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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
- Sales Rank: #167225 in Books
- Published on: 2013-12-02
- Original language: English
- Number of items: 1
- Dimensions: 9.56" h x 1.19" w x 7.56" l, 2.99 pounds
- Binding: Hardcover
- 570 pages
Review
"...a handy resource for instructors of neuroscience, particularly those interested in more intense data analysis and/or neural modeling."
“The book is clear, cogent, and systematic. It provides much more than the essential nuts-and-bolts―it also leads the reader to learn to think about the empirical enterprise writ large…This book should be given a privileged spot on the bookshelf of every teacher, student, and researcher in the behavioral and cognitive sciences. ―Stephen M. Kosslyn, John Lindsley Professor of Psychology, Dean of Social Science, Harvard University, Cambridge, MA, USA
“This is an excellent book that should be on the desk of any neuroscientist or psychologist who wants to analyze and understand his or her own data by using MATLAB…Several books with MATLAB toolboxes exist; I find this one special both for its clarity and its focus on problems related to neuroscience and cognitive psychology. ―Nikos Logothetis, Director, Max Planck Institute for Biological Cybernetics, T�bingen, Germany
“MATLAB for Neuroscientists provides a unique and relatively comprehensive introduction to the MATLAB programming language in the context of brain sciences…The book would work well as a supplementary source for an introductory course in computational analysis and modeling in visual neuroscience, for graduate students or advanced undergraduates. ―Eero P. Simoncelli, Investigator, Howard Hughes Medical Institute; Professor, Neural Science, Mathematics, and Psychology, New York University, New York, USA
From the Back Cover
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.
About the Author
Pascal Wallisch received his PhD from the University of Chicago, did postdoctoral work at the Center for Neural Science at New York University, and currently serves as a clinical assistant professor of Psychology at New York University. His research interests are at the intersection of Psychology and Neuroscience, specifically Cognitive and Computational Neuroscience. His current work focuses on motion perception, autism and the appraisal of film.
Most helpful customer reviews
15 of 17 people found the following review helpful.
Excellent reference and learning tool
By Grapeape
The title sounds very authoritative, giving the impression that this is THE book for any neuroscientist who uses MATLAB. I was happy to discover that, this time, the text lives-up to the expectation. Okay, so I was not thrilled about the first edition. I found it a bit abstruse as an instructional tool and too limited for experienced MATLAB users. In this second edition the authors reach out in both directions, devoting the first 150 pages to introduction and tutorials and then broadening the scope of the sections on data collection, analysis, and simulation. The chapters are well organized, succinct, and cover an impressive range of topics, making it a valuable reference even for the experienced programmer, who may otherwise spend too much time picking-apart and reconstructing poorly-written methods sections from primary research articles. Of course the book is not comprehensive (it's a book, not a Wikipedia). Also, not every section takes-on the burden of holding the reader's hand in implementing a method from start to finish--although doing so may be a mistake, by providing recipes that are not always perfectly suited for the reader's problem. In general, the book makes an excellent laboratory resource, even more so because it can be purchased as a DRM-free ebook (I bought mine as a PDF, which has made it very easy to store and access alongside other methods-related materials on my hard drive).
1 of 1 people found the following review helpful.
Excellent reference and learning tool
By Grapeape
The title sounds very authoritative, giving the impression that this is THE book for any neuroscientist who uses MATLAB. I was happy to discover that, this time, the text lives-up to the expectation. Okay, so I was not thrilled about the first edition. I found it a bit abstruse as an instructional tool and too limited for experienced MATLAB users. In this second edition the authors reach out in both directions, devoting the first 150 pages to introduction and tutorials and then broadening the scope of the sections on data collection, analysis, and simulation. The chapters are well organized, succinct, and cover an impressive range of topics, making it a valuable reference even for the experienced programmer, who may otherwise spend too much time picking-apart and reconstructing poorly-written methods sections from primary research articles. Of course the book is not comprehensive (it's a book, not a Wikipedia). Also, not every section takes-on the burden of holding the reader's hand in implementing a method from start to finish--although doing so may be a mistake, by providing recipes that are not always perfectly suited for the reader's problem. In general, the book makes an excellent laboratory resource, even more so because it can be purchased as a DRM-free ebook (I bought mine as a PDF, which has made it very easy to store and access alongside other methods-related materials on my hard drive).
0 of 0 people found the following review helpful.
Great book but its software repository needs a good reorg.
By Miguel Camarena Sainz
Excelente review of basic techniques needed forma neuroscience research. The focus on doing exercises for each of the techniques makes the learning process more manageable.
However its software repository is ill-organized and you may need have to go through each chapter zip file in the book website to find the appropiate code. If the authors improve this, they can make this a more efficient learning experience.
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