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An important aspect of neuroscience is to characterize the underlying connectivity patterns of the human brain (i.e., human connectomics). Over the past few years, researchers have demonstrated that by combining a variety of different neuroimaging technologies (e.g., structural MRI, diffusion MRI and functional MRI) with sophisticated analytic strategies such as graph theory, it is possible to noninvasively map the patterns of structural and functional connectivity of human whole-brain networks. With these novel approaches, many studies have shown that human brain networks have nonrandom properties such as modularity, small-worldness and highly connected hubs. Importantly, these quantifiable network properties change with age, learning and disease. Moreover, there is growing evidence for behavioral and genetic correlates. Network analysis of neuroimaging data is opening up a new avenue of research into the understanding of the organizational principles of the brain that will be of interest for all basic scientists and clinical researchers. Such approaches are powerful but there are a number of challenging issues when extracting reliable brain networks from various imaging modalities and analyzing the topological properties, e.g., definitions of network nodes and edges and reproducibility of network analysis. We assembled contributions related to the state-of-the-art methodologies of brain connectivity and the applications involving development, aging and neuropsychiatric disorders such as Alzheimer’s disease, schizophrenia, attention deficit hyperactivity disorder and mood and anxiety disorders. It is anticipated that the articles in this Research Topic will provide a greater range and depth of provision for the field of imaging connectomics.
connectomics --- connectivity --- graph theory --- Small-world --- MRI
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This book is prepared as a combination of the manuscripts submitted by respected mathematicians and scientists around the world. As an editor, I truly enjoyed reading each manuscript. Not only will the methods and explanations help you to understand more about graph theory, but I also hope you will find it joyful to discover ways that you can apply graph theory in your scientific field. I believe the book can be read from the beginning to the end at once. However, the book can also be used as a reference guide in order to turn back to it when it is needed. I have to mention that this book assumes the reader to have a basic knowledge about graph theory. The very basics of the theory and terms are not explained at the beginner level. I hope this book will support many applied and research scientists from different scientific fields.
Physical Sciences, Engineering and Technology --- Mathematics --- Discrete Mathematics --- Graph Theory
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According to the Semantic Web a formal representation of knowledge is described by an ontology. This formal representation enables a unique identification of elements within an ontology. By the use of natural language for element annotation, ambiguity occurs and a unique element identification based on natural language cannot be guaranteed. This book describes an approach to identify the most relevant element described by a natural language term by reducing the aspect of ambiguity to a minimum.
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This book compiles all articles within the Research Topic "Neuropsychology and neuropsychiatry of neurodegenerative disorders" published in the journal Frontiers in Aging Neuroscience. The call was launched in 2014 and closed in 2015 with 21 articles published. Papers deal on several important topics of neuropsychology -such as language and visuospatial functions- and neuropsychiatry - such us the emotional or motivational spheres - , and the interphase between them. There are also articles on psychometry, brain morphometry, brain connectivity, diagnostic tests and interventional studies. All these articles are focused on neurodegenerative conditions, mostly Alzheimer’s disease and Parkinson’s disease. Interestingly, several articles addressed the early stages of these diseases. All together, this Research Topic provides a rich perspective of the research made today around neuropsychological and neuropsychiatric aspects of neurodegenerative diseases. We hope readers enjoy this collection of articles.
Neuropsychology --- Neuropsychiatry --- Neurodegenerative Diseases --- Mild Cognitive Impairment --- Parkinson Disease --- Alzheimer Disease --- Neuroimaging --- Neuropsychological Tests --- Emotions --- graph theory
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This book constitutes the proceedings of the 21st International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2018, which took place in Thessaloniki, Greece, in April 2018, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2018.The 31 papers presented in this volume were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections named: semantics; linearity; concurrency; lambda-calculi and types; category theory and quantum control; quantitative models; logics and equational theories; and graphs and automata.
