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The cortex and the critical point : understanding the power of emergence / John M. Beggs.
Author
Beggs, John M.
[Browse]
Format
Book
Language
English
Εdition
1st ed.
Published/Created
Cambridge, Massachusetts : The MIT Press, [2022]
Description
1 online resource (217 pages)
Availability
Available Online
DOAB Directory of Open Access Books
CogNet Library Books
MIT Press Direct to Open 2022 Complete Monographs
Details
Subject(s)
Cerebral cortex
[Browse]
Brain
[Browse]
Neurology
[Browse]
Series
The MIT Press
Summary note
"A survey of the criticality hypothesis which imports theory from physics to understand the brain and could be a grand unifying theory of the brain at a time when neuroscience is dominated by data"-- Provided by publisher.
Source of description
OCLC-licensed vendor bibliographic record.
Language note
English
Contents
Intro
Contents
Acknowledgments
Introduction
The Critical Point in Context
The Goals and Structure of This Book
I. Background
1. The Main Idea
A Simple Model
Optimal Information Processing
The Appearance of Emergent Phenomena
Power Laws
Avalanches
A Phase Transition
From a Model to Data
The Criticality Hypothesis
Objections and Responses to the Criticality Hypothesis
Chapter Summary
2. Emergent Phenomena
Methodological Reductionism
The Wave as an Emergent Phenomenon
Emergent Phenomena in the Brain
A Simple Model of Emergent Phenomena in the Brain
Complex Emergent Phenomena Occur at a Phase Transition
More Complex Emergent Phenomena?
How to Study Emergent Phenomena
II. The Critical Point and Its Consequences
3. The Critical Point
The Branching Model: A Branching Ratio Near 1
The Branching Model: A Phase Transition with Control and Order Parameters
The Branching Model: An Exponent Relation between Multiple Power Laws
The Branching Model: Fractal Copies of Avalanches
Signatures of Being near the Critical Point
Signatures of the Critical Point from the Data
In Vitro Experiments
Data: A Branching Ratio near 1
Data: A Phase Transition with Control and Order Parameters
Data: An Exponent Relation between Multiple Power Laws
Data: Fractal Copies of Avalanches
Objections to These Signatures of Criticality
4. Optimality
The Branching Model: Information Transmission
The Branching Model: Dynamic Range
The Branching Model: Susceptibility
Data: Dynamic Range
Data: Information Transmission
Data: Susceptibility
Other Predictions Yet to Be Tested
5. Universality
Universality in Physical Systems
Universality in the Cortex: Indicators.
Indicators Seen across Species
Indicators Seen across Scales
Described by a Simple Model
III. Future Directions
6. Homeostasis and Health
Homeostasis toward the Critical Point after a Major Perturbation
Sleep and Homeostasis toward the Critical Point
Sensory Adaptation toward the Critical Point
Development toward the Critical Point
Themes from Homeostasis Results
Health
7. Quasicriticality
Universality: Unfinished Issues
A Possible Solution: Quasicriticality
Another View: Slightly Subcritical
Another View: Subsampling
Another View: Griffiths Phase
8. Cortex
The Expansion of Cortical Area
Associations of Associations
The Special Role of Layers 2 and 3
Multifunctionality and the Critical Point
Nearly Critical in Layers 2 and 3, but Not in Layer 5
Staying Nearly Critical While Learning
Timescales throughout the Hierarchy
9. Epilogue
What We Know
What We Don't Know
Frontier Issues
What I Did Not Cover
Appendix
Relation between Power-Law Exponent and Slope (Chapters 1 and 6)
When the Average Value of a Power Law Diverges and When It Does Not (Chapters 1 and 6)
Long-Range Temporal Correlations (Chapters 1, 6, and 8)
Informal Derivation of the Exponent Relation (Chapters 3, 5, 6, 7, and 8)
Avalanche Shape Collapse (Chapters 3, 5, 6, and 8)
How to Quantify Network Dynamics (Chapters 4 and 8)
Software and Data for Exercises and Analyses
Notes
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
References
Index.
Show 97 more Contents items
ISBN
0-262-37034-4
OCLC
1333708308
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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