How the cerebral cortex operates near a critical phase transition point for optimum performance.
Individual neurons have limited computational powers, but when they work together, it is almost like magic. Firing synchronously and then breaking off to improvise by themselves, they can be paradoxically both independent and interdependent. This happens near the critical point: when neurons are poised between a phase where activity is damped and a phase where it is amplified, where information processing is optimized, and complex emergent activity patterns arise. The claim that neurons in the cortex work best when they operate near the critical point is known as the criticality hypothesis. In this book John Beggs—one of the pioneers of this hypothesis—offers an introduction to the critical point and its relevance to the brain.
Drawing on recent experimental evidence, Beggs first explains the main ideas underlying the criticality hypotheses and emergent phenomena. He then discusses the critical point and its two main consequences—first, scale-free properties that confer optimum information processing; and second, universality, or the idea that complex emergent phenomena, like that seen near the critical point, can be explained by relatively simple models that are applicable across species and scale. Finally, Beggs considers future directions for the field, including research on homeostatic regulation, quasicriticality, and the expansion of the cortex and intelligence. An appendix provides technical material; many chapters include exercises that use freely available code and data sets.
Author(s): John M. Beggs
Edition: 1
Publisher: The MIT Press
Year: 2022
Language: English
Pages: 216
City: London
Tags: Cerebral Cortex; Brain; Neurology; Cortex Critical Point
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
Chapter Summary
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
Chapter Summary
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
Chapter Summary
5. Universality
Universality in Physical Systems
Universality in the Cortex: Indicators
Indicators Seen across Species
Indicators Seen across Scales
Described by a Simple Model
Chapter Summary
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
Chapter Summary
7. Quasicriticality
Universality: Unfinished Issues
A Possible Solution: Quasicriticality
Another View: Slightly Subcritical
Another View: Subsampling
Another View: Griffiths Phase
Chapter Summary
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
Chapter Summary
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