artificial intelligence --- computer software --- selection and evaluation --- formal logic --- graph theory --- modal logic --- petri nets --- program compilers --- programming language --- semantics --- separation logic --- software engineering --- theorem proving --- type systems --- verification
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This open access book explores the amazing similarity between paths taken by people and many other things in life, and its impact on the way we live, teach and learn. Offering insights into the new scientific field of paths as part of the science of networks, it entertainingly describes the universal nature of paths in large networked structures. It also shows the amazing similarity in the ways humans and other – even nonliving – things navigate in a complex environment, to allow readers to easily grasp how paths emerge in many walks of life, and how they are navigated. Paths is based on the authors recent research in the area of paths on networks, which points to the possible birth of the new science of “paths” as a natural consequence ‘and extension) of the science of “networks.” The approach is essentially story-based, supported by scientific findings, interdisciplinary approaches, and at times, even philosophical points of view. It also includes short illustrative anecdotes showing the amazing similarities between real-world paths and discusses their applications in science and everyday life. Paths will appeal to network scientists and to anyone interested in popular science. By helping readers to step away from the “networked” view of many recent popular scientific books and start to think of longer paths instead of individual links, it sheds light on these problems from a genuinely new perspective. --------------------------------------------------------------------------------- The path is the goal. The essence behind this short sentence is known to many people around the world, expressed through the interpretations of some of the greatest thinkers like Lao-Tze and Gandhi. It means that it is the journey that counts, not the destination. When speaking about such subjective and intangible things, philosophy and religion are some of the only approaches that are addressed. In this book, the authors address this conventional wisdom from the perspective of natural science. They explore a sequence of steps that leads the reader closer to the nature of paths and accompany him on the search for “the path to paths”.
Popular Science in Mathematics --- Mathematics --- network science --- graph theory --- path --- shortest path --- internet --- brain --- routing policy --- social networks --- artificial networks --- computer networks --- road networks --- open access --- Popular and recreational mathematics
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Symmetry is found everywhere, to a greater or lesser degree. It is essential in all sciences and also as the basic substrate in all arts. The same happens with Complex Networks, which are the majority of all those that interest for advanced knowledge, that is, for research. That is why these two themes have been unified here, whose intersection we are dealing with: in its first part, of fundamentals, and in its second part of applications, which are multiple in the world today.
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This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.
Database Management --- Data Mining and Knowledge Discovery --- Computing Milieux --- Machine Learning --- Computer Systems Organization and Communication Networks --- open access --- data mining --- learning systems --- classification --- clustering --- semantics --- learning algorithms --- supervised learning --- association rules --- social networks --- graphic methods --- neural networks --- artificial intelligence --- computer vision --- correlation analysis --- databases --- education --- engineering --- graph theory --- image analysis --- Databases --- Database programming --- Data mining --- Expert systems / knowledge-based systems --- Information technology: general issues --- Machine learning --- Computer networking & communications
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This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Database Management --- Information Systems Applications (incl. Internet) --- Logic in AI --- Computer Appl. in Administrative Data Processing --- Business Information Systems --- Computer and Information Systems Applications --- Computer Application in Administrative Data Processing --- artificial intelligence --- big data --- data analytics --- data handling --- data integration --- data mining --- databases --- digital storage --- domain knowledge --- graph theory --- information management --- information technology --- integrated data --- internet --- knowledge management --- knowledge-based system --- ontologies --- semantics --- Databases --- Database programming --- Information retrieval --- Internet searching --- Artificial intelligence --- Public administration --- Information technology: general issues --- Business mathematics & systems
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As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.
neural network --- Potts model --- latching --- recursion --- functional connectome --- graph theoretical analysis --- eigenvector centrality --- orderness --- network eigen-entropy --- information entropy production --- discrete Markov chains --- spike train statistics --- Gibbs measures --- maximum entropy principle --- pulse-gating --- channel capacity --- neural coding --- feedforward networks --- neural information propagation --- information theory --- mutual information decomposition --- synergy --- redundancy --- integrated information theory --- integrated information --- minimum information partition --- submodularity --- Queyranne’s algorithm --- consciousness --- maximum entropy --- higher-order correlations --- neural population coding --- Ising model --- brain network --- complex networks --- connectome --- information theory --- graph theory --- free-energy principle --- internal model hypothesis --- unconscious inference --- infomax principle --- independent component analysis --- principal component analysis --- goodness --- categorical perception --- perceptual magnet --- information theory --- perceived similarity --- mutual information --- synergy --- redundancy --- neural code --- hippocampus --- entorhinal cortex --- navigation --- neural code --- representation --- decoding --- spike-time precision --- discrimination --- noise correlations --- information theory --- mismatched decoding --- information theory --- neuroscience
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