Advanced Data Analysis In Neuroscience

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Advanced Data Analysis in Neuroscience

Author : Daniel Durstewitz
Publisher : Springer
Page : 292 pages
File Size : 48,7 Mb
Release : 2017-09-15
Category : Medical
ISBN : 9783319599762

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Advanced Data Analysis in Neuroscience by Daniel Durstewitz Pdf

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck

Multivariate Statistical Analysis in Neuroscience

Author : Giovanni Cugliari,Marco Ivaldi
Publisher : GRIN Verlag
Page : 185 pages
File Size : 44,6 Mb
Release : 2015-06-08
Category : Medical
ISBN : 9783656973751

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Multivariate Statistical Analysis in Neuroscience by Giovanni Cugliari,Marco Ivaldi Pdf

Research Paper (postgraduate) from the year 2015 in the subject Medicine - Other, grade: II Level Master, University of Pavia (Unit of Medical and Genomic Statistics), course: Medical and Genomic Statistics, language: English, abstract: Electroencephalography, commonly called 'EEG', estimates through the application of electrodes, the electrical activity of the brain (which is the sum of the electrical activity of each neuron). In recent years, with the goal of making more reliable the EEG, many researchers have turned their interest in the development of tools, methods and software. This thesis describes some best procedures for the experimental design, data visualization and descriptive or inferential statistical analysis. The application of statistical models to single or multiple subjects study-design are also described, including parametric and non-parametric approaches. Methods for processing multivariate data (PCA, ICA, clustering) were described. Re-sampling methods (bootstrap) using many randomly software-generated samples were also described. The aim of this work is to provide, with statistical concepts and examples, information on the qualitative and quantitative approaches related to the electroencephalographic signals. The work consists into three parts: INTRODUTION TO ELECTROENCEPHALOGRAPHY (GENERAL CHARACTERISTICS); DATA MINING AND STATISTICAL ANALYSIS; EXPERIMENTAL STUDY DESIGNS. The six works included in the section called “EXPERIMENTAL STUDY DESIGNS” analyze EEG alterations in the protocols: Electrocortical activity in dancers and non-dancers listening to different music genre and during imaginative dance motor activity; Electrocortical activity during monosynaptic reflex in athletes; Monitoring of electrocortical activity for evaluation of seasickness; Electrocortical activity in different body positions; Electrocortical activity in athletes and non-athletes during body balance tasks; Electrocortical responses in volunteers with and without specific experience watching movies including the execution of complex motor gestures. In the section called “OTHER INTERESTING THINGS” were included one work that analyze EMG (electromyography) alterations in pathological and healthy subjects in the protocol: Comparison between clinical diagnostic criteria of sleep bruxism and those provided by a validated portable holter. The described procedures can be used for clinical trials, although the studies proposed in this work do not refer to samples from pathological subjects. With its multi-specialist approach, through many theoretical and practical feedback, this work will be useful for specializing in neuroscience, statistics, engineering or physiology.

Analyzing Neural Time Series Data

Author : Mike X Cohen
Publisher : MIT Press
Page : 615 pages
File Size : 55,9 Mb
Release : 2014-01-17
Category : Psychology
ISBN : 9780262019873

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Analyzing Neural Time Series Data by Mike X Cohen Pdf

A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.

Towards Advanced Data Analysis by Combining Soft Computing and Statistics

Author : Christian Borgelt,María Ángeles Gil,João M.C. Sousa,Michel Verleysen
Publisher : Springer
Page : 378 pages
File Size : 55,9 Mb
Release : 2012-08-29
Category : Technology & Engineering
ISBN : 9783642302787

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Towards Advanced Data Analysis by Combining Soft Computing and Statistics by Christian Borgelt,María Ángeles Gil,João M.C. Sousa,Michel Verleysen Pdf

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.

The Statistical Physics of Data Assimilation and Machine Learning

Author : Henry D. I. Abarbanel
Publisher : Cambridge University Press
Page : 207 pages
File Size : 55,5 Mb
Release : 2022-02-17
Category : Computers
ISBN : 9781316519639

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The Statistical Physics of Data Assimilation and Machine Learning by Henry D. I. Abarbanel Pdf

The theory of data assimilation and machine learning is introduced in an accessible manner for undergraduate and graduate students.

Advanced State Space Methods for Neural and Clinical Data

Author : Zhe Chen
Publisher : Cambridge University Press
Page : 397 pages
File Size : 42,9 Mb
Release : 2015-10-15
Category : Computers
ISBN : 9781107079199

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Advanced State Space Methods for Neural and Clinical Data by Zhe Chen Pdf

An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.

