Content Library

Explanations, worked examples, and case studies for connectomics methods.

Find a method, a worked example, or background on a technical question. These reference pages can be read in any order.

Search topics across the siteFollow the connectomics course
About these reference pages

What this is

The content library is core reference material: the depth behind the one-sentence claims made in the technical units and modules.

It has no order and no end. You are not meant to work through it. Come here when a unit asserts something you want the argument for, when you need the worked example rather than the result, or when you are about to do a specific technical thing and want to read how it is done properly first.

If you want an order, that is what a track is for.

How this library works

Every entry below is a standalone, richly detailed reference document. Each contains:

  • Full instructor-ready narrative (not just bullet points)
  • Real scientific references with context
  • Worked examples with step-by-step reasoning
  • Common misconceptions and how to address them
  • Tags for cross-referencing across dimensions
  • Combines-with links identifying entries that pair well together, shown at the top of each entry
  • Real electron micrographs on the entries that make visual claims, rendered from the public H01 human cortex volume — see the EM figure library. Entries also carry older reference_images front matter describing figures that were specified but never produced; that metadata is not rendered, and is being replaced by the figures above as each entry is covered

Unit pages, slide decks, and modules link to these entries rather than duplicating content. This keeps the curriculum DRY (Don’t Repeat Yourself) and ensures a single source of truth for each topic.

Tag dimensions

Content is tagged across 9 dimensions for flexible combination:

Dimension Color Example tags
Neuroanatomy #4A90D9 soma, dendrite, axon, synapse, spine, organelle
Imaging #7B68EE electron-microscopy, SEM, TEM, FIB-SEM, SBEM, ATUM
Infrastructure #E67E22 pipeline, segmentation, alignment, CAVE, neuroglancer
Proofreading #E74C3C merge-error, split-error, QA-metrics, expected-run-length
Cell Types #27AE60 neuron-classification, glia, pyramidal-cell, interneuron
Connectomics #F39C12 graph-theory, motif, community-detection, hub, modularity
NeuroAI #9B59B6 structure-function, bio-inspired-architecture, deep-learning
Case Studies #1ABC9C FlyWire, MICrONS, H01, C-elegans, Drosophila
Methodology #95A5A6 experimental-design, reproducibility, benchmark, ground-truth

Neuroanatomy

Ultrastructural biology of neurons as seen in electron microscopy.

Browse the 160 neuroanatomy papers in the journal club →

Entry Scope Primary units
Soma ultrastructure Nuclear envelope, Nissl substance, Golgi, lipofuscin; EM identification 05
Dendrite biology Spine types, PSDs, microtubule organization, local translation 05, 06
Axon biology AIS, myelinated segments, boutons, vesicle pools, active zones 05, 06
Synapse classification Gray Type I/II, asymmetric vs symmetric, cleft structure 05, 08
Organelle annotation cues Mitochondria, ER, MVBs, lysosomes as compartment indicators 05, 06
Myelin and nodes of Ranvier Compact myelin, paranodal loops, Schmidt-Lanterman incisures 05, 06

Proofreading

Quality control of automated segmentation at connectome scale.

Proofreading and quality-control reading list → (the corpus has no separate proofreading dimension; proofreading papers sit under pipeline)

Entry Scope Primary units
Error taxonomy Merge, split, boundary, and identity errors with examples 08
Proofreading strategies Exhaustive, targeted, priority-ranked, crowd-sourced approaches 08
Proofreading tools CAVE, Neuroglancer, FlyWire, NeuTu; editing operations 08
Metrics and QA VI, ERL, edge F1, synapse-centric F1 with formulas 08
Worked examples Step-by-step correction scenarios for merge, split, synapse errors 08

Connectomics

Graph analysis, motif search, and the bridge to NeuroAI.

Browse the 300 circuit-structure papers in the journal club → (or the curated network analysis and statistics list)

Entry Scope Primary units
Connectome history C. elegans through FlyWire and MICrONS; milestones and lessons 01, 09
Graph representations Nodes, edges, weights, adjacency matrices, multigraphs 09
Network analysis methods Degree, clustering, path length, community detection, spectral 09
Motif analysis DotMotif, null models, subgraph isomorphism, statistics 09
NeuroAI bridge Structure-function, bio-inspired architectures, connectome-constrained models 09
Open problems for undergraduate teams Seven open problem areas scoped for undergrad teams, tied to BRAIN CONNECTS bottlenecks 01, 08, 09
Ethics and governance H01’s consent and provenance, de-identification in EM, portal licences and what they oblige, dual use, credit for proofreading labour 01, 08

Imaging

EM acquisition, image formation, and artifact management.

