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analysis:course [2013/11/14 10:06] mvdm [List of Topics] |
analysis:course [2018/07/07 10:19] (current) |
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- [[analysis:course:week7|Time-frequency analysis II: cross-frequency coupling]] | - [[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, autocorrelation, spike spectrum]] | + | - [[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:week10|Spike train analysis II: tuning curves, encoding, decoding]] | ||
- | - Spike-field relationships: phase locking, phase precession, cell assemblies | + | - [[analysis:course:week11|Spike-field relationships: spike-triggered average, phase locking, phase precession]] |
- | - Basic parametric hypothesis testing | + | - [[analysis:course:week12|Basic hypothesis testing: parametric, nonparametric, bootstrapping]] |
- | - Bootstrapping and nonparametric tests | + | - [[analysis:course:week13|Basic model fitting: regression, general linear models]] |
- | - Regression models | + | - [[analysis:course:week14|Dimensionality reduction methods, classification]] |
- | - Principal component analysis, classification | + | - [[analysis:course:week15|Spike sorting]] |
- | - Spike sorting | + | |
=== Resources === | === Resources === | ||
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=== What this course is not === | === What this course is not === | ||
- | Formal, thorough, complete. | + | 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. |
=== Assessment (only relevant if you are taking this course for credit) === | === Assessment (only relevant if you are taking this course for credit) === | ||