Analysis of Neural Data

Author : Robert E. Kass,Uri T. Eden,Emery N. Brown
Publisher : Springer
Page : 663 pages
File Size : 47,7 Mb
Release : 2014-07-08
Category : Medical
ISBN : 9781461496021

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Analysis of Neural Data by Robert E. Kass,Uri T. Eden,Emery N. Brown Pdf

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Handbook of Neuroimaging Data Analysis

Author : Hernando Ombao,Martin Lindquist,Wesley Thompson,John Aston
Publisher : CRC Press
Page : 702 pages
File Size : 49,6 Mb
Release : 2016-11-18
Category : Mathematics
ISBN : 9781482220988

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Handbook of Neuroimaging Data Analysis by Hernando Ombao,Martin Lindquist,Wesley Thompson,John Aston Pdf

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

Advanced Deep Learning Applications in Big Data Analytics

Author : Bouarara, Hadj Ahmed
Publisher : IGI Global
Page : 351 pages
File Size : 41,7 Mb
Release : 2020-10-16
Category : Computers
ISBN : 9781799827931

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Advanced Deep Learning Applications in Big Data Analytics by Bouarara, Hadj Ahmed Pdf

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Knowledge Modelling and Big Data Analytics in Healthcare

Author : Mayuri Mehta,Kalpdrum Passi,Indranath Chatterjee,Rajan Patel
Publisher : CRC Press
Page : 362 pages
File Size : 53,9 Mb
Release : 2021-12-09
Category : Computers
ISBN : 9781000477764

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Knowledge Modelling and Big Data Analytics in Healthcare by Mayuri Mehta,Kalpdrum Passi,Indranath Chatterjee,Rajan Patel Pdf

Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals. The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery. This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.

Advances in Computational Neuroscience

Author : Thomas Nowotny,Sacha Jennifer van Albada,Tatyana Sharpee,Jean-Marc Fellous,Renaud Blaise Jolivet,Julie S. Haas,Christoph Metzner
Publisher : Frontiers Media SA
Page : 253 pages
File Size : 42,9 Mb
Release : 2022-02-23
Category : Science
ISBN : 9782889745012

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Advances in Computational Neuroscience by Thomas Nowotny,Sacha Jennifer van Albada,Tatyana Sharpee,Jean-Marc Fellous,Renaud Blaise Jolivet,Julie S. Haas,Christoph Metzner Pdf

Advanced Imaging Methods in Neuroscience

Author : João O. Malva,Jorge Valero,Miguel Castelo-Branco,Alard Roebroeck
Publisher : Frontiers Media SA
Page : 498 pages
File Size : 47,5 Mb
Release : 2022-01-11
Category : Science
ISBN : 9782889717255

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Advanced Imaging Methods in Neuroscience by João O. Malva,Jorge Valero,Miguel Castelo-Branco,Alard Roebroeck Pdf

Advances in Cognitive Neurodynamics

Author : Rubin Wang,Fanji Gu,Enhua Shen
Publisher : Springer Science & Business Media
Page : 991 pages
File Size : 41,7 Mb
Release : 2008-09-15
Category : Medical
ISBN : 9781402083877

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Advances in Cognitive Neurodynamics by Rubin Wang,Fanji Gu,Enhua Shen Pdf

Fifty years ago, enthused by successes in creating digital computers and the DNA model of heredity, scientists were con?dent that solutions to the problems of und- standing biological intelligence and creating machine intelligence were within their grasp. Progress at ?rst seemed rapid. Giant ‘brains’ that ?lled air-conditioned rooms were shrunk into briefcases. The speed of computation doubled every two years. What these advances revealed is not the solutions but the dif?culties of the pr- lems. We are like the geographers who ‘discovered’ America, not as a collection of islands but as continents seen only at shores and demanding exploration. We are astounded less by the magnitude of our discoveries about how brains cogitate than by the enormity of the tasks we have undertaken, to explain and replicate the higher functions of brains. Five decades of brain research have led to the emergence of a new ?eld, which spans the entire range of brain cognition from quantum ?elds to social interactions, and which is combined by the conceptions of nonlinear neurodynamics operating simultaneously at and across all levels. A new breed of scientists has emerged, schooled in multiple academic disciplines, comfortable in working with data from different levels, and conversant with the mathematical tools that are essential to cross boundaries.

Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing

Author : Yizhang Jiang,Yu-Dong Zhang,Mohammad Khosravi
Publisher : Frontiers Media SA
Page : 239 pages
File Size : 51,6 Mb
Release : 2021-10-13
Category : Science
ISBN : 9782889714681

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Advanced Deep-Transfer-Leveraged Studies on Brain-Computer Interfacing by Yizhang Jiang,Yu-Dong Zhang,Mohammad Khosravi Pdf