Coverart for item
The Resource Cognitive phase transitions in the cerebral cortex : enhancing the neuron doctrine by modeling neural fields, Robert Kozma, Walter J. Freeman, (electronic book)

Cognitive phase transitions in the cerebral cortex : enhancing the neuron doctrine by modeling neural fields, Robert Kozma, Walter J. Freeman, (electronic book)

Label
Cognitive phase transitions in the cerebral cortex : enhancing the neuron doctrine by modeling neural fields
Title
Cognitive phase transitions in the cerebral cortex
Title remainder
enhancing the neuron doctrine by modeling neural fields
Statement of responsibility
Robert Kozma, Walter J. Freeman
Creator
Contributor
Author
Subject
Language
eng
Summary
This intriguing book was born out of the many discussions the authors had in the past 10 years about the role of scale-free structure and dynamics in producing intelligent behavior in brains. The microscopic dynamics of neural networks is well described by the prevailing paradigm based in a narrow interpretation of the neuron doctrine. This book broadens the doctrine by incorporating the dynamics of neural fields, as first revealed by modeling with differential equations (K-sets). The book broadens that approach by application of random graph theory (neuropercolation). The book concludes with diverse commentaries that exemplify the wide range of mathematical/conceptual approaches to neural fields. This book is intended for researchers, postdocs, and graduate students, who see the limitations of network theory and seek a beachhead from which to embark on mesoscopic and macroscopic neurodynamics
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Kozma, Robert
Dewey number
612.8/233
Illustrations
illustrations
Index
index present
LC call number
QP360.5
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Freeman, Walter J.
Series statement
Studies in systems, decision and control
Series volume
39
http://library.link/vocab/subjectName
  • Cognitive neuroscience
  • Cognition
  • Consciousness
Label
Cognitive phase transitions in the cerebral cortex : enhancing the neuron doctrine by modeling neural fields, Robert Kozma, Walter J. Freeman, (electronic book)
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Acknowledgments; Commentators; Contents; Part I Review of Dynamical Brain Theoriesand Experiments; 1 Introduction -- On the Languages of Brains; 1.1 Brains Are Not Computers; 1.2 Symbolic Approaches to Brains; 1.3 Connectionism; 1.4 Brains as Transient Dynamical Systems; 1.5 Random Graph Theory (RGT) for Brain Models; 1.6 Neuropercolation Modeling Paradigm; References; 2 Experimental Investigation of High-Resolution Spatio-Temporal Patterns; 2.1 Method; 2.1.1 Experiments with Rabbits; 2.1.2 Human ECoG Experiments; 2.1.3 Scalp EEG Design Considerations
  • 2.2 Temporal Patterns: The Carrier Wave2.3 Spatial Patterns of Amplitude Modulation (AM) and Phase Modulation (PM); 2.4 Classification of ECoG and EEG AM Patterns; 2.5 Characterization of Synchronization-Desynchronization Transitions in the Cortex; 2.6 Experimental Observation of Singularity; 2.7 Transmission of Macroscopic Output by Microscopic Pulses; References; 3 Interpretation of Experimental Results As Cortical Phase Transitions; 3.1 Theoretical Approaches to Nonlinear Cortical Dynamics; 3.2 Scales of Representation: Micro-, Meso-, and Macroscopic Levels
  • 3.3 Cinematic Theory of Cortical Phase Transitions3.4 Characterization of Phase Transitions; 3.4.1 Critical State; 3.4.2 Singular Dynamics; 3.4.3 Symmetry Breaking; 3.4.4 Transition Energy; 3.4.5 Zero Order Parameter; 3.4.6 Correlation Length Divergence; References; 4 Short and Long Edges in Random Graphs for Neuropil Modeling; 4.1 Motivation of Using Random Graph Theory for Modeling Cortical Processes; 4.2 Glossary of Random Graph Terminology; 4.3 Neuropercolation Basics; 4.4 Critical Behavior in Neuropercolation with Mean-Field, Local, and Mixed Models; 4.4.1 Mean-Field Approximation
  • 4.4.2 Mixed Short and Long Connections4.5 Finite Size Scaling Theory of Criticality in Brain Models ; References; 5 Critical Behavior in Hierarchical Neuropercolation Models of Cognition; 5.1 Basic Principles of Hierarchical Brain Models; 5.2 Narrow-Band Oscillations in Lattices with Inhibitory Feedback; 5.3 Broad-Band Oscillations in Coupled Multiple Excitatory-Inhibitory Layers; 5.4 Exponentially Expanding Graph Model; References; 6 Modeling Cortical Phase Transitions Using Random Graph Theory; 6.1 Describing Brain Networks in Terms of Graph Theory
