E-Book, Englisch, 310 Seiten
Morris / Tarassenko / Kenward Cognitive Systems - Information Processing Meets Brain Science
1. Auflage 2005
ISBN: 978-0-08-045826-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
E-Book, Englisch, 310 Seiten
ISBN: 978-0-08-045826-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
This book presents an overview of the exciting, truly multidisciplinary research by neuroscientists and systems engineers in the emerging field of cognitive systems, providing a cross-disciplinary examination of this cutting-edge area of scientific research. This is a great example of where research in very different disciplines touches to create a new emerging area of research. The book illustrates some of the technical developments that could arise from our growing understanding of how living cognitive systems behave, and the ability to use that knowledge in the design of artificial systems. This unique book is of considerable interest to researchers and students in information science, neuroscience, psychology, engineering and adjacent fields.
· Represents a remarkable collection of relevant experts from both the life sciences and computer science
· Includes state-of-the-art reviews of topics in cognitive systems from both a life sciences and a computer science perspective
· Discusses the impact of this research on our lives in the near future
Autoren/Hrsg.
Weitere Infos & Material
1;Cover;1
2;Cognitive Systems: Information Processing Meets Brain Science;4
3;Contents;6
4;Contributors;8
5;Preface;10
6;Introduction;12
6.1;The Right Time;13
6.2;Challenges for the Future;13
6.3;The Broader Remit;14
6.4;A New Generation;14
6.5;Public Debate;14
6.6;A New Dawn?;15
7;Section 1: How to Design a Cognitive System;16
7.1;Introduction;18
7.2;1 Self-organization in the Nervous System;20
7.2.1;1 INTRODUCTION;20
7.2.1.1;1.1 Self-organization in the Nervous System;21
7.2.1.2;1.2 Outline of the Chapter;21
7.2.2;2 SELF-ORGANIZATION IN DEVELOPMENT;22
7.2.2.1;2.1 Self-organization and Pattern Formation;23
7.2.2.1.1;2.1.1 Pattern Formation in the Specification of Forebrain;24
7.2.2.1.2;2.1.2 Pattern Formation in the Specification of Neocortex;26
7.2.2.1.3;2.1.3 Self-organization in Forebrain and Neocortical Development;28
7.2.2.1.4;2.1.4 Pattern Formation in the Positioning of Cells;28
7.2.2.2;2.2 Making the Correct Numbers of Cells: Cell Death;29
7.2.2.3;2.3 Development of Connections;30
7.2.2.3.1;2.3.1 Map Formation;31
7.2.2.3.2;2.3.2 Topographic Map Formation in the Visual System;33
7.2.2.3.3;2.3.3 The Elimination of Superinnervation from Developing Muscle;35
