Foreword by Walter J. Freeman. The induction of unconsciousness using anesthetic agents demonstrates that the cerebral cortex can operate in two very different behavioral modes: alert and responsive vs. unaware and quiescent. But the states of wakefulness and sleep are not single-neuron properties---they emerge as bulk properties of cooperating populations of neurons, with the switchover between states being similar to the physical change of phase observed when water freezes or ice melts. Some brain-state transitions, such as sleep cycling, anesthetic induction, epileptic seizure, are obvious and detected readily with a few EEG electrodes; others, such as the emergence of gamma rhythms during cognition, or the ultra-slow BOLD rhythms of relaxed free-association, are much more subtle. The unifying theme of this book is the notion that all of these bulk changes in brain behavior can be treated as phase transitions between distinct brain states. Modeling Phase Transitions in the Brain contains chapter contributions from leading researchers who apply state-space methods, network models, and biophysically-motivated continuum approaches to investigate a range of neuroscientifically relevant problems that include analysis of nonstationary EEG time-series; network topologies that limit epileptic spreading; saddle--node bifurcations for anesthesia, sleep-cycling, and the wake--sleep switch; prediction of dynamical and noise-induced spatiotemporal instabilities underlying BOLD, alpha-, and gamma-band Hopf oscillations, gap-junction-moderated Turing structures, and Hopf-Turing interactions leading to cortical waves.
The unifying theme of this book is the notion that all of these bulk changes in brain behavior can be treated as phase transitions between distinct brain states.
... is the analytic amplitude (the blue curve in Fig.9.1c), dt, (9.2) Aj(t) = √ ( v2j(t) + u2j(t) ) , (9.3) and the arctangent of the angle of the vector with respect to the real axis is the analytic phase (blue sawtooth in Fig.9.1d), ...
Written at an undergraduate mathematical level, this book provides the essential theoretical tools and foundations required to develop basic models to explain collective phase transitions for a wide variety of ecosystems.
Leading authorities in the field review current experimental and theoretical knowledge on criticality and brain function. The book begins by summarizing experimental evidence for criticality and self-organized criticality in the brain.
Written at an undergraduate mathematical level, this book provides the essential theoretical tools and foundations required to develop basic models to explain collective phase transitions for a wide variety of ecosystems.
Color represents the difference between the Granger causality values of each direction (larger—smaller), if both values were statistically significant. c Coherence-derived networks in theta (5–8 Hz), delta (1–5 Hz), and high gamma ...
This book introduces and explains techniques brought from physics to the study of neural networks.
... Brain: A Neuroscientist's Quest for What Makes Us Human, W.W. Norton & Company, New York (2011). 2. A. Steyn-Ross and M. Steyn-Ross (Eds.), Modeling Phase Transitions in the Brain, Springer, New York (2010). 3. https://en.wikipedia.org ...
A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience.
A serious review of live issues in science - from interaction and correlation to emergence, scale invariance, attractors, noise and chaos-this book demonstrates their relevance to intelligence and consciousness.