have built computer programs that mimic these processes so as to provide a better understanding of human intellectual development. Alongside this work in artificial intelligence, other chapters describe what is currently known about how real brains develop.
Author(s): Philip T. Quinlan
Series: Studies in Developmental Psychology
Publisher: Psychology Press
Year: 2003
Language: English
Commentary: 38947
Pages: 373
Book Cover......Page 1
Half-Title......Page 2
Title......Page 4
Copyright......Page 5
Contents......Page 6
List of Contributors......Page 7
Modelling Human Development: In Brief......Page 9
1. A Connectionist Perspective on Piagetian Development......Page 20
2. Connectionist Models of Learning and Development in Infancy......Page 49
3. The Role of Prefrontal Cortex in Perseveration: Developmental and Computational Explorations......Page 83
4. Language Acquisition in a Self-Organising Neural Network Model......Page 113
5. Connectionist Modelling of Lexical Segmentation and Vocabulary Acquisition......Page 144
6. Less is Less in Language Acquisition......Page 179
7. Pattern Learning in Infants and Neural Networks......Page 220
8. Does Visual Development Aid Visual Learning?......Page 242
9. Learning and Brain Development: A Neural Constructivist Perspective......Page 263
10. Cross-Modal Neural Development......Page 292
11. Evolutionary Connectionism......Page 325
Author Index......Page 344
Subject Index......Page 367