7.2.3;3 THE ROLE OF SELF-ORGANIZATION IN EXPERIENTIAL CHANGE;37
7.2.3.1;3.1 Feature Maps;37
7.2.3.1.1;3.1.1 Ocular Dominance, Orientation and Direction Selectivity;37
7.2.3.1.2;3.1.2 Relations Between the Different Feature Maps;38
7.2.3.1.3;3.1.3 The Effect of Neural Activity;38
7.2.3.1.4;3.1.4 Self-organization and the Formation of Feature Maps;39
7.2.3.2;3.2 Self-organization and the Acquisition of Cognitive Function;39
7.2.3.2.1;3.2.1 Cognitive Self-organization;40
7.2.3.2.2;3.2.2 Neural Constructivism and Neural Networks;41
7.2.4;4 SELF-ORGANIZATION AS A RESPONSE TO DAMAGE;42
7.2.4.1;4.1 Self-reorganization;42
7.2.4.2;4.2 Can the Nervous System Regenerate After All?;43
7.2.5;5 OPEN QUESTIONS;44
7.2.5.1;5.1 Questions for the Neurosciences;44
7.2.5.1.1;5.1.1 Levels of Analysis;44
7.2.5.1.2;5.1.2 The Use of Mathematical and Computer Models;45
7.2.5.1.3;5.1.3 Evidence from Invertebrates;45
7.2.5.2;5.2 Inspiration for Other Sciences – ‘Cognitive Systems’;46
7.2.6;Acknowledgments;46
7.2.7;Further Reading;46
7.2.8;References;47
7.3;2 Large-scale, Small-scale Systems;49
7.3.1;1 INTRODUCTION;49
7.3.1.1;1.1 State of the Art;49
7.3.1.2;1.2 Key Open Questions;51
7.3.2;2 INTRODUCTION;51
7.3.2.1;2.1 Biology in Cognitive Systems: Science and Engineering;51
7.3.2.2;2.2 Applications of BICAS;53
7.3.2.2.1;2.2.1 Circuit-level Computation;54
7.3.2.2.2;2.2.2 Networked and Distributed Computing;54
7.3.2.2.3;2.2.3 Artificial Autonomous Agents;55
7.3.2.3;2.3 Opportunities for BICAS;55
7.3.2.4;2.4 Structure of this Chapter;56
7.3.3;3 CIRCUIT-BASED SYSTEMS;56
7.3.3.1;3.1 Introduction;56
7.3.3.2;3.2 Key Questions;57
7.3.3.2.1;3.2.1 Dynamics;57
7.3.3.2.2;3.2.2 Self-organization;57
7.3.3.2.3;3.2.3 Synchronization;57
7.3.3.2.4;3.2.4 Processing Speed;58
7.3.3.2.5;3.2.5 Timing;58
7.3.3.2.6;3.2.6 Robustness;58
7.3.3.2.7;3.2.7 Information Representation in Transmission;58
7.3.3.2.8;3.2.8 Construction and Microcircuitry;58
7.3.3.3;3.3 Five-year View;58
7.3.3.4;3.4 Twenty-year View;59
7.3.4;4 DISTRIBUTED, NETWORKED COMPUTING SYSTEMS;59
7.3.4.1;4.1 Introduction;59
7.3.4.2;4.2 State of the Art;60
7.3.4.2.1;4.2.1 Biologically Inspired Models of Collective Organization;60
7.3.4.2.2;4.2.2 Multi-agent Machine Learning;60
7.3.4.3;4.3 Key Questions;61
7.3.4.4;4.4 Five-year View;62
7.3.4.5;4.5 Twenty-year View;62
7.3.5;5 AUTONOMOUS AGENTS;63
7.3.5.1;5.1 Introduction;63
7.3.5.2;5.2 State of the Art;63
7.3.5.2.1;5.2.1 Autonomous Robots;64
7.3.5.2.2;5.2.2 Software Agents;65
7.3.5.2.2.1;Business and Management;66
7.3.5.2.2.2;Auction Agents;67
7.3.5.3;5.3 Biological Metaphors in Research;69
