Enabling Big-Data Neuroscience
We work together with neuro experimentalists to discover fundamental principles governing the relationship between mind and brain — through open-source, data-driven tools that run at scale.
High-Throughput Imaging
Access multi-teravoxel brain imaging datasets captured via electron microscopy, CLARITY, array tomography, two-photon calcium imaging, and fMRI.
Scalable Infrastructure
A distributed database cluster designed for spatial analysis and annotation of high-throughput data. All interfaces are RESTful web services for maximum scalability.
Open Access
All datasets and services are publicly available. Our goal is to bring world-class scientific data to anyone with internet access — no barriers, no paywalls.
Neural Circuit Mapping
Reconstructing the structure and connectivity of the brain using computer vision pipelines on supercomputers, co-registered in scalable databases.
Community-Driven
"Alg-sourcing" — automated computer vision algorithms contributed by the community to reconstruct neural circuits collaboratively at scale.
Data-Intensive Science
Understanding the mechanisms for computation in the human brain and the neurological basis of complex disorders like autism, ADHD, and Alzheimer's.
From Cosmos to Connectomes
The Open Connectome Project (OCP) is a Johns Hopkins University initiative that provides access to high-resolution neuroanatomical images that can be used to explore connectomes. We provide programmatic access to this data for human and machine annotation, with a long-term goal of reconstructing the neural circuits comprising an entire brain.
Read More →Key Publications
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Vogelstein et al. A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data. Nature Methods, (11)15:846–847, 2018.
Nature Methods · 2018 -
Burns, Vogelstein, Szalay. From cosmos to connectomes: The evolution of data-intensive science. Neuron, (6)83:1249–1252, 2014.
Neuron · 2014 -
Burns et al. The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience. ACM SSDBM, 2013.
ACM SSDBM · 2013