Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields - Kozma, Robert; Freeman, Walter J.; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2016)
This intriguing book was born out of the many discussions the authors had in the past 10 years about the role of scale-free structure and dynamics in producing intelligent behavior in brains. The microscopic dynamics of neural networks is well described by the prevailing paradigm based in a narrow interpretation of the neuron doctrine. This book broadens the doctrine by incorporating the dynamics of neural fields, as first revealed by modeling with differential equations (K-sets).  The book broadens that approach by application of random graph theory (neuropercolation). The book concludes with diverse commentaries that exemplify the wide range of mathematical/conceptual approaches to neural fields. This book is intended for researchers, postdocs, and graduate students, who see the limitations of network theory and seek a beachhead from which to embark on mesoscopic and macroscopic neurodynamics.
Keywords: Computational intelligence; Artificial intelligence; Dynamics; Nonlinear theories; Cognitive psychology; Computational Intelligence; Artificial Intelligence; Applied Dynamical Systems; Cognitive Psychology