Lecture Plan: Why Map the Brain

What this document is

This page is a build plan for an instructor assembling a lecture on this unit. It gives the slide sequence, per-slide timing, the points at which figures belong, and the speaker notes that carry the argument. It is a design document, not a rendered deck: there are no slides on this page to project, and nothing here is written to be shown to learners as it stands.

A separately maintained Marp deck for this unit does exist, and it is linked at the foot of this page under Rendered deck artifacts. That deck was authored in its own right and does not follow this plan slide for slide, so treat this page as the teaching design and the Marp file as one existing implementation of it. The learner-facing material is the unit page linked under Connections.

Session profile

• Audience: advanced undergrad, graduate, and early-career researchers.
• Duration: 70 minutes lecture + 15 minutes discussion.
• Output: one hypothesis brief with measurable connectomics endpoints.

Slide-by-slide lecture plan

1. Slide 1 (2 min): Title and positioning
   • Technical Training: Nanoscale Connectomics as a hypothesis engine.
   • State this unit as the epistemic boundary-setting lecture.
2. Slide 2 (4 min): Why map structure at all?
   • Structural constraints as priors for mechanism.
   • Historical successes and modern scale shift.
3. Slide 3 (5 min): What structure can and cannot claim
   • Structure constrains candidate computations.
   • Structure alone does not prove dynamic causality.
4. Slide 4 (6 min): From biological question to measurable endpoint
   • Convert broad questions into quantifiable graph or morphology outputs.
   • Examples: motif enrichment, compartment targeting, path length constraints.
5. Slide 5 (6 min): Measurement units and data products
   • Synapse tables, skeletons, meshes, connectivity graphs.
   • Match unit choice to hypothesis.
6. Slide 6 (6 min): Minimum evidence requirements
   • Completeness thresholds by claim type.
   • Error budgets and uncertainty labeling.
7. Slide 7 (5 min): Null models and comparators
   • Degree-preserving and spatially constrained controls.
   • Why null mismatch invalidates conclusions.
8. Slide 8 (6 min): Worked example A
   • Local recurrent motif hypothesis from cortical microcircuit.
   • Define readout, null, and falsification condition.
9. Slide 9 (6 min): Worked example B
   • Cell-type-specific targeting hypothesis.
   • Show where scaling or annotation error breaks inference.
10. Slide 10 (5 min): Common failure modes
    • Claim inflation, metric mismatch, and dataset mismatch.
11. Slide 11 (5 min): Practical protocol
    • Five-step pre-analysis checklist for structural claims.
12. Slide 12 (4 min): Journal-club bridge
    • Required paper tie-in and what to extract from methods.
13. Slide 13 (5 min): In-class mini-lab prompt
    • Draft one study brief with question, metric, null, and limitation.
14. Slide 14 (5 min): Debrief and bridge to Unit 02
    • Scale selection as next gating technical decision.

Figure integration points

• Primary shortlist: course/units/figures/01-why-map-the-brain-selected-v1.md.
• Use one visual each for: motivation, evidence boundary, and hypothesis-to-metric mapping.

Speaker notes (expert-level)

• Explicitly separate descriptive outputs from mechanistic inference.
• Use at least one counterexample where strong structure data still leaves function ambiguous.
• Emphasize reproducibility requirements before interpretation.

Assessment and artifacts

• Deliverable: 1-page hypothesis brief.
• Rubric dimensions: testability, measurement alignment, null-model fit, and claim discipline.

Connections

• Unit page: Why Map the Brain
• Journal club: Technical Track Journal Club
• Dictionary: Connectomics Dictionary
• Existing module overlap: module01

Rendered deck artifacts