We help research labs standardize, share, and publish their neurophysiology data through custom software solutions and expert consulting.
We bridge the gap between academic research and professional software engineering. Our team combines deep neuroscience domain expertise with production-grade development practices, delivering solutions that are both scientifically rigorous and built to last.
Our engineers have published research and understand the nuances of neurophysiology data.
No vendor lock-in. Every tool we build is open source and belongs to the community.
Professional testing, documentation, and long-term maintainability. Not just research prototypes.
CatalystNeuro has worked successfully with diverse scientific research groups in a variety of capacities. All work we do is open source, so our team can fit seamlessly with research groups without worry of expensive licensing fees or vendor lock-in.
Convert your data to Neurodata Without Borders (NWB) and publish on the DANDI Archive.
Integrate existing analysis, visualization, and data management tools with open data via NWB and DANDI.
Leverage AI and machine learning to accelerate neuroscience research.
Working with the team at CatalystNeuro was a terrific, highly productive experience. They revamped a bespoke volumetric imaging pipeline we had developed, integrated it with our behavioral data, and made it all compatible with NWB. My lab has already used their CatalystNeuro pipeline in publication, and will undoubtedly find their NWB toolkit of great use in the future.
The DANDI Semantic Atlas places every Dandiset on a rotatable map built from sentence embeddings of its metadata, so datasets that describe similar science end up near one another. It rebuilds itself nightly from the DANDI API.
A new HDF5 virtual file driver that streams remote NWB files over HTTP with adaptive caching. It opens files several times faster than ROS3, works with any HDF5 build, and is now integrated into AqNWB.
zarr-matlab is a free, open-source, pure-MATLAB implementation of the Zarr v3 specification, bringing chunked, compressed, cloud-friendly N-dimensional arrays to MATLAB with interoperability tested against zarr-python on every commit.
Book a free 30-minute call and we'll map out the fastest path to standardized, shareable, reusable data.
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