Paths through the core, on two independent axes: what you are learning, and how you are using it.
The core is reference material: the content library, dictionary, journal club, atlas, hidden curriculum, and datasets. It has no order, and you are not meant to finish it.
Tracks are paths through it. Each selects from the core, puts it in a sequence, and adds labs that end in something you have made. A track is finishable, and each track page states what "done" means as a capability rather than as a set of pages visited.
Tracks are split two ways, and the two are independent:
Any track can be worked in any available mode. Pick the topic below, then the mode — or the other way round, if your situation is the fixed part.
Three tracks, aligned to the Fadel dimensions. Most people should start with Core Concepts & Methods and layer the others in as their practice develops.
Build scientific and technical fluency in nanoscale connectomics from motivation through analysis methods.
Time: 60-70 hours of focused work, typically over 12-16 weeks
Starting point: None. Introductory biology and comfort with basic arithmetic are enough to start.
Apply concepts in practical workflows, quality control, tools, and reproducible research operations.
Time: 70-80 hours, typically over 14-18 weeks, alongside a real project
Starting point: Core Concepts & Methods, or equivalent working familiarity with EM data and reconstruction.
Navigate hidden curriculum, mentorship, professional growth, and inclusive research identity development.
Time: 35-45 hours, spread across the whole of a training period rather than completed in a block
Starting point: None. This track is relevant from week one, not only at the end.
The same track is a different thing depending on the situation you are in. Two modes exist today; the third is declared because the gap is real, not because it is built.
One person, a browser, and public data. No cohort, no schedule.
For: Anyone working through the material on their own time, at any career stage.
A facilitator runs a session. Timing, materials, and rubric are already written.
For: Instructors, mentors, and program staff running a taught session, a lab meeting, or a summer-program block.
A longer, contributory program that draws on this material. Not built yet.
For: Trainees working inside a lab or program on real data, producing work others will rely on.
Every track routes through the same reference layer. If a track's sequence does not suit you, going straight to the core is a legitimate way to use this site.
Long-form reference documents at instructor depth: neuroanatomy, ultrastructure, imaging, infrastructure, cell types, connectomics, proofreading and case studies. Each entry runs a full argument with worked examples, misconceptions, and real references, rather than summarizing one.
Every term carries a definition, typical values with units, why the term matters, and what it is commonly confused with. The confusion field is the useful one: most vocabulary errors in this field are near-miss substitutions, not blanks.
The literature organized by topic, each entry stating what the paper established, what it did not establish, and the specific thing worth arguing with. Discussion prompts are written for a group but work alone.
The lookup layer: spatial and temporal scales side by side, canonical dataset dimensions, the acronym set, and the numbers that recur across the curriculum, with units attached and sources named.
The operating knowledge research training assumes you already have: technical practice, reading and judging, lab norms, career mechanics, meta-learning, belonging, and handling conflict. Written down because it is otherwise transmitted only by proximity to someone who already knows, which distributes it unequally by background.
What public volumes exist, what each can and cannot answer, how to get access, and the acquisition-to-interpretation workflow they sit inside. Includes the version-pinning practice that every downstream analysis depends on.
The tracks are a convenience, not a gate. Four routes that work as well for many people: