Unit: EM Prep and Imaging

Learning goals

• Describe why EM imaging is central to connectomics.
• Explain core imaging-prep pipeline stages at a practical level.
• Interpret how voxel/resolution decisions shape downstream reconstruction.

Scope boundaries

• In scope:
  • imaging and preparation concepts needed by technical learners
  • practical interpretation of scale, resolution, and sectioning
• Out of scope:
  • exhaustive instrument engineering details
  • downstream segmentation/proofreading deep dive (Unit 08)

Website draft blocks

Hero framing

Connectomics begins with imaging choices. Resolution, sectioning strategy, and data quality constraints set the ceiling for what can be reconstructed and analyzed later.

Core concepts

• Why EM is used for circuit-scale structural mapping.
• Sectioning, imaging, and volume assembly at high level.
• Resolution/voxel tradeoffs and their scientific consequences.

Practical implications

• Imaging artifacts propagate into segmentation and analysis.
• Quality decisions early in the pipeline reduce correction burden later.
• Scale planning must align with target biological questions.

Slide draft sequence (v1)

1. Why EM for connectomics
2. Historical context and current role
3. Sectioning and imaging workflow overview
4. Resolution and voxel-size tradeoffs
5. Data volume and storage implications
6. Common imaging artifacts and mitigation
7. Bridge to reconstruction/segmentation units
8. Summary + practical checklist

Figure candidates

See: course/units/figures/03-em-prep-and-imaging-selected-v1.md

Cross-links

• Related module: module05
• Related units: 02-brain-data-across-scales, 04-volume-reconstruction-infrastructure, 08-segmentation-and-proofreading
• Related datasets: /datasets/workflow/, /datasets/mouseconnects/

Open issues

• Add one concise prep/imaging glossary block for novice learners.
• Verify any quantitative imaging benchmarks before publication copy.

Scope check (expert pass)

• Include prep chain: fixation, staining, embedding, sectioning, imaging.
• Clarify common EM acquisition families (serial section EM, SBF-SEM, FIB-SEM) at conceptual level.
• Name artifact classes that affect downstream segmentation: charging, knife chatter, folds/tears, misalignment.

Technical anchors to preserve

• Resolution-volume-throughput tradeoff is fundamental.
• QA at acquisition stage is cheaper than correction downstream.
• Imaging metadata/provenance is required for reproducible reconstruction.