Browse the 160 volume-EM and optics papers in the journal club →

Entry Scope Primary units
EM principles Beam physics, contrast mechanisms, SEM vs TEM, resolution limits 03
Artifact taxonomy Knife chatter, charging, folds, tears, drift; downstream impact 03, 05
Tissue preparation Fixation, heavy-metal staining, embedding, sectioning strategies 03
Acquisition QA Per-tile QC, pilot reconstructions, metadata requirements 03

Infrastructure

Reconstruction pipelines, data formats, and reproducibility.

Browse the 300 pipeline and software-engineering papers in the journal club →

Entry Scope Primary units
Reconstruction pipeline Ingest, alignment, segmentation, agglomeration, serving 04
Data formats and representations Volumes, meshes, skeletons, graphs; when to use each 02, 04
Provenance and versioning Lineage metadata, CAVE materialization, reproducible reprocessing 04, 08
Synapse detection Cleft localisation, partner assignment, E/I classification; CREMI and what it predicts; cross-dataset degradation; what to check before trusting a synapse table 04, 05, 08

Cell types

Identification and classification of neuronal and glial cell types in EM.

Browse the 160 cell-type papers in the journal club →

Entry Scope Primary units
Axon-dendrite classification Multi-cue discrimination, edge cases, confidence scoring 06
Glia recognition Astrocytes, microglia, oligodendrocytes; boundary ambiguities 07
Neuron type identification Morphological and connectivity-based classification 05, 06, 09

Case studies

Deep dives into landmark connectomics projects.

Entry Scope Primary units
FlyWire whole-brain connectome 140K neurons, collaborative proofreading, brain-wide circuit analysis 08, 09
MICrONS visual cortex mm³ mouse cortex, functional connectomics, structure-function linking 01, 03, 08, 09
H01 human cortex Petavoxel human fragment, unique challenges, pathological features 05, 08
H01, step by step The full production pipeline — tissue, staining, sectioning, 61-beam imaging, alignment, segmentation, synapse detection — with figures rendered from the public volume 03, 04, 08
C. elegans revisited The first connectome, re-analysis, developmental connectomics 01, 09
MouseConnects HI-MC NIH BRAIN CONNECTS flagship, 10 mm³ hippocampus, ongoing project 01, 04

EM figure library

Every electron micrograph on this site in one place — with captions, attribution and ready-to-paste slide lines. All rendered from the public H01 human cortex volume and reusable under CC BY 4.0.

Browse the EM figure library →

Journal paper collection & literature corpus

A searchable corpus of 2,000 connectomics publications across 12 research domains and 3 nested tiers (Core 500, Expanded 1,000, Full 2,000). Browse recorded abstracts and citation relationships, with source-checked contribution notes where available. Each contribution note identifies the reported result, test context, limitations, source, and checking provenance; check substantive claims against the original publication.

Where each corpus domain leads

Every paper in the corpus carries one of twelve domain labels. The domain name links to the journal club filtered to that domain — that is the corpus itself, and it always works. The reading list column is a hand-annotated deep dive of 8–10 papers where one exists for that domain, and says so plainly where one does not. The library entry point is the reference page on this site that covers the same ground in prose.

Paper counts are the labels actually carried by the 2,000 shipped records, not the design allocation. The design allocation — the target share and tier split per domain — is on the corpus hub.

Corpus domain Papers Curated reading list Library entry point
Circuit Structure & Connectomes 300 Connectomics Connectome history
Pipeline & Software Engineering 300 Data storage & pipelines · Computer vision & ML Reconstruction pipeline · Synapse detection
Physiological Validation & Function 242 None yet — the largest gap in the deep-dive set MICrONS visual cortex
Behaviour & Circuit Dynamics 240 Case studies FlyWire whole-brain connectome
Volume EM & Advanced Optics 160 Imaging & sample preparation EM principles
Cell Types & Morphological Census 160 Cell types & morphology Neuron type identification
Neuroanatomy & Ultrastructure 160 Neuroanatomy Synapse classification
Synthesis, Theory & Reviews 142 Network analysis & statistics Open problems for undergraduate teams
Benchmark Datasets & Repositories 115 Datasets & case studies Datasets catalogue
NeuroAI, Biophysics & Models 100 NeuroAI & computational modeling NeuroAI bridge
Health, Disease & Translation 42 None yet H01 human cortex
Workforce Training & Outreach 21 None yet Ethics and governance

Two labels sit outside the twelve: 16 papers classified other, and 2 classified mri. Macroscale connectivity is out of scope for a nanoscale corpus, which is why the count is 2 — but the curated MRI & meso-connectomics reading list (10 papers on diffusion MRI and tractography) exists for readers arriving from that side of the field. It is a bridge out of this library, not a route into it.

How the corpus was selected, tiered and annotated is a separate question, and it has its own page: How the paper collection is built.