7.3.5.4;5.4 Key Research Questions;69
7.3.5.5;5.5 Five-year View;71
7.3.5.5.1;5.5.1 Autonomous Robots;71
7.3.5.5.2;5.5.2 Autonomous Software Agents;71
7.3.5.6;5.6 Twenty-year View;72
7.3.5.6.1;5.6.1 Autonomous Robots;72
7.3.5.6.2;5.6.2 Autonomous Software Agents;72
7.3.6;6 CONCLUSIONS;73
7.3.7;Acknowledgements;73
7.3.8;Bibliography;73
7.3.9;8 APPENDIX: KEY QUESTIONS;78
8;Section 2: Cognitive Systems in Touch with the World;80
8.1;Introduction;82
8.2;3 Representation;85
8.2.1;1 INTRODUCTION: THEORIES AND APPROACHES;86
8.2.1.1;1.1 What are Neural Representations and Why are they Relevant to New Technology?;87
8.2.1.1.1;1.1.1 The Nature of Representation;87
8.2.1.1.2;1.1.2 What Factors Determine Representations and Why are these Factors Technologically Relevant?;87
8.2.1.1.3;1.1.3 Necessity is What Brains have to do;87
8.2.1.1.4;1.1.4 Opportunity;87
8.2.1.1.5;1.1.5 Efficiency;88
8.2.2;2 KEY FINDINGS AND CONCEPTUAL ADVANCES OF THE PAST DECADE;88
8.2.2.1;2.1 Protocortex and Rerouting of Development;88
8.2.2.2;2.2 Remnants of Protocortex or Real Interactions?;89
8.2.2.3;2.3 Cross-Modal Integration;89
8.2.2.3.1;2.3.1 Competition, Cooperation and Compensation;89
8.2.2.3.1.1;Competition Rather than Cooperation?;90
8.2.2.3.1.2;Compensation;90
8.2.2.4;2.4 Learning;90
8.2.2.5;2.5 Reverse Hierarchy Theory;91
8.2.3;3 STATISTICS OF NATURAL SIGNALS;92
8.2.4;4 SIMPLE SYSTEMS;93
8.2.4.1;4.1 Background;93
8.2.4.2;4.2 Sensorimotor Integration;94
8.2.4.3;4.3 Coding;95
8.2.4.4;4.4 Pattern Recognition and Learning;95
8.2.4.5;4.5 Navigation;95
8.2.5;5 TECHNICAL DEVELOPMENTS;96
8.2.5.1;5.1 Experimental;96
8.2.5.2;5.2 Theoretical;96
8.2.6;6 FUTURE DIRECTIONS;96
8.2.6.1;6.1 Cross-Fertilization with Computer Scientists;97
8.2.7;Bibliography;97
8.3;4 Sensory Processing;100
8.3.1;1 INTRODUCTION;100
8.3.2;2 SIGHT: COMPUTER VISION;101
8.3.2.1;2.1 Introduction;101
8.3.2.2;2.2 Object Recognition;101
8.3.2.3;2.3 Three-dimensional Perception;102
8.3.2.4;2.4 Visual Tracking;103
8.3.2.4.1;2.4.1 Geometric/Dynamical Model;104
8.3.2.4.2;2.4.2 Inference Engine;104
8.3.2.5;2.5 Natural Systems;105
8.3.2.5.1;2.5.1 Attention;105
8.3.2.5.2;2.5.2 Invariant Object Recognition;105
8.3.2.6;2.6 Silicon Retinas;106
8.3.2.7;2.7 Open Questions;107
8.3.3;3 HEARING: SPEECH RECOGNITION;108
8.3.3.1;3.1 Introduction;108
8.3.3.2;3.2 Continuous Speech Recognition Using Hidden Markov Models;108
8.3.3.3;3.3 Natural Systems;110
8.3.3.4;3.4 Open Questions;111
8.3.4;4 SMELL: OLFACTION;111
8.3.4.1;4.1 Introduction;111
8.3.4.2;4.2 Electronic Noses;111
8.3.4.3;4.3 Natural Systems;112
8.3.4.4;4.4 Open Questions;113
8.3.5;5 SENSOR FUSION;113
