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Basic familiarity with MATLAB. Depending on your background and programming experience you might find the following resources helpful:

If you are unsure, take a look at the table of contents of the Primer. If there are things you don't recognize, use the Primer itself, or Chapter 2 of the MATLAB for Neuroscientists book to get up to speed.


This course is “standalone”, but the following textbooks provide more in-depth treatment of some of the topics.

What this course is

A hands-on introduction to basic management, visualization, and analysis of neurophysiology data (spike trains and LFPs from behaving rodents) using MATLAB. We will make contact with a few concepts from computer science, signal processing, and statistics. However, the focus is on making initial steps that work and getting pointers to more complete treatment, rather than a thorough theoretical grounding.

What this course is not

This course will provide a brief introduction to a number of concepts which are themselves the subject of multiple courses and thick textbooks. These include signal processing topics such as Fourier analysis and filter design, computer science concepts such as object-oriented programming and binary data formats, and a number of statistical ideas and tools. Be aware that if any of these are particularly important to your research, you should consider taking more in-depth coursework and/or working through relevant textbooks on your own.

Note for Linux and OS X users

The lab codebase is set up for machines running 64-bit Windows 7. To make the low-level loading functions work on OSX or Linux, you'll need to download them yourself from the Neuralynx website. Some more specific instructions are provided in subsequent modules when loading is introduced.


If you are using a vandermeerlab computer, make sure you have read the General info. Note that one of the steps is to send me confirmation that you understand and agree with certain things. Do this before going any further.

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analysis/nsb2014.txt · Last modified: 2018/07/07 10:19 (external edit)