Case studies in neural data analysis: a guide for the practicing neuroscientist
Series: Computational NeurosciencePublication details: MIT Press, 2016. Cambridge:Description: xi, 370p : ill. : pb. ; 23cmISBN:- 9780262529372
- 616.80475 KRA
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
---|---|---|---|---|---|---|---|
Books | IIT Gandhinagar General Stacks | General | 616.80475 KRA (Browse shelf(Opens below)) | 1 | Available | 030598 |
Includes bibliography and index
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.
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