  • 6.1.1 Synchronization and the 'Aha' Moment6.1.2 Practical Considerations on Synchrony; 6.1.3 Results of Synchronization Measurements; 6.2 Evolution of Critical Behavior in the Neuropil -- a Hypothesis; 6.3 Singularity and sudden transitions -- Interpretation of Experimental Findings; References; 7 Summary of Main Arguments; 7.1 Brain Imaging Combining Structural and Functional MRI, EEG, MEG and Unit Recordings; 7.2 Significance of RGT for Brain Modeling; 7.2.1 Relevance to Brain Diseases; 7.2.2 Neuropercolation as a Novel Mathematical Tool; 7.3 Neuromorphic Nanoscale Hardware Platforms
Control code
SPR927404605
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319244068
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-24406-8
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Label
Cognitive phase transitions in the cerebral cortex : enhancing the neuron doctrine by modeling neural fields, Robert Kozma, Walter J. Freeman, (electronic book)
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Acknowledgments; Commentators; Contents; Part I Review of Dynamical Brain Theoriesand Experiments; 1 Introduction -- On the Languages of Brains; 1.1 Brains Are Not Computers; 1.2 Symbolic Approaches to Brains; 1.3 Connectionism; 1.4 Brains as Transient Dynamical Systems; 1.5 Random Graph Theory (RGT) for Brain Models; 1.6 Neuropercolation Modeling Paradigm; References; 2 Experimental Investigation of High-Resolution Spatio-Temporal Patterns; 2.1 Method; 2.1.1 Experiments with Rabbits; 2.1.2 Human ECoG Experiments; 2.1.3 Scalp EEG Design Considerations
  • 2.2 Temporal Patterns: The Carrier Wave2.3 Spatial Patterns of Amplitude Modulation (AM) and Phase Modulation (PM); 2.4 Classification of ECoG and EEG AM Patterns; 2.5 Characterization of Synchronization-Desynchronization Transitions in the Cortex; 2.6 Experimental Observation of Singularity; 2.7 Transmission of Macroscopic Output by Microscopic Pulses; References; 3 Interpretation of Experimental Results As Cortical Phase Transitions; 3.1 Theoretical Approaches to Nonlinear Cortical Dynamics; 3.2 Scales of Representation: Micro-, Meso-, and Macroscopic Levels
  • 3.3 Cinematic Theory of Cortical Phase Transitions3.4 Characterization of Phase Transitions; 3.4.1 Critical State; 3.4.2 Singular Dynamics; 3.4.3 Symmetry Breaking; 3.4.4 Transition Energy; 3.4.5 Zero Order Parameter; 3.4.6 Correlation Length Divergence; References; 4 Short and Long Edges in Random Graphs for Neuropil Modeling; 4.1 Motivation of Using Random Graph Theory for Modeling Cortical Processes; 4.2 Glossary of Random Graph Terminology; 4.3 Neuropercolation Basics; 4.4 Critical Behavior in Neuropercolation with Mean-Field, Local, and Mixed Models; 4.4.1 Mean-Field Approximation
  • 4.4.2 Mixed Short and Long Connections4.5 Finite Size Scaling Theory of Criticality in Brain Models ; References; 5 Critical Behavior in Hierarchical Neuropercolation Models of Cognition; 5.1 Basic Principles of Hierarchical Brain Models; 5.2 Narrow-Band Oscillations in Lattices with Inhibitory Feedback; 5.3 Broad-Band Oscillations in Coupled Multiple Excitatory-Inhibitory Layers; 5.4 Exponentially Expanding Graph Model; References; 6 Modeling Cortical Phase Transitions Using Random Graph Theory; 6.1 Describing Brain Networks in Terms of Graph Theory
  • 6.1.1 Synchronization and the 'Aha' Moment6.1.2 Practical Considerations on Synchrony; 6.1.3 Results of Synchronization Measurements; 6.2 Evolution of Critical Behavior in the Neuropil -- a Hypothesis; 6.3 Singularity and sudden transitions -- Interpretation of Experimental Findings; References; 7 Summary of Main Arguments; 7.1 Brain Imaging Combining Structural and Functional MRI, EEG, MEG and Unit Recordings; 7.2 Significance of RGT for Brain Modeling; 7.2.1 Relevance to Brain Diseases; 7.2.2 Neuropercolation as a Novel Mathematical Tool; 7.3 Neuromorphic Nanoscale Hardware Platforms
Control code
SPR927404605
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9783319244068
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-24406-8
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

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