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analysis:course

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~~DISCUSSION~~

List of Topics

  1. Time-frequency analysis II: cross-frequency coupling, phase-amplitude relationships
  2. Interactions between multiple signals: coherence and phase slope index
  3. Spike train analysis: firing rate, interspike interval distributions, autocorrelation, spike spectrum
  4. Spike train analysis II: tuning curves, encoding, decoding
  5. Spike-field relationships: phase locking, phase precession, cell assemblies
  6. Basic parametric hypothesis testing
  7. Bootstrapping and nonparametric tests
  8. Regression models
  9. Principal component analysis, classification
  10. Spike sorting

Resources

What this course is

A hands-on introduction to basic management, visualization, and analysis of vandermeerlab data (spike trains and LFPs from behaving rats) 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.

The general format is that you work through the materials presented here on the wiki, you upload your work, I look at it, and we all discuss together at the following class meeting. So for the Week 2 meeting, work through the material under (1) above.

Class meetings are initially set for 1.30-3.00pm in PAS 2464, but this might change – changes will be announced by e-mail. There is no course website other than this one.

What this course is not

Formal, thorough, complete.

Assessment (only relevant if you are taking this course for credit)

Most weeks have you accomplish a series of tasks for which it will be obvious if you have succeeded or not. If you do only these and no more, you will receive a mark of 70%, but there are many ways to do better.

For instance, most weeks additionally will have more open-ended problems, for which a range of solutions and accompanying interpretations are possible, some of which will be better than others.

Contributions to the course wiki (elaborations, clarifications, useful resources, etc.) are also valued.

Collaboration on all aspects of the course is encouraged! As always, work you submit should reflect your own understanding; copying code is not allowed. Recall the uWaterloo guidelines on this.

OS X users

The lab codebase is set up for machines running 64-bit Windows 7. I have seen everything done on a Mac, but I don't own one and cannot tell you much about how to make it work. Neuralynx has OS X versions of their MATLAB data loaders.

Preliminaries

If you are using a lab 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.

Next, add your name and e-mail address to the course participants page.

Each wiki page has a Subscribe option, so you can get updates by e-mail when the page is changed; please do this, the subscription link is on the right of the page.

analysis/course.1382543599.txt.gz · Last modified: 2018/07/07 10:19 (external edit)