8.3.5.1;5.1 Introduction;113
8.3.5.1.1;Applications of Data Fusion;113
8.3.5.1.2;Open Questions;114
8.3.6;6 THE NEOCORTICAL MICROCIRCUIT;114
8.3.6.1;6.1 Open Questions;115
8.3.7;7 LEARNING: PROBABILISTIC GRAPHICAL MODELS;115
8.3.7.1;7.1 Open Questions;117
8.3.8;Acknowledgements;117
8.3.9;References;117
8.4;5 Speech and Language;120
8.4.1;1 INTRODUCTION;120
8.4.2;2 STATE OF THE ART;120
8.4.2.1;2.1 Language and Speech – the Cross-Disciplinary Challenge;121
8.4.2.1.1;2.1.1 The Cognitive and Psycholinguistic Framework for the Study of Language Function;121
8.4.2.1.2;2.1.2 Cortical Localization of Language Function;122
8.4.2.1.3;2.1.3 Neurobiological Constraints;124
8.4.2.1.4;2.1.4 Speech Processing in the Human Brain;125
8.4.2.1.5;2.1.5 The Cross-Linguistic Dimension;128
8.4.3;3 IMPLICATIONS AND FUTURE DEVELOPMENTS;130
8.4.4;4 OPEN QUESTIONS;130
8.4.5;References;130
9;Section 3: Cognitive Systems in Action;132
9.1;Introduction;134
9.2;6 Action;136
9.2.1;1 INTRODUCTION;136
9.2.2;2 FRAMEWORK;138
9.2.2.1;2.1 Implementation;138
9.2.2.2;2.2 Computation;140
9.2.3;3 ACTION SPECIFICATION;142
9.2.4;4 ACTION SELECTION;146
9.2.4.1;4.1 Selection architectures;147
9.2.4.2;4.2 The Vertebrate Solution?;148
9.2.5;5 LINKS AND OPEN QUESTIONS;150
9.2.5.1;5.1 Open Questions;150
9.2.6;References and Further Reading;151
9.3;7 Social Cognition;153
9.3.1;1 INTRODUCTION;153
9.3.1.1;1.1 What do We Mean by Social Cognition?;154
9.3.1.2;1.2 What are the ‘Building Blocks’ of Social Cognition?;155
9.3.1.3;1.3 What can be Measured?;155
9.3.2;2 MECHANISMS OF SOCIAL COGNITION: HOW DOES THE BRAIN DEAL WITH THE SOCIAL WORLD?;156
9.3.2.1;2.1 Reading Faces;157
9.3.2.2;2.2 Recognizing Emotional Expressions;157
9.3.2.3;2.3 Eye Gaze;158
9.3.2.4;2.4 Joint Attention;158
9.3.2.5;2.5 Sensitivity to Biological Motion;159
9.3.2.6;2.6 Perception into Action: Mirror Neurons;159
9.3.2.7;2.7 Detecting Agency;161
9.3.2.7.1;2.7.1 Distinguishing the Self and Other Agents;161
9.3.2.7.2;2.7.2 Knowing that Something is an Agent Like You;161
9.3.2.8;2.8 Imitation;162
9.3.2.9;2.9 Theory of Mind;162
9.3.2.10;2.10 Deception;164
9.3.2.11;2.11 Interpretation of Complex Emotions;164
9.3.2.12;2.12 Empathy;165
9.3.2.13;2.13 Morality;165
9.3.2.14;2.14 The Future of Research in Social Cognition;166
9.3.2.14.1;2.14.1 Social Competence;166
9.3.2.14.2;2.14.2 Robot Communication;166
9.3.2.14.3;2.14.3 Cultural Evolution;167
9.3.2.14.4;2.14.4 Psychopharmacology;167
9.3.3;3 WHEN SOCIAL COMMUNICATION FAILS;167
9.3.3.1;3.1 Autism;168
9.3.3.2;3.2 Antisocial Behaviour;170
9.3.3.3;3.3 Psychopathy;170
9.3.3.4;3.4 Social Cognition Impairments in Schizophrenia;171
9.3.4;4 SOME BURNING QUESTIONS FROM EVERYDAY SOCIAL INTERACTIONS;172
9.3.4.1;4.1 Transdisciplinary Research;173
9.3.4.2;4.2 Public Engagement with Science;173
9.3.5;References;173
9.4;8 Motivation, Planning and Interaction;178
9.4.1;1 INTRODUCTION;178
9.4.2;2 AGENT MOTIVATION;180
9.4.2.1;2.1 Motivation in Psychology, Ethology and Computer Science;181
9.4.2.2;2.2 Computational Modelling of Motivations;182
9.4.2.3;2.3 Modelling Motivation;183
9.4.2.4;2.4 Open Questions;183
9.4.2.4.1;2.4.1 Utility;184
9.4.2.5;2.5 Motivation and Neuroscience?;184
9.4.3;3 AGENT PLANNING;185
9.4.3.1;3.1 Overview;186
9.4.3.2;3.2 AI Planning;186
9.4.3.3;3.3 The State of the Art;187
9.4.3.3.1;3.3.1 Recent Developments;188
9.4.3.3.2;3.3.2 International Planning Competitions;189
9.4.3.3.3;3.3.3 Planning in a Wider Context;190
9.4.3.3.3.1;Robots as Executive Machines;191
9.4.3.4;3.4 Planning: the Future;192
9.4.3.5;3.5 Planning and Cognitive Science;193
9.4.3.5.1;3.5.1 Learning;193
9.4.3.5.2;3.5.2 Cognitive Robotics;194
9.4.3.6;3.6 Open Questions;194
9.4.3.7;3.7 Conclusion;195
9.4.4;4 AGENT INTERACTIONS;196
9.4.4.1;4.1 Machine–Machine Interactions;196
9.4.4.2;4.2 People-Machine Interactions;198
9.4.4.2.1;4.2.1 Speech Recognition;198
9.4.4.2.2;4.2.2 Virtual Reality;199
9.4.4.3;4.3 Person to Person Interactions;199
9.4.4.4;4.4 Key Issues for Neuroscience;201
9.4.5;References;201
9.4.6;Source Material for Planning;203
10;Section 4: Memory;204
10.1;Introduction;206
10.2;9 Learning and Memory;208
10.2.1;1 INTRODUCTORY SUMMARY;208
10.2.2;2 DEFINITIONS, CONCEPTS AND TECHNIQUES;209
10.2.2.1;2.1 Definitions and Concepts;209
10.2.2.2;2.2 Techniques;211
10.2.2.3;2.3 Open Questions;213
10.2.3;3 THE ORGANIZATION OF MEMORY SYSTEMS IN THE BRAIN;214
10.2.3.1;3.1 Working Memory;215
10.2.3.1.1;3.1.1 Psychological Characteristics;215
10.2.3.1.2;3.1.2 Cerebral Localization;216
10.2.3.1.3;3.1.3 Neural Mechanisms;217
10.2.3.1.4;3.1.4 Evolution of Working Memory;217
10.2.3.1.5;3.1.5 Open Questions;218
10.2.3.2;3.2 Long-term Memory;219
10.2.3.2.1;3.2.1 Episodic Memory;219
10.2.3.2.2;3.2.2 Familiarity-based Recognition Memory;221
10.2.3.2.3;3.2.3 Semantic Memory;223
10.2.3.2.4;3.2.4 Semantic and Episodic Memory;225
10.2.3.2.5;3.2.5 Sensorimotor Skills;226
10.2.3.2.6;3.2.6 Value and Emotional Memory;227
10.2.3.2.7;3.2.7 Open Questions;229
10.2.4;4 THE NEUROBIOLOGY OF LEARNING AND MEMORY;231
10.2.4.1;4.1 Long-term Potentiation and Memory;232
10.2.4.2;4.2 Place-cells, Spatial Memory and Event Memory;233
10.2.4.3;4.3 Neuronal Development and Learning;234
10.2.4.4;4.4 Open Questions;235
