Fractals Of Brain Fractals Of Mind

This collective volume is the first to discuss systematically what are the possibilities to model different aspects of brain and mind functioning with the formal means of fractal geometry and deterministic chaos. At stake here is not an approximation to the way of actual performance, but the possibility of brain and mind to implement nonlinear dynamic patterns in their functioning. The contributions discuss the following topics (among others): the edge-of-chaos dynamics in recursively organized neural systems and in intersensory interaction, the fractal timing of the neural functioning on different scales of brain networking, aspects of fractal neurodynamics and quantum chaos in novel biophysics, the fractal maximum-power evolution of brain and mind, the chaotic dynamics in the development of consciousness, etc. It is suggested that the ‘margins’ of our capacity for phenomenal experience, are ‘fractal-limit phenomena’. Here the possibilities to prove the plausibility of fractal modeling with appropriate experimentation and rational reconstruction are also discussed. A conjecture is made that the brain vs. mind differentiation becomes possible, most probably, only with the imposition of appropriate symmetry groups implementing a flowing interface of features of local vs. global brain dynamics. (Series B)

The Fractal Brain Theory, or the Symmetry, Self Similarity and Recursivity Theory of Brain and Mind, is a Revolutionary new way of looking at the nature of intelligence and also genomics. It is the key to a powerful and new kind of Recursively Self Modifying Artificial Intelligence. Wai H. Tsang presents an exciting new synthesis of all things psychological, linguistic, neuroscientific, genomic, evolutionary, informatic, computational, complex and fractal. Dealing with the most central puzzles of mind science and AI, and weaving in some of the most fundamental concepts in mathematics such as symmetry, geometry, functions, discrete maths and formal axiomatic systems. This book presents nothing less than a seamless unified theory of Brain, Mind, Artificial Intelligence, Functional Genomics, Ontogenesis and Evolution. Also covering topics such as the quest for the Perfect & Universal Language, Recursively Self Modifying Algorithms, Super Intelligence & Technological Singularity.

Reviews the most intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and disadvantages. Will bring an understanding of fractals to clinicians and researchers also if they do not have a mathematical background, and will serve as a good tool for teaching the translational applications of computational models to students and scholars of different disciplines. This comprehensive collection is organized in four parts: (1) Basics of fractal analysis; (2) Applications of fractals to the basic neurosciences; (3) Applications of fractals to the clinical neurosciences; (4) Analysis software, modeling and methodology.

Fractal dynamics provide an unparalleled tool for understanding the evolution of natural complexity throughout physical, biological, and psychological realms. This book’s conceptual framework helps to reconcile several persistent dichotomies in the natural sciences, including mind-brain, linear-nonlinear, subjective-objective, and even personal-transpersonal processes. A fractal approach is especially useful when applied to recursive processes of consciousness, both within their ordinary and anomalous manifestations. This novel way to study the interconnection of seemingly divided wholes encompasses multiple dimensions of experience and being. It brings together experts in diverse fields—neuropsychologists, psychiatrists, physicists, physiologists, psychoanalysts, mathematicians, and professors of religion and music composition—to demonstrate the value of fractals as model, method, and metaphor within psychology and related social and physical sciences. The result is a new perspective for understanding what has often been dismissed as too subjective, idiosyncratic, and ineffably beyond the scope of science, bringing these areas back into a natural-scientific framework.

Even though the fractal approach to sustainability and organizational change management is not new, no authors so far seem to have truly attempted to use fractals as a mathematical means to map and measure organizational sustainability. Several sustainability maturity models and change management models and frameworks, concepts and computer generated systems came to the fore during the past two decades. They provided a set of useful tools for managers, academics and students to refer to, or on which to base their own actions and plans. However, one issue remains: most of those models and frameworks share a rather similar linear ‘skeleton’; the main difference between them is the quantitative variety of steps within each phase, stage, and parameter and how in depth each of these is presented. The authors' work addresses a clear gap in the literature and in applied research, as it emphasizes the relevance of using a complex mathematically-based but user-friendly fractal approach. Readers are able to better understand, implement, map and measure change management processes leading to a sustainability-focused mindset. Subsequent chapters guide you through the steps towards creating committed sustainability-based strategies, attitudes, actions and practices across all levels in the broad organizational context. This text is essential reading for students researching business and management and who are interested in the Fractal Sustainability concept.

The book is characterized by the illustration of cases of fractal, self-similar and multi-scale structures taken from the mechanics of solid and porous materials, which have a technical interest. In addition, an accessible and self-consistent treatment of the mathematical technique of fractional calculus is provided, avoiding useless complications.

The possibility of direct interfacing between biological and technological information devices could result in a merger of mind and machine - Ultimate Computing. This book, a thorough consideration of this idea, involves a number of disciplines, including biochemistry, cognitive science, computer science, engineering, mathematics, microbiology, molecular biology, pharmacology, philosophy, physics, physiology, and psychology.

These new studies by prominent neuroscientists, psychologists and philosophers work toward a coherent framework for understanding emotion and its contribution to the functioning of consciousness in general, as an aspect of self-organizing, embodied subjects. Distinguishing consciousness from unconscious information processing hinges on the role of motivating emotions in all conscious modalities, and how emotional brain processes interact with those traditionally associated with cognitive function. Computationally registering/processing sensory signals (e.g. in the occipital lobe or area V4) by itself does not result in perceptual consciousness, which requires subcortical structures such as amygdala, hypothalamus, and brain stem. This interdisciplinary anthology attempts to understand the complexity of emotional intentionality; why the role of motivation in self-organizing processes is crucial in distinguishing conscious from unconscious processes; how emotions account for 'agency'; and how an adequate approach to emotion-motivation can address the traditional mind-body problem through a holistic understanding of the conscious, behaving organism. (Series B)

There are new and important advancements in today’s complexity theories in ICT and requires an extraordinary perspective on the interaction between living systems and information technologies. With human evolution and its continuous link with the development of new tools and environmental changes, technological advancements are paving the way for new evolutionary steps. Complexity Science, Living Systems, and Reflexing Interfaces: New Models and Perspectives is a collection of research provided by academics and scholars aiming to introduce important advancements in areas such as artificial intelligence, evolutionary computation, neural networks, and much more. This scholarly piece will provide contributions that will define the line of development in complexity science.