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An Introduction to Scientific Computing in Matlab
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By
Pascal Wallisch, New York University, NY, USA
Michael Lusignan, The University of Chicago, IL, USA
Marc Benayoun, The University of Chicago, IL, USA
Tanya Baker, The Salk Institute for Biological Studies, La Jolla, CA, USA
Adam Dickey, The University of Chicago, IL, USA
Nicho Hatsopoulos, The University of Chicago, IL, USA
Description
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. Two co-authors
(PW and NH) have presented their respective work on teaching Matlab at national meetings and two of the co-authors (PW and MB) were awarded
the coveted University of Chicago's Booth Prize for excellence in teaching these courses. (http://chronicle.uchicago.edu/070524/boothprize.shtml
).
Audience
Undergraduate and graduate students in systems, cognitive, and behavioral neuroscience, cognitive psychology, and related fields, as well as researchers in these fields who use Matlab.
Contents
Preface
Part I: Fundamentals
Introduction
Tutorial
Part II: Data Collection with Matlab
Visual Search and Pop Out
Attention
Psychophysics
Signal Detection Theory
Part III: Data Analysis with Matlab
Frequency Analysis Part I
Frequency Analysis Part II: Non-stationary Signals
and Spectrograms
Wavelets
Convolution
Introduction to Phase Plane Analysis
Exploring the Fitzhugh-Nagumo Model
Neural Data Analysis:
Encoding
Principal Components Analysis
Information Theory
Neural Decoding: Discrete variables
Neural Decoding: Continuous variables
Functional
Magnetic Imaging
Part IV: Data Modeling with Matlab
Voltage-Gated Ion Channels
Models of a Single Neuron
Models of the Retina
Simplified
Models of Spiking Neurons
Fitzhugh-Nagumo Model: Traveling Waves
Decision Theory
Markov Model
Modeling Spike Trains as a Poisson Process
Synaptic Transmission
Neural Networks: Unsupervised learning
Neural Network: Supervised Learning
Appendices
Appendix 1: Thinking in
Matlab
Appendix 2: Linear Algebra Review
| Bibliographic details |
Hardbound, 400 pages, publication date: OCT-2008
ISBN-13: 978-0-12-374551-4
Imprint: ACADEMIC PRESS
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EUR 56.95
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Last update: 25 Nov 2009
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