10.2.5;5 NEURODEGENERATIVE DISEASES;236
10.2.5.1;5.1 Memory in the Elderly;237
10.2.5.2;5.2 Neurodegenerative Disease;237
10.2.5.3;5.3 Open Questions;240
10.2.6;6 CAN WE IMPROVE MEMORY?;240
10.2.6.1;6.1 Pharmaceuticals, Prospects and Perils;241
10.2.6.2;6.2 Cognitive Engineering;242
10.2.6.3;6.3 Open Questions;243
10.2.7;7 COMPUTATIONAL MODELLING;244
10.2.7.1;7.1 Small Networks with Biologically Realistic Parameters;244
10.2.7.2;7.2 Connecting Networks;244
10.2.7.3;7.3 Neuroinformatics;245
10.2.8;8 OPEN QUESTIONS: A SUMMARY;245
10.2.8.1;8.1 Definitions, Concepts, Techniques;245
10.2.8.2;8.2 The Organization of Memory;245
10.2.8.3;8.3 The Neurobiology of Memory;245
10.2.8.4;8.4 Neurodegenerative Diseases and Cognitive Dysfunction;245
10.2.8.5;8.5 Can We Improve Memory?;245
10.2.8.6;8.6 Computational Modelling;246
10.2.9;References;246
10.3;10 Memory, Reasoning and Learning;251
10.3.1;1 INTRODUCTION;251
10.3.1.1;1.1 State of the Art;251
10.3.1.2;1.2 Open Questions;252
10.3.2;2 SCOPE AND ASSUMPTIONS;253
10.3.2.1;2.1 Scope;253
10.3.2.1.1;2.1.1 Type of Research;253
10.3.2.1.2;2.1.2 Location;253
10.3.2.1.3;2.1.3 Background Assumptions;253
10.3.2.2;2.2 Memory, Reasoning and Learning;254
10.3.2.3;2.3 Human and Artificial Neural Computing;254
10.3.2.3.1;2.3.1 Input from the Neurosciences;255
10.3.2.3.2;2.3.2 Lessons from the Comparison;255
10.3.2.3.3;2.3.3 Metaphors;256
10.3.2.4;2.4 Top-down and Bottom-up Approaches;256
10.3.2.4.1;2.4.1 Logic and Virtual Machines;256
10.3.2.4.2;2.4.2 Holistic, Bottom-up Approaches;256
10.3.2.5;2.5 The Physical and the Digital;257
10.3.3;3 MEMORY;257
10.3.3.1;3.1 Content Addressable Memory and Associative Memory;257
10.3.3.1.1;3.1.1 Five-year Horizon;258
10.3.3.1.2;3.1.2 Twenty-year Horizon;258
10.3.3.2;3.2 Multimedia Issues;258
10.3.3.2.1;3.2.1 Five-year Horizon;258
10.3.3.2.2;3.2.2 Twenty-year Horizon;258
10.3.3.3;3.3 Different Types of Memory;259
10.3.3.3.1;3.3.1 Five-year Horizon;259
10.3.3.3.2;3.3.2 Twenty-year Horizon;259
10.3.3.4;3.4 Forgetting;259
10.3.3.4.1;3.4.1 Five-year Horizon;260
10.3.3.4.2;3.4.2 Twenty-year Horizon;260
10.3.3.5;3.5 Symbol Grounding;260
10.3.3.5.1;3.5.1 Five-year Horizon;261
10.3.3.5.2;3.5.2 Twenty-year Horizon;261
10.3.4;4 REASONING;262
10.3.4.1;4.1 Logic and Alternatives;262
10.3.4.1.1;4.1.1 The Relation between Logic-based Reasoning and Neural Nets;262
10.3.4.1.2;4.1.2 Five-year Horizon;262
10.3.4.1.3;4.1.3 Non-monotonic Reasoning;262
10.3.4.1.4;4.1.4 Five-year Horizon;262
10.3.4.1.5;4.1.5 Hardware and Evolution;263
10.3.4.1.6;4.1.6 Twenty-year Horizon;263
10.3.4.2;4.2 Uncertainty;263
