Applied Electives

Level 7 is not another rung. The first seven levels are a ladder, each one assuming the one below; this level is a fan, and its eight lessons are independent of each other. Each carries its own prerequisites, drawn from wherever in the ladder it needs them — sleep from time-frequency, real-time from filtering, biomarkers from oscillations and effect sizes, scale from pipelines and reporting — so you can take one elective, or three, or all eight, in whatever order your work requires.

What you bring to them is the thing the ladder was for. You can read a raw trace and name what is on it; you can turn a recording into a spectrum and say which parts of it are rhythms; you can build a preprocessing pipeline whose every decision is written down; you can measure an ERP without letting the measurement choose itself; you can tell a connectivity result from a volume-conduction artifact; and you can state what a p-value licenses and what it does not. Every elective here assumes all of that and adds one domain’s own constraints on top — because in each of them the constraint, rather than the analysis, is what decides the answer. A BCI is judged by cross-subject transfer; a real-time loop by a latency budget you can decompose; a consumer headset by a hardware bandwidth that has nothing to do with its sampling rate; a biomarker by a reliability that bounds every effect size you will ever report from it.

Three of these lessons ship with less than was planned, and in each case the reason is the same policy and it is worth reading before you start. L7.4 has no figure of an epileptiform discharge, because no dataset here whose licence permits shipping a snippet contains a scored one, and drawing a plausible spike would fabricate the clinical finding the lesson warns you not to over-read. L7.7 has no widget, no notebook and no figure at all: this site holds no simultaneous EEG–fMRI, EEG–TMS or EEG–eye-tracking recording, so the gradient artifact, the ballistocardiogram and the TMS pulse are described rather than shown. L7.5 lost a dataset outright — ds-mpeng turned out to be CC BY-NC 4.0 rather than the CC BY 4.0 this site’s catalog had recorded, downstream of the consent its participants gave, so it is named, described and linked, and nothing here derives from it. None of the three is a gap in the teaching. They are what it looks like when a site refuses to show you something it cannot honestly show, and the reasoning is in each lesson rather than in a footnote.

The capstone is where the ladder ends: reproduce a published result end to end, from raw, with the plan committed before the analysis and a repository anyone can run. It is the only capstone that asks you to publish rather than to write, and the only one whose rubric is about a stranger’s machine.

Three pages exist for what comes after. /datasets is the directory as a working instrument — twenty-eight entries with their licences, access classes, acquisition tables and documented caveats, which is where an analysis plan should start rather than end. /cite is how to cite this site and, more usefully, how to cite every dataset it names, with the DOI and the reference text already assembled. /changelog records what changed here and when, which matters because several of the facts in these lessons — a licence, an access class, a field nobody has been able to confirm yet — are the current state of a record rather than a permanent truth, and the honest thing a teaching site can offer is a date.