Baker Tanya - MATLAB for Neuroscientists

The publication of the first edition of MATLAB for Neuroscientists was met with a reception that far exceeded our expectations, vindicating our intuition that there was an urgent need for such a text. Cynical voices often suggest that a new edition of a textbook is primarily designed to enrich the publisher. Not so in this case. While the first edition was widely adopted as a textbook as well as by individual students and investigators, several developments made it prudent to consider a second edition. First, neuroscience itself has changed, e.g., there is now an increased interest in the exploration of LFP signals. Second, MATLAB has evolved, e.g., through the introduction of parallel computing environments. Finally, and most importantly, we received copious feedback in response to the first edition. For example, there was an overwhelming consensus that the book would benefit from an increased number of basic tutorials in the front matter. Taken together, all of this suggested to us that it might be time for an update. Deciding to release a second edition afforded us the opportunity to address these issues, and also to improve upon the first version in other ways. For instance, we were now able to introduce full-color figures throughout the book, something which we think will improve its usability considerably, given that data visualization is one of MATLABs greatest strengths.

One thing that has not changed in the second edition is our philosophy of and focus on trying to foster behavioral change. Unless a book somehow leads to a change in behavior (that is, the way you go about doing things), it is very likely that you will forget what you read. We know; it happened to us countless times. Sometimes, the only thing one remembers about a book is that one read it, but nothing else. Thats not what this book is about. This book is about creating lasting behavioral change, specifically allowing you to use MATLAB more effectively, which in turn will (hopefully) make your research more productive. This requires more than just reading. It requires interaction with the content on a deep level. Thus, we tried to frame the content of this book to maximize the probability of meaningful engagement with the material.

The unbroken popularity of MATLAB among the neurosciences underscores the need for an accessible and up-to-date guide to its use. We hope that we succeeded in our intention to fulfill this need.

Many people helped us in our attempt to do so, and we thank them here. In addition to all the people we thanked in the first edition (on which this second edition is based), we also would like to thank April Graham, Mica Haley, Melissa Walker, and Greg Harris as well as Caroline Johnson and Melinda Rankin for their almost inexhaustible patience, kindness, and support; Donald McLaren for helping us with the neuroimaging chapter; and Qian Cheng for educational advice.

Finally, we alsoand in particularwould like to thank our students and colleagues for feedback on the first edition. In a sense, experts are the last people who should write a book like this. By their very experthood, they are often incapable of appreciating what would be helpful to someone who is not an expert and is just beginning to build cognitive structures in this domain. Therefore, feedback is absolutely crucial to give the experts information on how to make these materials more accessible to nonexperts. In a sense, writing a book like this teaches the authorsthrough feedbackhow to write a book like this. And thus, the circle is complete.

The authors