10.3.4.2.1;4.2.1 Five-year Horizon;263
10.3.4.2.2;4.2.2 Twenty-year Horizon;263
10.3.4.2.3;4.2.3 Probabilistic Reasoning;263
10.3.4.2.3.1;Five-year Horizon;264
10.3.4.2.4;4.2.4 Web-scale Applications: Semantic Harvesting;264
10.3.4.2.4.1;Five-year Horizon;264
10.3.4.3;4.3 Demands of Multimedia;264
10.3.4.3.1;4.3.1 Five-year Horizon;264
10.3.4.3.2;4.3.2 Twenty-year Horizon;264
10.3.4.4;4.4 Usability;264
10.3.4.4.1;4.4.1 Five-year Horizon;264
10.3.4.4.2;4.4.2 Twenty-year Horizon;265
10.3.4.5;4.5 Indexing, Navigating and Linking;265
10.3.4.5.1;4.5.1 Five-year Horizon;265
10.3.4.5.2;4.5.2 Twenty-year Horizon;266
10.3.4.6;4.6 eScience and the Grid;266
10.3.4.6.1;4.6.1 Five-year Horizon;266
10.3.5;5 LEARNING;267
10.3.5.1;5.1 Personalization of Content;267
10.3.5.1.1;5.1.1 Five-year Horizon;267
10.3.5.1.2;5.1.2 Twenty-year Horizon;267
10.3.5.2;5.2 Reinforcement Learning;268
10.3.5.2.1;5.2.1 Five-year Horizon;268
10.3.5.2.2;5.2.2 Twenty-year Horizon;268
10.3.5.3;5.3 Plasticity;269
10.3.5.3.1;5.3.1 Five-year Horizon;269
10.3.5.3.2;5.3.2 Twenty-year Horizon;269
10.3.5.4;5.4 Machine Learning;269
10.3.5.4.1;5.4.1 Five-year Horizon;270
10.3.5.4.2;5.4.2 Twenty-year Horizon;270
10.3.5.5;5.5 Problem Representation;270
10.3.5.5.1;5.5.1 Five-year Horizon;270
10.3.6;References and Further Reading;271
10.3.7;Further Reading;272
10.3.8;Further Browsing;273
10.3.9;6 APPENDIX: OPEN QUESTIONS AND POSSIBLE RESEARCH DIRECTIONS FOR THE FUTURE;273
11;Section 5: Science Applied;276
11.1;11 Advanced Neuroscience Technologies;278
11.1.1;1 INTRODUCTION: TECHNOLOGICAL DEVELOPMENTS IN COGNITIVE AND IMAGING NEUROSCIENCE;278
11.1.2;2 IMAGING THE HUMAN BRAIN;279
11.1.2.1;2.1 State of the Art;279
11.1.2.2;2.2 Neurophysiology;280
11.1.2.3;2.3 Multimodal Integration;281
11.1.2.4;2.4 Biomathematics and Functional Integration;282
11.1.2.5;2.5 Computational Neuroanatomy;282
11.1.2.6;2.6 Potential Clinical Applications of Neuroimaging;284
11.1.2.7;2.7 New Technologies;285
11.1.2.8;2.8 Interim Conclusion;286
11.1.3;3 MULTIPLE SINGLE-NEURON RECORDING: HOW INFORMATION IS REPRESENTED IN THE BRAIN – THE NEURAL CODE;286
11.1.3.1;3.1 Introduction;286
11.1.3.2;3.2 How do Populations of Neurons Represent Information?;286
11.1.3.3;3.3 New Methods for Recording Spiking Activity of Many Neurons;287
11.1.3.4;3.4 Understanding the Computational Properties of Population Codes;289
11.1.4;4 VISUALIZING MOLECULAR EVENTS AND INTRINSIC SIGNALS IN LIVING NEURONS;289
11.1.4.1;4.1 Introduction;289
11.1.4.2;4.2 Basic Aspects of the Technical Advances;290
11.1.4.2.1;4.2.1 ‘Tagging’ Neuronal Structures with Fluorescent Proteins;290
