Methods in Brain Connectivity Inference through Multivariates Time Series Analysis
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Opis: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis

Interest in brain connectivity inference has become ubiquitous and is now increasingly adopted in experimental investigations of clinical, behavioral, and experimental neurosciences. Methods in Brain Connectivity Inference through Multivariate Time Series Analysis gathers the contributions of leading international authors who discuss different time series analysis approaches, providing a thorough survey of information on how brain areas effectively interact. Incorporating multidisciplinary work in applied mathematics, statistics, and animal and human experiments at the forefront of the field, the book addresses the use of time series data in brain connectivity interference studies. Contributors present codes and data examples to back up their methodological descriptions, exploring the details of each proposed method as well as an appreciation of their merits and limitations. Supplemental material for the book, including code, data, practical examples, and color figures is supplied in the form of a CD with directories organized by chapter and instruction files that provide additional detail. The field of brain connectivity inference is growing at a fast pace with new data/signal processing proposals emerging so often as to make it difficult to be fully up to date. This consolidated panorama of data-driven methods includes theoretical bases allied to computational tools, offering readers immediate hands-on experience in this dynamic arena.Brain Connectivity: An Overview, Luiz A. Baccala and Koichi Sameshima Directed Transfer Function: A Pioneering Concept in Connectivity Analysis, Maciej Kaminski and Katarzyna J. Blinowska An Overview of Vector Autoregressive Models, Pedro A. Morettin Partial Directed Coherence, Luiz A. Baccala and Koichi Sameshima Information Partial Directed Coherence, Daniel Y. Takahashi, Luiz A. Baccala and Koichi Sameshima Assessing Connectivity in the Presence of Instantaneous Causality, Luca Faes Asymptotic PDC Properties, Koichi Sameshima, Daniel Y. Takahashi and Luiz A. Baccala Nonlinear Parametric Granger Causality in Dynamical Networks, Daniele Marinazzo, Wei Liao, Mario Pellicoro and Sebastiano Stramaglia Time-Variant Estimation of Connectivity and Kalman Filter, Linda Sommerlade, Marco Thiel, Bettina Platt, Andrea Plano, Gernot Riedel, Celso Grebogi, Wolfgang Mader, Malenda Mader, Jens Timmer and Bjorn Schelter Connectivity Analysis Based on Multielectrode EEG Inversion Methods with and without fMRI a Priori Information, Laura Astolfi and Fabio Babiloni Methods for Connectivity Analysis in fMRI, Joao R. Sato, Philip A. Dean and Gilson Vieira Assessing Causal Interactions among Cardiovascular Variability Series through a Time-Domain Granger Causality Approach, Alberto Porta, Anielle C. M. Takahashi, Aparecida M. Catai and Nicola Montano Multivariate Time-Series Brain Connectivity: A Sum-Up, Luiz A. Baccala and Koichi Sameshima


Szczegóły: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis

Tytuł: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis
Producent: CRC Press Inc.
ISBN: 9781439845721
Rok produkcji: 2014
Ilość stron: 282
Oprawa: Twarda
Waga: 0.57 kg


Recenzje: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis
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Methods in Brain Connectivity Inference through Multivariates Time Series Analysis

Interest in brain connectivity inference has become ubiquitous and is now increasingly adopted in experimental investigations of clinical, behavioral, and experimental neurosciences. Methods in Brain Connectivity Inference through Multivariate Time Series Analysis gathers the contributions of leading international authors who discuss different time series analysis approaches, providing a thorough survey of information on how brain areas effectively interact. Incorporating multidisciplinary work in applied mathematics, statistics, and animal and human experiments at the forefront of the field, the book addresses the use of time series data in brain connectivity interference studies. Contributors present codes and data examples to back up their methodological descriptions, exploring the details of each proposed method as well as an appreciation of their merits and limitations. Supplemental material for the book, including code, data, practical examples, and color figures is supplied in the form of a CD with directories organized by chapter and instruction files that provide additional detail. The field of brain connectivity inference is growing at a fast pace with new data/signal processing proposals emerging so often as to make it difficult to be fully up to date. This consolidated panorama of data-driven methods includes theoretical bases allied to computational tools, offering readers immediate hands-on experience in this dynamic arena.Brain Connectivity: An Overview, Luiz A. Baccala and Koichi Sameshima Directed Transfer Function: A Pioneering Concept in Connectivity Analysis, Maciej Kaminski and Katarzyna J. Blinowska An Overview of Vector Autoregressive Models, Pedro A. Morettin Partial Directed Coherence, Luiz A. Baccala and Koichi Sameshima Information Partial Directed Coherence, Daniel Y. Takahashi, Luiz A. Baccala and Koichi Sameshima Assessing Connectivity in the Presence of Instantaneous Causality, Luca Faes Asymptotic PDC Properties, Koichi Sameshima, Daniel Y. Takahashi and Luiz A. Baccala Nonlinear Parametric Granger Causality in Dynamical Networks, Daniele Marinazzo, Wei Liao, Mario Pellicoro and Sebastiano Stramaglia Time-Variant Estimation of Connectivity and Kalman Filter, Linda Sommerlade, Marco Thiel, Bettina Platt, Andrea Plano, Gernot Riedel, Celso Grebogi, Wolfgang Mader, Malenda Mader, Jens Timmer and Bjorn Schelter Connectivity Analysis Based on Multielectrode EEG Inversion Methods with and without fMRI a Priori Information, Laura Astolfi and Fabio Babiloni Methods for Connectivity Analysis in fMRI, Joao R. Sato, Philip A. Dean and Gilson Vieira Assessing Causal Interactions among Cardiovascular Variability Series through a Time-Domain Granger Causality Approach, Alberto Porta, Anielle C. M. Takahashi, Aparecida M. Catai and Nicola Montano Multivariate Time-Series Brain Connectivity: A Sum-Up, Luiz A. Baccala and Koichi Sameshima

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Cena 534,04 PLN
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Oszczędzasz 6%
Wysyłka: Niedostępna
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Szczegóły: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis

Tytuł: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis
Producent: CRC Press Inc.
ISBN: 9781439845721
Rok produkcji: 2014
Ilość stron: 282
Oprawa: Twarda
Waga: 0.57 kg


Recenzje: Methods in Brain Connectivity Inference through Multivariates Time Series Analysis

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