neuPrint

neuPrint provides graph-database-backed query and analysis of connectome data to support study of neural connectivity reconstructed from electron microscopy.

Key Features:

• Data Model and Database Integration: Organizes connectome data as a graph database using Neo4j, accommodating datasets with tens of thousands of neurons and millions of synaptic connections, including examples from Drosophila melanogaster.
• Cypher Query Language: Exposes the Cypher query language to access connectome data at multiple levels of abstraction for both detailed and summary analyses.
• Connectomics REST Interface: Provides a RESTful interface with authenticated and unauthenticated modes for programmatic access to the connectome data model.
• Programmatic API: Offers a programmer-facing API exposing endpoints for automated data retrieval and interaction with the graph model.
• Compatibility with Modern Workflows: Includes tools for assessing reconstruction quality and supports batch and incremental updates to integrate with evolving connectome reconstruction workflows.
• Query and Visualization Plugins: Includes query plugins for reusable Cypher queries and visualization plugins that provide reusable visualizations and query outputs.

Scientific Applications:

• Large-scale connectome analysis: Enables analysis of large-scale neural networks, including whole-brain or region-scale connectomes such as those from Drosophila melanogaster.
• Multi-scale connectivity analysis: Supports both single-neuron/synapse-level investigations and network-level summaries to study circuit organization and connectivity patterns.
• Reconstruction quality assessment: Facilitates assessment of the quality of automated reconstructions and the integration of quality metrics into reconstruction workflows.

Methodology:

Uses a Neo4j graph database queried via Cypher, exposes a RESTful API with authenticated and unauthenticated modes, supports batch and incremental updates, and provides query and visualization plugins plus tools for reconstruction quality assessment.