Matlab For Neuroscientists

Autore: Pascal Wallisch
Editore: Academic Press
ISBN: 0123838371
Grandezza: 53,33 MB
Formato: PDF, Kindle
Vista: 1315
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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

Matlab For Neuroscientists

Autore:
Editore: Academic Press
ISBN: 9780123745514
Grandezza: 53,47 MB
Formato: PDF, ePub, Mobi
Vista: 3357
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Matlab is the accepted standard for scientific computing, used globally in virtually all Neuroscience and Cognitive Psychology laboratories. For instance, SPM, the most used software for the analysis and manipulation of fMRI images in research and clinical practice is fully programmed in matlab, and its use of the possibility to allow for sophisticated software modules to be freely added to the software has established it as the by far dominant software in the field. Many universities now offer, or are beginning to offer matlab introductory courses in their neuroscience and psychology programs. Nevertheless, so far there hasn't been a textbook specific to this market, and the use of the plethora of existing engineering focused Matlab textbooks is notoriously difficult for teaching the package in those environments. This is the first comprehensive teaching resource and textbook for the teaching of Matlab in the Neurosciences and in Psychology. Matlab is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes". Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some rare cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research. The ability to effectively use computers in research is necessary in an academic environment that is increasingly focused on quantitative issues. Matlab represents an ideal language of scientific computing. It is based on powerful linear algebra structures which lend themselves to empirical problems on the one hand, while at the same time allowing the student to make rapid problem-oriented progress (particularly in terms of visualization of data points) without having to lose focus by worrying too much about memory allocation and other "plumbing" minutiae as would be required in other, more low-level programming languages such as C or C++. Currently, there are several books that provide introductions to Matlab that are either too generic and fundamental or too irrelevant for neuroscientists and cognitive psychologists who typically face a very circumscribed range of problems in data collection, data analysis and signal processing. Some non-book tutorials and primers that are in use in the community are typically out of date. Matlab versions are usually not backwards compatible. Many commands and functions used in older tutorials and primers, such as "flops" won't work in current versions of Matlab, necessitating a book that is timely and up-to-date. The complete lack of a relevant resource in this area, combined with a clearly felt need for such a text provided the primary and initial impetus for this project. The authors provide such a dearly needed resource adapting and pooling materials that developed for and used in highly rated courses involving the use of Matlab in Neuroscience at the University of Chicago.

Matlab For Neuroscientists 2nd Edition

Autore: Pascal Wallisch
Editore:
ISBN:
Grandezza: 22,15 MB
Formato: PDF, Mobi
Vista: 6294
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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.

Neural Data Science

Autore: Erik Lee Nylen
Editore: Academic Press
ISBN: 012804098X
Grandezza: 40,58 MB
Formato: PDF, ePub
Vista: 7436
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A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner’s introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. Includes discussions of both MATLAB and Python in parallel Introduces the canonical data analysis cascade, standardizing the data analysis flow Presents tactics that strategically, tactically, and algorithmically help improve the organization of code

Statistical Techniques For Neuroscientists

Autore: Young K. Truong
Editore: CRC Press
ISBN: 1315356759
Grandezza: 46,62 MB
Formato: PDF, ePub, Docs
Vista: 7642
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Statistical Techniques for Neuroscientists introduces new and useful methods for data analysis involving simultaneous recording of neuron or large cluster (brain region) neuron activity. The statistical estimation and tests of hypotheses are based on the likelihood principle derived from stationary point processes and time series. Algorithms and software development are given in each chapter to reproduce the computer simulated results described therein. The book examines current statistical methods for solving emerging problems in neuroscience. These methods have been applied to data involving multichannel neural spike train, spike sorting, blind source separation, functional and effective neural connectivity, spatiotemporal modeling, and multimodal neuroimaging techniques. The author provides an overview of various methods being applied to specific research areas of neuroscience, emphasizing statistical principles and their software. The book includes examples and experimental data so that readers can understand the principles and master the methods. The first part of the book deals with the traditional multivariate time series analysis applied to the context of multichannel spike trains and fMRI using respectively the probability structures or likelihood associated with time-to-fire and discrete Fourier transforms (DFT) of point processes. The second part introduces a relatively new form of statistical spatiotemporal modeling for fMRI and EEG data analysis. In addition to neural scientists and statisticians, anyone wishing to employ intense computing methods to extract important features and information directly from data rather than relying heavily on models built on leading cases such as linear regression or Gaussian processes will find this book extremely helpful.

