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Principles of Brain Dynamics : Global State Interactions.

By: Contributor(s): Material type: TextTextSeries: Computational Neuroscience SeriesPublisher: Cambridge : MIT Press, 2012Copyright date: ©2012Edition: 1st edDescription: 1 online resource (355 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780262305587
Subject(s): Genre/Form: Additional physical formats: Print version:: Principles of Brain DynamicsDDC classification:
  • 612.8/2
LOC classification:
  • QP376 -- .P75 2012eb
Online resources:
Contents:
Intro -- Contents -- Series Foreword -- Introduction -- 1 The Dynamical and Structural Basis of Brain Activity -- 1.1 Introduction -- 1.2 Attractors and Brain Dynamics -- 1.3 Autonomous Brain Dynamics -- 1.4 Conclusion -- 2 Functional Connectivity, Neurocognitive Networks, and Brain Dynamics -- 2.1 A Connectivity and Network Perspective on Cognition -- 2.2 Identifying Major Cognitive Networks -- 2.3 Intrinsic Connectivity Networks -- 2.4 Three Core Neurocognitive Networks -- 2.5 Dynamics of Signaling in the CEN, SN, and DMN -- 2.6 A Dynamical Network Model of Saliency, Attention, and Control -- 2.7 Conclusion -- 3 Decoding Mental States from Patterns of Brain Activity -- 3.1 Introduction -- 3.2 Multivariate Decoding -- 3.3 Decoding Dynamics -- 3.4 Conclusion -- 4 Transient Brain Dynamics -- 4.1 Transients versus Attractors in Perception -- 4.2 Robustness through Metastability: Winnerless Competition -- 4.3 Hierarchical Competition: Canonical Models -- 4.4 Modulation Instability and Resting-State Dynamics -- 4.5 Modeling Psychopathology -- 4.6 Conclusion -- 5 A Dynamic Field Account of Language-Related Brain Potentials -- 5.1 Introduction -- 5.2 ERP Experiment -- 5.3 Dynamic Cognitive Modeling -- 5.4 Conclusion -- 6 Recognition of Sequences of Sequences Using Nonlinear Dynamical Systems -- 6.1 Introduction -- 6.2 Stable Heteroclinic Channels -- 6.3 Hierarchies of Stable Heteroclinic Channels -- 6.4 Bayesian Recognition Using SHC Hierarchies -- 6.5 A Model of Speech Recognition -- 6.6 Some Simulated Examples -- 6.7 Discussion -- 7 The Stability of Information Flows in the Brain -- 7.1 How to Define an Information Flow in the Brain? -- 7.2 Working Memory Capacity -- 7.3 Limits of Sequential Language Processing -- 7.4 Interaction of Heteroclinic Channels: Binding Problem -- 7.5 Sequential Decision Making -- 7.6 Future Directions.
8 Multiscale Electroencephalographic Dynamics and Brain Function -- 8.1 Neuronal Correlates of Electroencephalographic and Local Field Potential Rhythms -- 8.2 Measuring Multiscale Field Dynamics -- 8.3 Spatiotemporal Field Dynamics in Sleep -- 8.4 Mechanisms of Neuronal Synchronization -- 8.5 Effects of Electrical Fields on Neuronal Activity during Sleep -- 8.6 Conclusion -- 9 Mapping the Multiscale Information Content of Complex Brain Signals -- 9.1 Brain as a Complex System -- 9.2 Information-Theoretic Tools -- 9.3 Information and Nonlinear Dynamics -- 9.4 Approximate and Sample Entropy -- 9.5 Estimation of Sample Entropy -- 9.6 Multiscale Entropy -- 9.7 Applications of Multiscale Entropy -- 9.8 Complexity and Spectral Power -- 9.9 Complexity and Nonstationarity -- 9.10 Complexity and Network Structure -- 9.11 Conclusion -- 10 Connectivity and Dynamics of Neural Information Processing -- 10.1 Introduction -- 10.2 Structured Flows as Functional Units of Processes -- 10.3 Structured Flows on Manifolds -- 10.4 Emergence of SFMs from Spiking Neuron Networks -- 10.5 Functional Architectures: SFM and Timescale Hierarchies -- 10.6 Discussion -- 11 Transient Motor Behavior and Synchronization in the Cortex -- 11.1 Motor Behavior and Loss of Stability -- 11.2 Behavioral Models -- 11.3 A Model for Cortical Areas -- 11.4 Neural Mass Models - From Coupled Oscillators to Network Activity -- 11.5 Conclusion -- 12 Free Energy and Global Dynamics -- 12.1 Introduction -- 12.2 The Free-Energy Principle -- 12.3 Action and Its Observation -- 12.4 Conclusion -- 13 Perception, Action, and Utility: The Tangled Skein -- 13.1 Introduction -- 13.2 The Classical View -- 13.3 Segregation of Probability and Utility in the Brain? -- 13.4 Approximate Inference -- 13.5 New Vistas -- 13.6 Conclusion -- 14 Short Guide to Modern Nonlinear Dynamics -- 14.1 Dynamical Systems.
14.2 Chaotic Dynamics -- 14.3 Homoclinic and Heteroclinic Dynamics -- 14.4 Conclusion -- Contributors -- Index.
Summary: Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field.
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Intro -- Contents -- Series Foreword -- Introduction -- 1 The Dynamical and Structural Basis of Brain Activity -- 1.1 Introduction -- 1.2 Attractors and Brain Dynamics -- 1.3 Autonomous Brain Dynamics -- 1.4 Conclusion -- 2 Functional Connectivity, Neurocognitive Networks, and Brain Dynamics -- 2.1 A Connectivity and Network Perspective on Cognition -- 2.2 Identifying Major Cognitive Networks -- 2.3 Intrinsic Connectivity Networks -- 2.4 Three Core Neurocognitive Networks -- 2.5 Dynamics of Signaling in the CEN, SN, and DMN -- 2.6 A Dynamical Network Model of Saliency, Attention, and Control -- 2.7 Conclusion -- 3 Decoding Mental States from Patterns of Brain Activity -- 3.1 Introduction -- 3.2 Multivariate Decoding -- 3.3 Decoding Dynamics -- 3.4 Conclusion -- 4 Transient Brain Dynamics -- 4.1 Transients versus Attractors in Perception -- 4.2 Robustness through Metastability: Winnerless Competition -- 4.3 Hierarchical Competition: Canonical Models -- 4.4 Modulation Instability and Resting-State Dynamics -- 4.5 Modeling Psychopathology -- 4.6 Conclusion -- 5 A Dynamic Field Account of Language-Related Brain Potentials -- 5.1 Introduction -- 5.2 ERP Experiment -- 5.3 Dynamic Cognitive Modeling -- 5.4 Conclusion -- 6 Recognition of Sequences of Sequences Using Nonlinear Dynamical Systems -- 6.1 Introduction -- 6.2 Stable Heteroclinic Channels -- 6.3 Hierarchies of Stable Heteroclinic Channels -- 6.4 Bayesian Recognition Using SHC Hierarchies -- 6.5 A Model of Speech Recognition -- 6.6 Some Simulated Examples -- 6.7 Discussion -- 7 The Stability of Information Flows in the Brain -- 7.1 How to Define an Information Flow in the Brain? -- 7.2 Working Memory Capacity -- 7.3 Limits of Sequential Language Processing -- 7.4 Interaction of Heteroclinic Channels: Binding Problem -- 7.5 Sequential Decision Making -- 7.6 Future Directions.

