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analysis:nsb2014 [2014/06/24 19:37] mvdm [List of Topics] |
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~~DISCUSSION~~ | ~~DISCUSSION~~ | ||
- | === List of Topics === | + | === Contents === |
- | * [[analysis:nsb2014:week1|Module 1: Good habits for data analysis (paths, backups, versioning, annotation)]] | + | * [[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: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: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:week3|Anatomy of neural data: time series, sampling, aliasing]] | ||
- | - [[analysis:course:week4|Fourier series, transforms, power spectra]] | ||
- | - [[analysis:course:week5|Filtering: filter design, use, caveats]] | ||
- | - [[analysis:course:week6|Time-frequency analysis: spectrograms]] | ||
- | - [[analysis:course:week7|Time-frequency analysis II: cross-frequency coupling]] | ||
- [[analysis:course:week8|Interactions between multiple signals: coherence and other connectivity measures]] | - [[analysis:course:week8|Interactions between multiple signals: coherence and other connectivity measures]] | ||
- | - [[analysis:course:week9|Spike train analysis: firing rate, interspike interval distributions, auto- and crosscorrelations]] | ||
- | - [[analysis:course:week10|Spike train analysis II: tuning curves, encoding, decoding]] | ||
- [[analysis:course:week11|Spike-field relationships: spike-triggered average, phase locking, phase precession]] | - [[analysis:course:week11|Spike-field relationships: spike-triggered average, phase locking, phase precession]] | ||
- [[analysis:course:week12|Basic hypothesis testing: parametric, nonparametric, bootstrapping]] | - [[analysis:course:week12|Basic hypothesis testing: parametric, nonparametric, bootstrapping]] | ||
- [[analysis:course:week13|Basic model fitting: regression, general linear models]] | - [[analysis:course:week13|Basic model fitting: regression, general linear models]] | ||
- [[analysis:course:week14|Dimensionality reduction methods, classification]] | - [[analysis:course:week14|Dimensionality reduction methods, classification]] | ||
- | - [[analysis:course:week15|Spike sorting]] | + | |
=== Prerequisites === | === Prerequisites === | ||
Basic familiarity with MATLAB. Depending on your background and programming experience you might find the following resources helpful: | Basic familiarity with MATLAB. Depending on your background and programming experience you might find the following resources helpful: | ||
- | * Textbook: {{:analysis:wallisch_matlabforneuro.pdf|Wallisch, MATLAB for Neuroscientists}} | + | * Textbook: {{|Wallisch, MATLAB for Neuroscientists}} |
+ | * [[http://www.mathworks.com/academia/student_center/tutorials/launchpad.html|"Getting Started with MATLAB" Primer]]. | ||
- | If you can solve these exercises you are ready for this course. | + | 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 === | === Resources === | ||
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This course is "standalone", but the following textbooks provide more in-depth treatment of some of the topics. | This course is "standalone", but the following textbooks provide more in-depth treatment of some of the topics. | ||
- | * Textbook: {{:analysis:leis_dspusingmatlab.pdf|Leis, Digital Signal Processing using MATLAB for Students and Researchers}} | + | * Textbook: {{|Leis, Digital Signal Processing using MATLAB for Students and Researchers}} |
- | * Textbook: {{:analysis:johnstonwu.pdf|Johnston and Wu, Foundations of Cellular Neurophysiology}} | + | * Textbook: {{|Johnston and Wu, Foundations of Cellular Neurophysiology}} |
- | * Textbook: {{:analysis:dayanabbott_theoneuro.pdf|Dayan & Abbott, Theoretical Neuroscience}} | + | * Textbook: {{|Dayan & Abbott, Theoretical Neuroscience}} |
=== What this course is === | === What this course is === |