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eBay item number:235477732113
Item specifics
- Condition
- ISBN
- 9780262529372
- Book Title
- Case Studies in Neural Data Analysis : a Guide for the Practicing Neuroscientist
- Book Series
- Computational Neuroscience Ser.
- Publisher
- MIT Press
- Item Length
- 9 in
- Publication Year
- 2016
- Format
- Trade Paperback
- Language
- English
- Illustrator
- Yes
- Item Height
- 0.7 in
- Genre
- Science, Psychology, Medical
- Topic
- Neurology, Neuroscience, Life Sciences / Neuroscience, Assessment, Testing & Measurement
- Item Weight
- 25.6 Oz
- Item Width
- 7.1 in
- Number of Pages
- 384 Pages
About this product
Product Identifiers
Publisher
MIT Press
ISBN-10
0262529378
ISBN-13
9780262529372
eBay Product ID (ePID)
221411076
Product Key Features
Book Title
Case Studies in Neural Data Analysis : a Guide for the Practicing Neuroscientist
Number of Pages
384 Pages
Language
English
Publication Year
2016
Topic
Neurology, Neuroscience, Life Sciences / Neuroscience, Assessment, Testing & Measurement
Illustrator
Yes
Genre
Science, Psychology, Medical
Book Series
Computational Neuroscience Ser.
Format
Trade Paperback
Dimensions
Item Height
0.7 in
Item Weight
25.6 Oz
Item Length
9 in
Item Width
7.1 in
Additional Product Features
Intended Audience
Trade
LCCN
2016-014656
Dewey Edition
23
Dewey Decimal
616.80475
Synopsis
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 computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference., 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 computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.
LC Classification Number
QP357.5.K69 2016
ebay_catalog_id
4
Copyright Date
2016
Item description from the seller
Seller assumes all responsibility for this listing.
eBay item number:235477732113
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Item location:
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