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Download the fantastic book titled Analyzing Neural Time Series Data written by Mike X Cohen, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Analyzing Neural Time Series Data", which was released on 17 January 2014. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Psychology genre.

Summary of 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.


Detail About Analyzing Neural Time Series Data PDF

  • Author : Mike X Cohen
  • Publisher : MIT Press
  • Genre : Psychology
  • Total Pages : 615 pages
  • ISBN : 0262019876
  • PDF File Size : 47,9 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Analyzing Neural Time Series Data

Analyzing Neural Time Series Data
  • Publisher : MIT Press
  • File Size : 48,6 Mb
  • Release Date : 17 January 2014
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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

Analyzing Neural Time Series Data

Analyzing Neural Time Series Data
  • Publisher : MIT Press
  • File Size : 26,7 Mb
  • Release Date : 17 January 2014
GET BOOK

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

Analysis of Neural Data

Analysis of Neural Data
  • Publisher : Springer
  • File Size : 50,5 Mb
  • Release Date : 08 July 2014
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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,

Case Studies in Neural Data Analysis

Case Studies in Neural Data Analysis
  • Publisher : MIT Press
  • File Size : 46,8 Mb
  • Release Date : 04 November 2016
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A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in

Neural Data Science

Neural Data Science
  • Publisher : Academic Press
  • File Size : 32,8 Mb
  • Release Date : 24 February 2017
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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

MATLAB for Brain and Cognitive Scientists

MATLAB for Brain and Cognitive Scientists
  • Publisher : MIT Press
  • File Size : 34,9 Mb
  • Release Date : 12 May 2017
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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. MATLAB is one of the most popular

Time Series Modeling of Neuroscience Data

Time Series Modeling of Neuroscience Data
  • Publisher : CRC Press
  • File Size : 32,9 Mb
  • Release Date : 26 January 2012
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Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze

Time Series

Time Series
  • Publisher : CRC Press
  • File Size : 22,8 Mb
  • Release Date : 17 May 2019
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The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data.

Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R
  • Publisher : Packt Publishing Ltd
  • File Size : 31,5 Mb
  • Release Date : 31 May 2019
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Build efficient forecasting models using traditional time series models and machine learning algorithms. Key FeaturesPerform time series analysis and forecasting using R packages such as Forecast and h2oDevelop models