(Spring 2017)


For undergraduates in NSC3270, introductory Neuroscience (NSC2201) or an equivalent course is a prerequisite for enrolling in this course. For graduate students in NSC5270, some knowledge of neuroscience is assumed.

Because most computational models and computational approaches are described in the language of mathematics, and because many of the models we describe are dynamic, involving changes in activity over time, we will assume that students have a basic understanding of calculus, especially the fundamental concepts of the derivative and the integral. For undergraduates, at least one semester of calculus is required. For graduate students without this prerequisite knowledge of elementary calculus, gaps will need to be filled with outside readings.

Some knowledge of computer programming in a high-level language (e.g., Matlab, Python, R, C++, Javascript) is required. We will be using Matlab for demonstrations and homework assignments. We will not assume that everyone knows Matlab. For students who do not know Matlab, we will cover basic elements of the language in class; for students who do know Matlab, this will be a (hopefully) useful review. For undergraduates, at least one semester of computer programming is required, not necessarily in Matlab. For graduate students, prior classwork or other experience using some computer programming language will be assumed.


Students are encouraged to bring laptops to class. We may distribute example code before class that will be used during class. We must insist that everyone please refrain from using their laptops for any non-class purposes during class, as it can be very distracting to others.

Course Requirements and Grading

Homework assignments will be handed out regularly – at least weekly – throughout the course to allow students the opportunity to put the ideas discussed during class into practice. Homework assignments are the primary determinant of the course grade. There will be no graded quizzes or exams. Poor attendance and participation can be used to lower the final grade.

While we encourage students to help each other out with conceptual misunderstandings, all homework assignments must be completed individually. Unexcused late assignments will be penalized 10% for every 24 hours late, starting from the time class ends, for a maximum of two days, after which they will earn a 0.

Any student auditing the course is expected to attend class and can participate in a way commensurate with the amount of work they do on class homework assignments.

Graduate students are required to enroll in NSC5270. In addition to completing the homework assignments and attending class, graduate students are required to complete a small final project in Matlab that relates somehow to the principles and approaches discussed in class. Graduate students will meet with one of the professors to discuss potential projects and get our okay to proceed. The final submitted project will consist of Matlab code that can be run and a short description of what the code is used for. The final project can be closely related to your graduate research but it does not need to be. The final project will constitute 10% of your final course grade.


There is no book for this course. Instead, course readings (book chapters, articles, links to web sites) will be posted for download on Blackboard and will be announced in class.


We will use Matlab in this course. Vanderbilt has a site license that users contribute to by purchasing individual licenses; we anticipate that some graduate students will have access to Matlab through a license purchased for them by their research advisor. Students without laboratory access can buy a Matlab license for themselves from VUIT Software Store.


All course materials (readings, powerpoints slides, homework assignments, example code, solutions) will be posted on the Blackboard site for this course. You will also turn in your homework assignments on Blackboard; while you can turn in a homework assignment more than once, we will only look at and grade the last version you turn in. You can also view your grades and comments for the assignments within Blackboard as well.

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