Signal Processing for Neuroscientists

Author: Wim van Drongelen
Publisher: Elsevier
ISBN: 9780080467757
Format: PDF, Kindle
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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

Author: Wim van Drongelen
Publisher: Academic Press
ISBN: 9780128104828
Format: PDF
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Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling. Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises Contains the basics and background for more advanced topics in extensive notes and appendices Includes practical examples of algorithm development and implementation in MATLAB Features a companion website with MATLAB scripts, data files, figures and video lectures

Signal Processing for Neuroscientists

Author: Wim van Drongelen
Publisher: Academic Press
ISBN: 012810483X
Format: PDF, Kindle
Download and Read
Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling. Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises Contains the basics and background for more advanced topics in extensive notes and appendices Includes practical examples of algorithm development and implementation in MATLAB Features a companion website with MATLAB scripts, data files, figures and video lectures

Signal Processing for Neuroscientists An Introduction to the Analysis of Physiological Signals

Author: Wim Van Drongelen
Publisher: Academic Press
ISBN: 9781493300891
Format: PDF, Docs
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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(r). * 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

Author: Karim G. Oweiss
Publisher: Academic Press
ISBN: 9780080962962
Format: PDF, Docs
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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

MATLAB for Neuroscientists

Author: Pascal Wallisch
Publisher: Academic Press
ISBN: 0123838371
Format: PDF, Docs
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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

Signal Processing for Neuroscientists A Companion Volume

Author: Wim van Drongelen
Publisher: Elsevier
ISBN: 0123849160
Format: PDF, ePub
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The popularity of signal processing in neuroscience is increasing, and with the current availability and development of computer hardware and software, it is anticipated that the current growth will continue. Because electrode fabrication has improved and measurement equipment is getting less expensive, electrophysiological measurements with large numbers of channels are now very common. In addition, neuroscience has entered the age of light, and fluorescence measurements are fully integrated into the researcher’s toolkit. Because each image in a movie contains multiple pixels, these measurements are multi-channel by nature. Furthermore, the availability of both generic and specialized software packages for data analysis has altered the neuroscientist’s attitude toward some of the more complex analysis techniques. This book is a companion to the previously published Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals, which introduced readers to the basic concepts. It discusses several advanced techniques, rediscovers methods to describe nonlinear systems, and examines the analysis of multi-channel recordings. Covers the more advanced topics of linear and nonlinear systems analysis and multi-channel analysis Includes practical examples implemented in MATLAB Provides multiple references to the basics to help the student

Bioelectrical Signal Processing in Cardiac and Neurological Applications

Author: Leif Sörnmo
Publisher: Academic Press
ISBN: 0124375529
Format: PDF, Mobi
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The analysis of bioelectrical signals continues to receive wide attention in research as well as commercially because novel signal processing techniques have helped to uncover valuable information for improved diagnosis and therapy. This book takes a unique problem-driven approach to biomedical signal processing by considering a wide range of problems in cardiac and neurological applications-the two "heavyweight" areas of biomedical signal processing. The interdisciplinary nature of the topic is reflected in how the text interweaves physiological issues with related methodological considerations. Bioelectrical Signal Processing is suitable for a final year undergraduate or graduate course as well as for use as an authoritative reference for practicing engineers, physicians, and researchers. Solutions Manual available online at http://www.textbooks.elsevier.com · A problem-driven, interdisciplinary presentation of biomedical signal processing · Focus on methods for processing of bioelectrical signals (ECG, EEG, evoked potentials, EMG) · Covers both classical and recent signal processing techniques · Emphasis on model-based statistical signal processing · Comprehensive exercises and illustrations · Extensive bibliography · For companion web site with project descriptions and signals for download see www.biosignal.lth.se

Fundamental Neuroscience

Author: Larry R. Squire
Publisher: Academic Press
ISBN: 0123858704
Format: PDF, ePub, Mobi
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Fundamental Neuroscience, 3rd Edition introduces graduate and upper-level undergraduate students to the full range of contemporary neuroscience. Addressing instructor and student feedback on the previous edition, all of the chapters are rewritten to make this book more concise and student-friendly than ever before. Each chapter is once again heavily illustrated and provides clinical boxes describing experiments, disorders, and methodological approaches and concepts. A companion web site contains test questions, and an imagebank of the figures for ready use in presentations, slides, and handouts. Capturing the promise and excitement of this fast-moving field, Fundamental Neuroscience, 3rd Edition is the text that students will be able to reference throughout their neuroscience careers! New to this edition: * 30% new material including new chapters on Dendritic Development and Spine Morphogenesis, Chemical Senses, Cerebellum, Eye Movements, Circadian Timing, Sleep and Dreaming, and Consciousness * Companion website with figures, web links to additional material, and test questions * Additional text boxes describing key experiments, disorders, methods, and concepts * Multiple model system coverage beyond rats, mice, and monkeys * Extensively expanded index for easier referencing

Observed Brain Dynamics

Author: Partha Mitra
Publisher: Oxford University Press
ISBN: 0198039638
Format: PDF, ePub
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The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. Written by investigators who have played an important role in developing the subject and in its pedagogical exposition, the current volume addresses the need for a textbook in this interdisciplinary area. The book is written for a broad spectrum of readers ranging from physical scientists, mathematicians, and statisticians wishing to educate themselves about neuroscience, to biologists who would like to learn time series analysis methods in particular and refresh their mathematical and statistical knowledge in general, through self-pedagogy. It may also be used as a supplement for a quantitative course in neurobiology or as a textbook for instruction on neural signal processing. The first part of the book contains a set of essays meant to provide conceptual background which are not technical and shall be generally accessible. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above (also available as part of the Chronux data analysis platform from http://chronux.org), and the fourth part contains special topics.