Journal Paper Collection

A curated library of essential connectomics papers, organized by dimension and tagged for cross-referencing with the content library. Each paper includes:


By Dimension

Dimension Papers Focus
Neuroanatomy 6 Ultrastructure, synapses, spines, organelles, serial reconstruction
Imaging & Sample Preparation 6 SBEM, FIB-SEM, ATUM, tissue preparation, acquisition pipelines
Computational Infrastructure 6 Segmentation (FFN, affinity), annotation (CAVE, VAST), pipeline engineering
Proofreading & Quality Control 6 Crowd-sourced proofreading, error detection, agglomeration, QA metrics
Cell Types & Classification 6 Morphological, transcriptomic, connectivity-based classification
Graph Analysis & Network Science 6 Graph theory, motifs, community structure, comparative connectomics
NeuroAI & Computational Modeling 6 Structure-function, bio-inspired AI, learning rules, model taxonomy
Datasets & Case Studies 7 C. elegans, FAFB/FlyWire, MICrONS, H01, Kasthuri, Cook

Total: 49 papers across 8 dimensions.


How to Use This Collection

For self-study

Start with the beginner summary to orient yourself, then read the paper, then compare your understanding with the intermediate and advanced summaries. Use the key figures list to focus your reading.

For journal club

Use the discussion prompts to structure group discussion. The three-level summaries help facilitators calibrate discussion depth for mixed-expertise groups. See the Technical Track Journal Club for scheduling guidance.

For micro lesson design

Use tags to find papers that align with specific content library entries. The combines_with field on content library entries and the Related content links on papers create a cross-referenced web for assembling multi-resource micro lessons.

For course design

Papers are organized to follow the technical training sequence. Each dimension aligns with specific technical training units:

Dimension Primary units
Neuroanatomy 05, 06
Imaging 03
Infrastructure 04, 08
Proofreading 08
Cell Types 05, 06, 07
Connectomics 09
NeuroAI 09
Case Studies 01, 02, 08, 09

Expertise Level Guide

Level Assumes Best for
Beginner No neuroscience or connectomics background New trainees, interdisciplinary collaborators, public engagement
Intermediate Familiar with EM, basic neuroscience, and computational concepts Graduate students, postdocs entering the field
Advanced Active researcher or advanced trainee Methodological deep dives, experimental design, peer review