Signal Processing for Neuroscientists Book

Signal Processing for Neuroscientists


  • Author : Wim van Drongelen
  • Publisher : Elsevier
  • Release Date : 2006-12-18
  • Genre: Science
  • Pages : 320
  • ISBN 10 : 008046775X

GET BOOK
Signal Processing for Neuroscientists Excerpt :

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Signal Processing for Neuroscientists Book

Signal Processing for Neuroscientists


  • Author : Wim van Drongelen
  • Publisher : Unknown
  • Release Date : 2007
  • Genre: Medical
  • Pages : 308
  • ISBN 10 : 0123708672

GET BOOK
Signal Processing for Neuroscientists Excerpt :

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. * Multiple color illustrations are integrated in the text * Includes an introduction to biomedical signals, noise characteristics, and recording techniques * Basics and background for more advanced topics can be found in extensive notes and appendices * A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Statistical Signal Processing for Neuroscience and Neurotechnology Book
Score: 5
From 1 Ratings

Statistical Signal Processing for Neuroscience and Neurotechnology


  • Author : Karim G. Oweiss
  • Publisher : Academic Press
  • Release Date : 2010-09-22
  • Genre: Science
  • Pages : 433
  • ISBN 10 : 0080962963

GET BOOK
Statistical Signal Processing for Neuroscience and Neurotechnology Excerpt :

This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems

Advances in Neural Signal Processing Book

Advances in Neural Signal Processing


  • Author : Ramana Vinjamuri
  • Publisher : BoD – Books on Demand
  • Release Date : 2020-09-09
  • Genre: Medical
  • Pages : 142
  • ISBN 10 : 9781789841138

GET BOOK
Advances in Neural Signal Processing Excerpt :

Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications.

Signal Processing in Neuroscience Book

Signal Processing in Neuroscience


  • Author : Xiaoli Li
  • Publisher : Springer
  • Release Date : 2016-08-31
  • Genre: Medical
  • Pages : 288
  • ISBN 10 : 9789811018220

GET BOOK
Signal Processing in Neuroscience Excerpt :

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjunction with existing computational tools to analyse neural activity, which is monitored through different sensors such as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date.

EEG Signal Processing and Feature Extraction Book
Score: 5
From 1 Ratings

EEG Signal Processing and Feature Extraction


  • Author : Li Hu
  • Publisher : Springer Nature
  • Release Date : 2019-10-12
  • Genre: Medical
  • Pages : 437
  • ISBN 10 : 9789811391132

GET BOOK
EEG Signal Processing and Feature Extraction Excerpt :

This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.

Principles of Neurobiological Signal Analysis Book

Principles of Neurobiological Signal Analysis


  • Author : Edmund Glaser
  • Publisher : Elsevier
  • Release Date : 2012-12-02
  • Genre: Science
  • Pages : 484
  • ISBN 10 : 9780323148627

GET BOOK
Principles of Neurobiological Signal Analysis Excerpt :

Principles of Neurobiological Signal Analysis deals with the principles of signal analysis as applied to the electrical activity of the nervous system. Topics covered include biological signals, the basics of signal processing, and power spectra and covariance functions. Evoked potentials, spontaneous and driven single unit activity, and multiunit activity are also considered, along with the relations between slow wave and unit activity. This book consists of eight chapters and begins by establishing the theoretical groundwork of signal analysis, with emphasis on the properties of signal and noise; sampling and conversion of biological signals into sequences of digital numbers readily digestible by a computer; and the concepts of power spectrum and covariance analysis. The following chapters explore techniques for extracting evoked responses from background noise; multivariate statistical procedures for treating evoked response waveshapes as variables dependent upon the experimental manipulations performed upon a subject; and spike (action potential) activity generated by neurons. The final chapter describes methods for studying how such spike activity may be related to the concurrently observed slow wave (EEG-like) activity of the nervous system. This monograph will be of interest to physiologists and neurobiologists.

Cooperative and Graph Signal Processing Book

Cooperative and Graph Signal Processing


  • Author : Petar Djuric
  • Publisher : Academic Press
  • Release Date : 2018-07-04
  • Genre: Computers
  • Pages : 866
  • ISBN 10 : 9780128136782

GET BOOK
Cooperative and Graph Signal Processing Excerpt :

Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book

MATLAB for Neuroscientists Book

MATLAB for Neuroscientists


  • Author : Pascal Wallisch
  • Publisher : Academic Press
  • Release Date : 2014-01-09
  • Genre: Computers
  • Pages : 570
  • ISBN 10 : 9780123838377

GET BOOK
MATLAB for Neuroscientists Excerpt :

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Analyzing Neural Time Series Data Book

Analyzing Neural Time Series Data


  • Author : Mike X Cohen
  • Publisher : MIT Press
  • Release Date : 2014-01-17
  • Genre: Psychology
  • Pages : 600
  • ISBN 10 : 9780262019873

GET BOOK
Analyzing Neural Time Series Data Excerpt :

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.

