This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. Readers will learn the basic concepts and methods of complex system research. The book is not highly technical mathematically, but teaches and uses the basic mathematical notions of dynamical system theory, making the book useful for students of science majors and graduate courses.

This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematical models can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.

This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematical models can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. It illuminates how complex collective behavior emerges from the parts of a system, due to the interaction between the system and its environment. Readers will learn the basic concepts and methods of complex system research. The book is not highly technical mathematically, but teaches and uses the basic mathematical notions of dynamical system theory, making the book useful for students of science majors and graduate courses.

This volume contains invited and contributed papers presented at the eighth edition of the International Summer School on Neural Networks, dedicated to Prof.EduardoR.Caianiello.Theschoolwasestablishedin1996byProf.Antonio Zichichi, director of the Ettore Maiorana Centre for Scienti?c Culture in Erice (Sicily), and Prof. Maria Marinaro, director of the International Institute for Advanced Scienti?c Studies in Vietri sul Mare, in Italy. The school is held each year,alternatingbetweenEriceandVietri,proposingsurveysonseveralresearch ?elds related to cybernetics studies and human-machine interaction. The eighth edition of the school was on cortical dynamics and was held in Erice. The contributions collected in this book are aimed at providing primarily high-level tutorial coverage of the ?elds related to cortical dynamics, repo- ing recent experimental and theoretical results investigating the processing, the transmission, and the imprinting of information in the brain, and important functions of the cortical area such as cortical rhythms, cortical neural plasticity, and their structural basis and functional signi?cance. Height surveys, reporting the most recent original results, are o?ered by specialists in the ? eld. Consequently, the volume may be used as a reference book on models of cortical dynamics from neuroscienceand physics. To this aim the volume is divided into two sections: fundamentals of cortical dynamics, and mathematical models of cortical dynamics.

This book propagates a new way of thinking about managing our resources by integrating the perspectives of complex systems theory and social psychology. By resources, the authors mean objects, such as cell phones and cars, and human resources, such as family members, friends, and the small and large communities they belong to. As we all face the "replace or repair" dichotomy, readers will understand how to repair themselves, their relationships, and communities, accept the "new normal," and contribute to repairing the world. The book is offered to Zoomers, growing up in a world where it seems everything is falling apart; people in their 30s and 40s, who are thinking about how to live a fulfilling life; people from the Boomers generation, who are thinking back on life and how to repair relationships. The Reader will enjoy the intellectual adventure of connecting the natural and social worlds and understanding the transition's pathways from a "throwaway society" to a "repair society.

Human beings are competitive. We want to know who is the strongest, who is the richest, and who is the cleverest of all. Some situations, like ranking people based on height, can be ranked in objective ways. However, many "Top Ten" lists are based on subjective categorization and give only the illusion of objectivity. In fact, we don't always want to be seen objectively since we don't mind having a better image or rank than deserved. Ranking: The Unwritten Rules of the Social Game We All Play applies scientific theories to everyday experience by raising and answering questions like: Are college ranking lists objective? How do we rank and rate countries based on their fragility, level of corruption, or even happiness? How do we find the most relevant web pages? How are employees ranked? This book is for people who have a neighbor with a fancier car; employees, who are being ranked by their supervisors; managers, who are involved in ranking but may have qualms about the process; businesspeople interested in creating better visibility for their companies; scientists, writers, artists, and other competitors who would like to see themselves at the top of a success list; or college students who are just preparing to enter a new phase of social competition. Readers will engage in an intellectual adventure to better understand the difficulties of navigating between objectivity and subjectivity and to better identify and modify their place in real and virtual communities by combining human and computational intelligence. Translation editions available in German, Korean, Japanese, Complex Chinese, and Simplified Chinese.

In Neural Organization, Arbib, Erdi, and Szentagothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. In Neural Organization, Arbib, Erdi, and Szentagothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. Both structure-based "bottom-up" and function- based "top-down" models offer coherent concepts by which to evaluate the experimental data. The goal of this book is to point out the advantages of a multidisciplinary, multistrategied approach to the brain. Part I of Neural Organization provides a detailed introduction to each of the three areas of structure, function, and dynamics. Structure refers to the anatomical aspects of the brain and the relations between different brain regions. Function refers to skills and behaviors, which are explained by means of functional schemas and biologically based neural networks. Dynamics refers to the use of a mathematical framework to analyze the temporal change of neural activities and synaptic connectivities that underlie brain development and plasticity-in terms of both detailed single-cell models and large-scale network models. In part II, the authors show how their systematic approach can be used to analyze specific parts of the nervous system-the olfactory system, hippocampus, thalamus, cerebral cortex, cerebellum, and basal ganglia-as well as to integrate data from the study of brain regions, functional models, and the dynamics of neural networks. In conclusion, they offer a plan for the use of their methods in the development of cognitive neuroscience.