Matlab For Brain And Cognitive Scientists

Autore: Mike X Cohen
Editore: MIT Press
ISBN: 0262035820
Grandezza: 66,83 MB
Formato: PDF, ePub
Vista: 6696
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An introduction to a popular programming language for neuroscience research, taking the reader from beginning to intermediate and advanced levels of MATLAB programming.

Mathematics For Neuroscientists

Autore: Fabrizio Gabbiani
Editore: Academic Press
ISBN: 0128019069
Grandezza: 77,88 MB
Formato: PDF, Kindle
Vista: 5632
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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

Fundamentals Of Computational Neuroscience

Autore: Thomas Trappenberg
Editore: Oxford University Press
ISBN: 0199568413
Grandezza: 18,77 MB
Formato: PDF, ePub
Vista: 8832
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The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental networkarchitectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can begained with such studies.

Signal Processing For Neuroscientists

Autore: Wim van Drongelen
Editore: Academic Press
ISBN: 012810483X
Grandezza: 66,26 MB
Formato: PDF, ePub, Mobi
Vista: 7441
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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

Python In Neuroscience

Autore: Eilif Muller
Editore: Frontiers Media SA
ISBN: 2889196089
Grandezza: 12,53 MB
Formato: PDF, ePub, Docs
Vista: 9631
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Python is rapidly becoming the de facto standard language for systems integration. Python has a large user and developer-base external to theneuroscience community, and a vast module library that facilitates rapid and maintainable development of complex and intricate systems. In this Research Topic, we highlight recent efforts to develop Python modules for the domain of neuroscience software and neuroinformatics: - simulators and simulator interfaces - data collection and analysis - sharing, re-use, storage and databasing of models and data - stimulus generation - parameter search and optimization - visualization - VLSI hardware interfacing. Moreover, we seek to provide a representative overview of existing mature Python modules for neuroscience and neuroinformatics, to demonstrate a critical mass and show that Python is an appropriate choice of interpreter interface for future neuroscience software development.

Signal Processing For Neuroscientists

Autore: Wim van Drongelen
Editore:
ISBN: 9780123708670
Grandezza: 61,90 MB
Formato: PDF, Docs
Vista: 7007
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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

Programming Behavioral Experiments With Matlab And Psychtoolbox

Autore: Erman Misirlisoy
Editore: Taylor & Francis
ISBN: 1317205634
Grandezza: 58,31 MB
Formato: PDF, ePub
Vista: 4511
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Human behavior is fascinating so it’s no surprise that psychologists and neuroscientists spend their lives designing rigorous experiments to understand it. MATLAB is one of the most widely used pieces of software for designing and running behavioral experiments, and it opens up a world of quick and flexible experiment programming. This book offers a step-by-step guide to using MATLAB with Psychtoolbox to create customisable experiments. Its pocket size and simple language allow you to get straight to the point and help you to learn fast in order to complete your work in great time. In nine simple steps, it guides you all the way from setting parameters for your experiment to analysing the output. Gone are the daunting days of working through hundreds of irrelevant and complicated documents, as in this handy book, Erman Misirlisoy coaxes you in the right direction with his friendly and encouraging tricks and tips. If you want to learn how to develop your own experiments to collect and analyse behavioral data, then this book is a must-read. Whether you are a student in experimental psychology, a researcher in cognitive neuroscience, or simply someone who wants to run behavioral tasks on your friends for fun, this book will offer you the skills to succeed.