8 Multiscale Electroencephalographic Dynamics and Brain Function -- 8.1 Neuronal Correlates of Electroencephalographic and Local Field Potential Rhythms -- 8.2 Measuring Multiscale Field Dynamics -- 8.3 Spatiotemporal Field Dynamics in Sleep -- 8.4 Mechanisms of Neuronal Synchronization -- 8.5 Effects of Electrical Fields on Neuronal Activity during Sleep -- 8.6 Conclusion -- 9 Mapping the Multiscale Information Content of Complex Brain Signals -- 9.1 Brain as a Complex System -- 9.2 Information-Theoretic Tools -- 9.3 Information and Nonlinear Dynamics -- 9.4 Approximate and Sample Entropy -- 9.5 Estimation of Sample Entropy -- 9.6 Multiscale Entropy -- 9.7 Applications of Multiscale Entropy -- 9.8 Complexity and Spectral Power -- 9.9 Complexity and Nonstationarity -- 9.10 Complexity and Network Structure -- 9.11 Conclusion -- 10 Connectivity and Dynamics of Neural Information Processing -- 10.1 Introduction -- 10.2 Structured Flows as Functional Units of Processes -- 10.3 Structured Flows on Manifolds -- 10.4 Emergence of SFMs from Spiking Neuron Networks -- 10.5 Functional Architectures: SFM and Timescale Hierarchies -- 10.6 Discussion -- 11 Transient Motor Behavior and Synchronization in the Cortex -- 11.1 Motor Behavior and Loss of Stability -- 11.2 Behavioral Models -- 11.3 A Model for Cortical Areas -- 11.4 Neural Mass Models - From Coupled Oscillators to Network Activity -- 11.5 Conclusion -- 12 Free Energy and Global Dynamics -- 12.1 Introduction -- 12.2 The Free-Energy Principle -- 12.3 Action and Its Observation -- 12.4 Conclusion -- 13 Perception, Action, and Utility: The Tangled Skein -- 13.1 Introduction -- 13.2 The Classical View -- 13.3 Segregation of Probability and Utility in the Brain? -- 13.4 Approximate Inference -- 13.5 New Vistas -- 13.6 Conclusion -- 14 Short Guide to Modern Nonlinear Dynamics -- 14.1 Dynamical Systems.

14.2 Chaotic Dynamics -- 14.3 Homoclinic and Heteroclinic Dynamics -- 14.4 Conclusion -- Contributors -- Index.

Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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