Directed Information Measures In Neuroscience
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Directed Information Measures In Neuroscience
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Author : Michael Wibral
language : en
Publisher: Springer
Release Date : 2014-03-20
Directed Information Measures In Neuroscience written by Michael Wibral and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-20 with Technology & Engineering categories.
Analysis of information transfer has found rapid adoption in neuroscience, where a highly dynamic transfer of information continuously runs on top of the brain's slowly-changing anatomical connectivity. Measuring such transfer is crucial to understanding how flexible information routing and processing give rise to higher cognitive function. Directed Information Measures in Neuroscience reviews recent developments of concepts and tools for measuring information transfer, their application to neurophysiological recordings and analysis of interactions. Written by the most active researchers in the field the book discusses the state of the art, future prospects and challenges on the way to an efficient assessment of neuronal information transfer. Highlights include the theoretical quantification and practical estimation of information transfer, description of transfer locally in space and time, multivariate directed measures, information decomposition among a set of stimulus/responses variables and the relation between interventional and observational causality. Applications to neural data sets and pointers to open source software highlight the usefulness of these measures in experimental neuroscience. With state-of-the-art mathematical developments, computational techniques and applications to real data sets, this book will be of benefit to all graduate students and researchers interested in detecting and understanding the information transfer between components of complex systems.
Information Theory In Neuroscience
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Author : Stefano Panzeri
language : en
Publisher: MDPI
Release Date : 2019-03-15
Information Theory In Neuroscience written by Stefano Panzeri and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Mathematics categories.
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.
Transfer Entropy
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Author : Deniz Gençağa
language : en
Publisher: MDPI
Release Date : 2018-08-24
Transfer Entropy written by Deniz Gençağa and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-24 with Mathematics categories.
This book is a printed edition of the Special Issue "Transfer Entropy" that was published in Entropy
An Introduction To Transfer Entropy
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Author : Terry Bossomaier
language : en
Publisher: Springer
Release Date : 2016-11-15
An Introduction To Transfer Entropy written by Terry Bossomaier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-15 with Computers categories.
This book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance. The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
Information Decomposition Of Target Effects From Multi Source Interactions
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Author : Joseph Lizier
language : en
Publisher: MDPI
Release Date : 2018-09-04
Information Decomposition Of Target Effects From Multi Source Interactions written by Joseph Lizier and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-04 with Mathematics categories.
This book is a printed edition of the Special Issue "Information Decomposition of Target Effects from Multi-Source Interactions" that was published in Entropy
Information Based Methods For Neuroimaging Analyzing Structure Function And Dynamics
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Author : Jesus M. Cortés
language : en
Publisher: Frontiers Media SA
Release Date : 2015-05-07
Information Based Methods For Neuroimaging Analyzing Structure Function And Dynamics written by Jesus M. Cortés and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-07 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.
The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion. Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables. In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology. Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications. This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.
From Matter To Life
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Author : Sara Imari Walker
language : en
Publisher: Cambridge University Press
Release Date : 2017-02-23
From Matter To Life written by Sara Imari Walker and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-23 with Philosophy categories.
This book tackles the most difficult and profound open questions about life and its origins from an information-based perspective.
Advances In Information Technology Research And Application 2012 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2012-12-26
Advances In Information Technology Research And Application 2012 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-26 with Computers categories.
Advances in Information Technology Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Information Technology. The editors have built Advances in Information Technology Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Information Technology in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Information Technology Research and Application / 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
New Insights On Basic And Clinical Aspects Of Eeg And Meg Connectome
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Author : Ryouhei Ishii
language : en
Publisher: Frontiers Media SA
Release Date : 2018-08-31
New Insights On Basic And Clinical Aspects Of Eeg And Meg Connectome written by Ryouhei Ishii and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with categories.
Recent advances in the neuroimaging field areas allow us to visualize the aggregate of neural connections at the macroscopic level within the brain, the so-called “connectome”. In order to promote the development of the neurophysiological investigation of connectome of brain oscillations, this eBook aims at bringing together contributions from researchers in basic and clinical neuroscience using EEG and MEG connectome analysis. The most important focal point will be to address the functional roles of connectome of brain oscillations in contributing to understandings of higher cognitive processes in normal subjects and pathophysiology of psychiatric diseases. This Research Topic presented novel methodologies and various applications of neurophysiological connectome analysis. As a result, these papers were cited more than 120 times in these four years in total and threw light and impact on new directions for investigating the connectome of human brain.
Exploratory Causal Analysis With Time Series Data
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Author : James M. McCracken
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Exploratory Causal Analysis With Time Series Data written by James M. McCracken and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments. Data analysis techniques are required for identifying causal information and relationships directly from such observational data. This need has led to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in time series data sets. Exploratory causal analysis (ECA) provides a framework for exploring potential causal structures in time series data sets and is characterized by a myopic goal to determine which data series from a given set of series might be seen as the primary driver. In this work, ECA is used on several synthetic and empirical data sets, and it is found that all of the tested time series causality tools agree with each other (and intuitive notions of causality) for many simple systems but can provide conflicting causal inferences for more complicated systems. It is proposed that such disagreements between different time series causality tools during ECA might provide deeper insight into the data than could be found otherwise.