Search Results for "matlab-for-neuroscientists"

MATLAB for Neuroscientists

MATLAB for Neuroscientists

An Introduction to Scientific Computing in MATLAB

  • Author: Pascal Wallisch,Michael E. Lusignan,Marc D. Benayoun,Tanya I. Baker,Adam Seth Dickey,Nicholas G. Hatsopoulos
  • Publisher: Academic Press
  • ISBN: 0123838371
  • Category: Computers
  • Page: 570
  • View: 4105
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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

MATLAB for Neuroscientists

An Introduction to Scientific Computing in MATLAB

  • Author: N.A
  • Publisher: Academic Press
  • ISBN: 9780123745514
  • Category: Computers
  • Page: 384
  • View: 1925
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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.

Statistical Techniques for Neuroscientists

Statistical Techniques for Neuroscientists

  • Author: Young K. Truong,Mechelle M. Lewis
  • Publisher: CRC Press
  • ISBN: 1315356759
  • Category: Mathematics
  • Page: 415
  • View: 883
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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.

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

  • Author: Thomas Trappenberg
  • Publisher: Oxford University Press
  • ISBN: 0199568413
  • Category: Mathematics
  • Page: 390
  • View: 636
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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.

Neural Data Science

Neural Data Science

A Primer with MATLAB® and PythonTM

  • Author: Erik Lee Nylen,Pascal Wallisch
  • Publisher: Academic Press
  • ISBN: 012804098X
  • Category: Science
  • Page: 368
  • View: 9003
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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

Signal Processing for Neuroscientists

Signal Processing for Neuroscientists

An Introduction to the Analysis of Physiological Signals

  • Author: Wim van Drongelen
  • Publisher: Elsevier
  • ISBN: 9780080467757
  • Category: Science
  • Page: 320
  • View: 7085
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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

Mathematics for Neuroscientists

Mathematics for Neuroscientists

  • Author: Fabrizio Gabbiani,Steven James Cox
  • Publisher: Academic Press
  • ISBN: 0128019069
  • Category: Science
  • Page: 628
  • View: 2398
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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

Web Application Obfuscation

Web Application Obfuscation

'-/WAFs..Evasion..Filters//alert(/Obfuscation/)-'

  • Author: Mario Heiderich,Eduardo Alberto Vela Nava,Gareth Heyes,David Lindsay
  • Publisher: Elsevier
  • ISBN: 1597496057
  • Category: Computers
  • Page: 296
  • View: 6936
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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

MATLAB for Brain and Cognitive Scientists

MATLAB for Brain and Cognitive Scientists

  • Author: Mike X Cohen
  • Publisher: MIT Press
  • ISBN: 0262035820
  • Category: Psychology
  • Page: 576
  • View: 9749
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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.