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The Magical Dance of Brain Waves: Why Does EEG Reveal the Deeper Workings of Our Minds?
In the field of computational neuroscience, the "metastable" theory reveals the ability of the human brain to integrate multiple functional parts and generate neural oscillations in a coordinated manner, which lays the foundation for conscious activities. Metastability is a state in which a signal (such as an oscillating wave) is outside of its natural equilibrium state but can persist for an extended period of time, a principle that describes how the brain makes sense of seemingly random environmental cues. Over the past 25 years, interest in metastable states and their nonlinear dynamics has grown as computer simulations of brain activity have advanced.
Overview
An electroencephalogram (EEG) measures the overall electrical activity of the brain and is observed on the surface of the skull. In metastability theory, the EEG output produces oscillatory patterns that can be described and that are correlated at certain frequencies. Each neuron in a neural network usually outputs a dynamic oscillating waveform, and also has the ability to output chaotic waveforms. When neurons are integrated into neural networks through their interfaces with each other, the dynamic oscillations created by each neuron can combine to form highly predictable EEG pulses. By identifying these associations and the individual neurons that contribute to predictable EEG spikes, scientists were able to determine which cortical areas are processing in parallel and which neural networks are intertwined.
In many cases, metastability describes how distant parts of the brain interact in response to environmental stimuli.
Metastable Frequency Domain
Research suggests that one of the brain dynamics that underpins conscious thought is the brain's ability to transform seemingly noisy or chaotic signals into predictable oscillation patterns. In EEG oscillations of neural networks, the frequencies of adjacent waveforms are correlated on a logarithmic scale rather than a linear scale. Therefore, the average frequencies in the oscillation band cannot be linked together according to the linear relationship of their average frequencies. In contrast, phase transitions are linked according to their coupling capabilities with adjacent phases, always between unstable and stable phase synchronization transitions. This phase synchronization forms the basis for metastable behavior in neural networks.
Theory of Metastability
Oscillatory activity and coordination dynamics
Dynamic system models represent networks consisting of integrated neural systems as a theory of communication between unstable and stable phases. Coordination dynamics forms the basis of this dynamic system model, describing mathematical formulas and paradigms that regulate the coupling between environmental stimuli and their effects.
History of Coordination Dynamics and the Haken-Kelso-Bunz (HKB) Model
The so-called HKB model is an early and respected theory describing the coordination dynamics of the brain. The model describes in part the formation of neural networks as self-organization, where individual neurons and small neural systems aggregate and coordinate to adapt or respond to local stimuli. Over time, the HKB model has become increasingly popular in explaining the coordinated movements and behaviors of individual neurons up to large neural networks. This model originally described a series of spontaneous transitions in phase motion.
In the HKB model experiment, subjects were asked to use their respective fingers to move in two movement patterns: the first was asynchronous movement, and the second was synchronous movement.
This theory continues to evolve with our deeper understanding of the nervous system, attempting to reveal how synchronized activity in different areas of the brain affects the formation of individual consciousness.
Future-oriented metastable research
Current research not only focuses on exploring the impact of metastable interactions on social functions, but also increasingly focuses on exploring coordinated dynamic systems and global workspaces in Alzheimer's disease, Parkinson's disease, stroke, schizophrenia, etc. Role in the progression of degenerative diseases.
As attention to the effects of traumatic or semi-traumatic brain injury grows, the exploration of metastability in contemporary neuroscience will undoubtedly continue. The brain's magical dance makes us rethink the boundaries between consciousness and unconsciousness, and how these boundaries affect our daily lives.
