~~DISCUSSION~~

=== Contents ===

   * [[analysis:nsb2014:week0|Introduction: Principles of careful data analysis]]
   * [[analysis:nsb2014:week1|Module 1: Good data management habits and tools (paths, backups, versioning, annotation)]]
   * [[analysis:nsb2014:week2|Module 2: Introduction to Neuralynx data formats and preprocessing]]
   * [[analysis:nsb2014:week3|Module 3: Anatomy of neural data: time series, sampling, aliasing]]
   * [[analysis:nsb2014:week4|Module 4: Spike sorting]]
   * [[analysis:nsb2014:week5|Module 5: Visualizing neural data in MATLAB]]
   * [[analysis:nsb2014:week6|Module 6: Fourier series, transforms, power spectra]]
   * [[analysis:nsb2014:week7|Module 7: Filtering: filter design, use, caveats]]
   * [[analysis:nsb2014:week8|Module 8: Time-frequency analysis: spectrograms]]
   * [[analysis:nsb2014:week9|Module 9: Time-frequency analysis II: cross-frequency coupling]]
   * [[analysis:nsb2014:week10|Module 10: Interactions between multiple signals: coherence and other connectivity measures]]
   * [[analysis:nsb2014:week11|Module 11: Spike train analysis: firing rate, interspike interval distributions, auto- and crosscorrelations]]
   * [[analysis:nsb2014:week12|Module 12: Spike train analysis II: tuning curves, encoding, decoding]]
   * [[analysis:nsb2014:week13|Module 13: Spike-field relationships: spike-triggered average, phase locking, phase precession]]

FIXME Modules still to be adapted for NS&B by %%MvdM%% (can look as a preview, but will not work):

   - [[analysis:course:week8|Interactions between multiple signals: coherence and other connectivity measures]]
   - [[analysis:course:week11|Spike-field relationships: spike-triggered average, phase locking, phase precession]]
   - [[analysis:course:week12|Basic hypothesis testing: parametric, nonparametric, bootstrapping]]
   - [[analysis:course:week13|Basic model fitting: regression, general linear models]]
   - [[analysis:course:week14|Dimensionality reduction methods, classification]]


=== Prerequisites ===

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

  * Textbook: {{|Wallisch, MATLAB for Neuroscientists}}
  * [[http://www.mathworks.com/academia/student_center/tutorials/launchpad.html|"Getting Started with MATLAB" Primer]]. 

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.

=== Resources ===

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

  * Textbook: {{|Leis, Digital Signal Processing using MATLAB for Students and Researchers}}
  * Textbook: {{|Johnston and Wu, Foundations of Cellular Neurophysiology}}
  * Textbook: {{|Dayan & Abbott, Theoretical Neuroscience}}

=== 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.

=== Preliminaries === 

If you are using a vandermeerlab computer, make sure you have read the [[computing:labcomputers|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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