11.1.4.2.2;4.2.2 Recent Advances in Microscopy Techniques;290
11.1.4.2.3;4.2.3 Time-lapse Imaging;291
11.1.4.2.4;4.2.4 Biosensors;291
11.1.4.3;4.3 Optical Imaging of Intrinsic Signals in the Brain;292
11.1.4.4;4.4 Non-invasive Optical Techniques: Near-infrared Spectroscopy;293
11.1.4.5;4.5 State of the Art in Optical Imaging;294
11.1.5;Further Reading on Optical Imaging;294
11.1.6;5 GLOSSARY OF TERMS;295
11.1.7;References;295
11.1.8;Web Sites;297
11.2;12 Applications and Impact;298
11.2.1;1 SETTING THE SCENE;298
11.2.1.1;1.1 What are Cognitive Systems?;298
11.2.1.2;1.2 The Biological Computer and the Artificial Brain;299
11.2.1.2.1;1.2.1 Hofstadter’s Law;299
11.2.1.3;1.3 Characteristic Capabilities;300
11.2.1.3.1;1.3.1 Sense and Perceive;301
11.2.1.3.2;1.3.2 Act;301
11.2.1.3.3;1.3.3 Think: Recognize, Recall, Compare, Reason, Decide, Plan, …;302
11.2.1.3.4;1.3.4 Feel: Have Emotions, Motivations and Relate to Others;302
11.2.1.3.5;1.3.5 Communicate with Each Other;302
11.2.1.3.6;1.3.6 Learn;302
11.2.1.3.7;1.3.7 Evolve;303
11.2.1.4;1.4 Motivations;303
11.2.1.5;1.5 Summary;304
11.2.2;2 APPLICATIONS AND SOCIETAL IMPACT;304
11.2.2.1;2.1 Business;305
11.2.2.1.1;2.1.1 The Ambient Web;305
11.2.2.1.2;2.1.2 Commercialization Concerns;306
11.2.2.2;2.2 Two Perspectives on the Ambient Web;307
11.2.2.2.1;2.2.1 Multi-Agent Network Systems;307
11.2.2.2.2;2.2.2 From PDA to PDE: The Personal Digital Environment;308
11.2.2.3;2.3 Embodied Cognition: Robots and Smart Things;308
11.2.2.4;2.4 Health, Well-being and Performance;310
11.2.2.4.1;2.4.1 Drivers of Change;310
11.2.2.4.1.1;Macro Mapping of Brain Function: Architecture of Brain and Mind;310
11.2.2.4.1.2;External Brain Interfaces;310
11.2.2.4.1.3;Micro Mapping of Brain Function: Cognitive Components;310
11.2.2.4.1.4;Internal Neuronal Interfaces;310
11.2.2.4.1.5;Personal Sensing;310
11.2.2.4.2;2.4.2 Applications;310
11.2.2.4.2.1;Neuroprosthetics;311
11.2.2.4.2.2;Neurofeedback;311
11.2.2.4.2.3;Direct Brain Interfaces;312
11.2.2.4.2.4;Closing the Loop;312
11.2.2.4.2.5;Assisted Cognition;312
11.2.2.4.2.6;Assistive Robotics;314
11.2.2.5;2.5 Transport;314
11.2.2.6;2.6 Sociable Technologies: Arts, Entertainment and Companions;315
11.2.2.7;2.7 Education;317
11.2.2.8;2.8 Military;317
11.2.3;3 WIDER VIEW;318
11.2.4;Acknowledgements;319
11.2.5;References;319
12;Index;320
12.1;A;320
12.2;B;320
12.3;C;321
12.4;D;321
12.5;E;321
12.6;F;322
12.7;G;322
12.8;H;322
12.9;I;322
12.10;J;322
12.11;L;322
12.12;M;322
12.13;N;323
12.14;O;323
12.15;P;323
12.16;R;324
12.17;S;324
12.18;T;325
12.19;U;325
12.20;V;325
12.21;W;325
12.22;X;325
