Frontiers | Why Brain Criticality Is Clinically Relevant: A Scoping Review

brain-criticalityneuroscienceepilepsyself-organized-criticalityphase-transitions

Abstraction: Scoping review of brain criticality theory and clinical applications

Key points:

Brain criticality hypothesis: neural networks self-organize to a critical state (between ordered and disordered phases) that maximizes information transmission, storage, dynamic range, and computational power
Key markers of criticality include: branching parameter σ ≈ 1, long-range temporal correlation (LRTC, measured by DFA/Hurst exponent), power-law distributed avalanche sizes, and shape collapse of avalanche profiles
Self-organized criticality (SOC) proposes the control parameter is autonomously tuned to the critical value via decentralized feedback (e.g., homeostatic plasticity); rat cortical networks lost criticality after visual deprivation but recovered within 48 h
Clinical domains reviewed (78 studies): anesthesia, epilepsy, neurodegeneration, neurodevelopment, cognition, sleep medicine, psychiatry
Epilepsy application: seizures show SOC-like properties (power-law inter-seizure intervals, Omori-law temporal clustering analogous to earthquakes); LRTC and Hurst exponent can aid seizure localization and potentially prediction; signal correlations in ECoG extended up to 40 days before seizure onset
Debate remains on whether seizures represent a critical phenomenon or a departure from the resting brain's critical state; the "avalanche approach" and "earthquake approach" examine different variables and may not be directly comparable

Connections: Brain Criticality · Self Organized Criticality · Phase Transitions · Neural Avalanches