Web Application Obfuscation

Autore: Mario Heiderich
Editore: Elsevier
ISBN: 1597496057
Grandezza: 39,83 MB
Formato: PDF, Mobi
Vista: 365
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Web applications are used every day by millions of users, which is why they are one of the most popular vectors for attackers. Obfuscation of code has allowed hackers to take one attack and create hundreds-if not millions-of variants that can evade your security measures. Web Application Obfuscation takes a look at common Web infrastructure and security controls from an attacker's perspective, allowing the reader to understand the shortcomings of their security systems. Find out how an attacker would bypass different types of security controls, how these very security controls introduce new types of vulnerabilities, and how to avoid common pitfalls in order to strengthen your defenses. Named a 2011 Best Hacking and Pen Testing Book by InfoSec Reviews Looks at security tools like IDS/IPS that are often the only defense in protecting sensitive data and assets Evaluates Web application vulnerabilties from the attacker's perspective and explains how these very systems introduce new types of vulnerabilities Teaches how to secure your data, including info on browser quirks, new attacks and syntax tricks to add to your defenses against XSS, SQL injection, and more

Case Studies In Neural Data Analysis

Autore: Mark A. Kramer
Editore: MIT Press
ISBN: 0262529378
Grandezza: 46,64 MB
Formato: PDF, ePub
Vista: 2097
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A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data.

Tissue Engineering Made Easy

Autore: Farhana Akter
Editore: Academic Press
ISBN: 0128092289
Grandezza: 76,91 MB
Formato: PDF
Vista: 9971
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Tissue Engineering Made Easy provides concise, easy to understand, up-to-date information about the most important topics in tissue engineering. These include background and basic principles, clinical applications for a variety of organs (skin, nerves, eye, heart, lungs and bones), and the future of the field. The descriptions and explanations of each topic are such that those who have not had any exposure to the principles and practice of tissue engineering will be able to understand them, and the volume will serve as a source for self-teaching to get readers to a point where they can effectively engage with active researchers. Offers readers a truly introductory way to understand the concepts, challenges and the new trends in reconstructive medicine Features accessible language for students beginning their research careers, private practice physician collaborators, and residents just beginning their research rotation Addresses the specifics for a variety of organs/systems – nerves, skin, bone, cardiovascular, respiratory, ophthalmic Provides examples from clinical and everyday situations

Neuroscience

Autore: Alwyn Scott
Editore: Springer Science & Business Media
ISBN: 9780387954028
Grandezza: 44,23 MB
Formato: PDF, Mobi
Vista: 1601
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This book will be of interest to anyone who wishes to know what role mathematics can play in attempting to comprehend the dynamics of the human brain. It also aims to serve as a general introduction to neuromathematics. The book gives the reader a qualitative understanding and working knowledge of useful mathematical applications to the field of neuroscience. The book is readable by those who have little knowledge of mathematics for neuroscience but are committed to begin acquiring such knowledge.

Advanced Data Analysis In Neuroscience

Autore: Daniel Durstewitz
Editore: Springer
ISBN: 3319599763
Grandezza: 26,34 MB
Formato: PDF, Mobi
Vista: 1610
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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 explanat ory 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

Neural Engineering

Autore: Chris Eliasmith
Editore: MIT Press
ISBN: 9780262550604
Grandezza: 34,18 MB
Formato: PDF
Vista: 8183
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A synthesis of current approaches to adapting engineering tools to the study of neurobiological systems.

The Development And Improvement Of Speech Therapy Tools Using Matlab Environment

Autore: Eman Abbas Alkafawi
Editore:
ISBN:
Grandezza: 39,29 MB
Formato: PDF, Docs
Vista: 8373
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Analyzing Neural Time Series Data

Autore: Mike X Cohen
Editore: MIT Press
ISBN: 026231956X
Grandezza: 54,42 MB
Formato: PDF, Kindle
Vista: 4686
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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.