Dynamic Neuroscience Book

Dynamic Neuroscience


  • Author : Zhe Chen
  • Publisher : Springer
  • Release Date : 2017-12-27
  • Genre: Technology & Engineering
  • Pages : 327
  • ISBN 10 : 9783319719764

GET BOOK
Dynamic Neuroscience Excerpt :

This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.

Mathematics for Neuroscientists Book

Mathematics for Neuroscientists


  • Author : Fabrizio Gabbiani
  • Publisher : Academic Press
  • Release Date : 2017-03-21
  • Genre: Science
  • Pages : 628
  • ISBN 10 : 9780128019061

GET BOOK
Mathematics for Neuroscientists Excerpt :

Mathematics for Neuroscientists, Second Edition, presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons, neural networks and their relation to behavior. The book contains more than 200 figures generated using Matlab code available to the student and scholar. Mathematical concepts are introduced hand in hand with neuroscience, emphasizing the connection between experimental results and theory. Fully revised material and corrected text Additional chapters on extracellular potentials, motion detection and neurovascular coupling Revised selection of exercises with solutions More than 200 Matlab scripts reproducing the figures as well as a selection of equivalent Python scripts

Wavelets in Neuroscience Book

Wavelets in Neuroscience


  • Author : Alexander E. Hramov
  • Publisher : Springer Nature
  • Release Date : 2021-06-16
  • Genre: Science
  • Pages : 384
  • ISBN 10 : 9783030759926

GET BOOK
Wavelets in Neuroscience Excerpt :

This book illustrates how modern mathematical wavelet transform techniques offer fresh insights into the complex behavior of neural systems at different levels: from the microscopic dynamics of individual cells to the macroscopic behavior of large neural networks. It also demonstrates how and where wavelet-based mathematical tools can provide an advantage over classical approaches used in neuroscience. The authors well describe single neuron and populational neural recordings. This 2nd edition discusses novel areas and significant advances resulting from experimental techniques and computational approaches developed since 2015, and includes three new topics: • Detection of fEPSPs in multielectrode LFPs recordings. • Analysis of Visual Sensory Processing in the Brain and BCI for Human Attention Control; • Analysis and Real-time Classification of Motor-related EEG Patterns; The book is a valuable resource for neurophysiologists and physicists familiar with nonlinear dynamical systems and data processing, as well as for graduate students specializing in these and related areas.

Auditory Neuroscience Book

Auditory Neuroscience


  • Author : Jan Schnupp
  • Publisher : MIT Press
  • Release Date : 2012-08-17
  • Genre: Medical
  • Pages : 366
  • ISBN 10 : 9780262518024

GET BOOK
Auditory Neuroscience Excerpt :

An integrated overview of hearing and the interplay of physical, biological, and psychological processes underlying it. Every time we listen—to speech, to music, to footsteps approaching or retreating—our auditory perception is the result of a long chain of diverse and intricate processes that unfold within the source of the sound itself, in the air, in our ears, and, most of all, in our brains. Hearing is an "everyday miracle" that, despite its staggering complexity, seems effortless. This book offers an integrated account of hearing in terms of the neural processes that take place in different parts of the auditory system. Because hearing results from the interplay of so many physical, biological, and psychological processes, the book pulls together the different aspects of hearing—including acoustics, the mathematics of signal processing, the physiology of the ear and central auditory pathways, psychoacoustics, speech, and music—into a coherent whole.

Models of Information Processing in the Basal Ganglia Book

Models of Information Processing in the Basal Ganglia


  • Author : James C. Houk
  • Publisher : MIT Press
  • Release Date : 1995
  • Genre: Medical
  • Pages : 382
  • ISBN 10 : 0262082349

GET BOOK
Models of Information Processing in the Basal Ganglia Excerpt :

This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Recent years have seen a remarkable expansion of knowledge about the anatomical organization of the part of the brain known as the basal ganglia, the signal processing that occurs in these structures, and the many relations both to molecular mechanisms and to cognitive functions. This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Organized in four parts - fundamentals, motor functions and working memories, reward mechanisms, and cognitive and memory operations - the chapters present a unique admixture of theory, cognitive psychology, anatomy, and both cellular- and systems- level physiology written by experts in each of these areas. The editors have provided commentaries as a helpful guide to each part. Many new discoveries about the biology of the basal ganglia are summarized, and their impact on the computational role of the forebrain in the planning and control of complex motor behaviors discussed. The various findings point toward an unexpected role for the basal ganglia in the contextual analysis of the environment and in the adaptive use of this information for the planning and execution of intelligent behaviors. Parallels are explored between these findings and new connectionist approaches to difficult control problems in robotics and engineering. Contributors James L. Adams, P. Apicella, Michael Arbib, Dana H. Ballard, Andrew G. Barto, J. Brian Burns, Christopher I. Connolly, Peter F. Dominey, Richard P. Dum, John Gabrieli, M. Garcia-Munoz, Patricia S. Goldman-Rakic, Ann M. Graybiel, P. M. Groves, Mary M. Hayhoe, J. R. Hollerman, George Houghton, James C. Houk, Stephen Jackson, Minoru Kim