The Kavli Foundation has provided seed grants to aid labs in standardizing their experimental data using the NWB data format. Funds were used to support the building and sharing of data or software in the NWB:N ecosystem. We are no longer accepting applications for 2022 and 2023.
Recent seed grant awardees include:
- Kurt Haas, University of British Columbia
- SWC Integration with NWB
- Chi Wang Ip, University Hospital Würzburg
- Extending NWB standard and NWB widgets to capture DBS datasets
- Lauri Nurminen, University of Houston
- Database to share data for optogenetic perturbation of recurrent cortical connections
- Johannes Sarnthein, University of Zurich
- Convert dataset of human single neuron recordings
- Dennis Segebarth, University Hospital Würzburg
- Converting Defence Circuits Lab data into NWB
- Stephan Bickel, Feinstein Institute of Medical Research
- Converting iEEG dataset into NWB
- Dayu Lin, New York University
- Developing codes for translating fiber photometry datasets into NWB
- Mala Murthy, Princeton University
- Adding NWB functionality to SLEAP: An Open Source Platform for Multi-Animal Pose Tracking
- Ruben Portugues and Luigi Petrucco, Technical University of Munich
- Bring zebrafish datasets to NWB with a Stytra data converter
- Chris Rogers, Emory University
- Converting mouse model of object recognition data
- John Thompson and Daniel Kramer, University of Colorado Anschutz
- Use of NWB format for three unique intracranial human datasets
- Lingling Yang, University of Minnesota
- Convert data from Neuromodulation Research Center into NWB
- György Buzsáki, New York University
- Translating electrophysiological datasets collected in the Buzsáki Lab into NWB for public access
- Rosa Cossart and Michel Picardo, Institut de Neurobiologie de la Méditerranée
- NWB compatible open-source toolboxes for calcium imaging
- Robert Gaunt and Rehab Neural Engineering Labs, University of Pittsburgh
- Integrating Multipurpose Data Framework with NWB using data from sacral spinal cord stimulation in cats
- Ashley Juavinett, University of California, San Diego
- Training students and educators to use Neurodata Without Borders for learning Neural Data Science
- Sabine Kastner, Princeton University
- Integrating non-human primate electrophysiological data collected through different recording systems into NWB to promote data sharing and open research
- Eric Kuebler and Julio Martinez, Western University
- Conducting a cross-species, cross-laboratory comparison of mouse, macaque, and human cortical intracellular electrophysiology datasets using NWB
- Alexander Mathis, EPFL
- Integrate NWB data format within the DeepLabCut ecosystem
- Rebecca Mease with Alexander Groh, Heidelberg University
- Standardize in vivo single and multiunit electrophysiology recordings from neurons in the corticothalamic system in the NWB format
- Konstantinos Nasiotis, Nevronas Inc.
- Provide interoperability between Brainstorm and matNWB
- Josef Parvizi, Stanford University
- Convert ECoG data collected from humans during mathematical processing tasks
- Diego Restrepo and Serapio Baca, University of Colorado, Anschutz Medical Campus
- Reading out/in NWB data streams for olfactory studies that utilize electrophysiology, calcium imaging, and behavioral discrimination tasks
- Edward Ruthazer and Dylan Roskams-Edris, McGill University
- A NWB data standardization pipeline for electrophysiology and 2-photon data in Xenopus and Zebrafish
- Tim Buschman, Princeton Neuroscience Institute, Princeton University
- Convert electrophysiological recordings from non-human primates performing a working memory task into the NWB format.
- Andrea Giovannucci, The University of North Carolina at Chapel Hill
- A graphical visualization tool for NWB calcium imaging pipelines.
- Dieter Jaeger, Emory University
- Create NWB format for multiscale analysis of sensory-motor cortical gating in behaving mice
- Simon Schultz, Imperial College London
- Adapt NeuroSEE two photon calcium imaging pipeline to NWB, and convert electrophysiology (Tang, PLOS ONE, 2016) and calcium imaging data in mice.
- Nick Steinmetz, University of Washington
- Convert extracellular electrophysiology data recorded using a neuropixel probe in mice.
- Shreejoy Tripathy, Centre for Addiction and Mental Health in Toronto
- Converting Axon Binary Format based intracellular electrophysiology data files to NWB
- Taufik Valiante, University of Toronto
- Convert whole cell patch-clamp electrophysiological recordings from human cortical neurons into the NWB format.
- Joshua Berke, University of California, San Francisco
- Convert a data set collect from dopamine neurons in the rat ventral tegmental area into the NWB format.
- Eddie Chang, University of California, San Francisco
- Convert an ECoG dataset from a human electrophysiological experiment into the NWB format for sharing.
- Nuo Li, Baylor College of Medicine
- Create tutorials for the neuroscience community to demonstrate how to use API functions to convert MATLAB data structures into NWB files, using data taken from premotor cortex during decision-making.
- Daniel O’Connor, Johns Hopkins University
- Convert dataset of recordings from primary afferent neurons that innervate mouse whiskers in behaving animals into NWB format.
- Ueli Rutishauser, Cedars-Sinai Medical Center
- Convert dataset of >1000 human single neuron recordings collected during a recognition memory task into the NWB format.
- Bernardo Sabatini, Harvard University
- Convert whole-cell electrophysiological data from mouse acute brain slices in response to stimulation and/or after application of peptide and small-molecule neuromodulators into the NWB format.
- Anne Churchland, Cold Spring Harbor Laboratory
- Convert existing data sets from the Churchland lab (imaging and electrophysiology) into NWB format for sharing.
The Kavli Foundation is providing support (2019-present) to Oliver Rübel at the Lawrence Berkeley National Lab to support community engagement, outreach and software development. This program is currently supporting Benjamin Dichter as a community liaison for NWB:N.
The Simons Foundation funds projects (Aug.2017 – present) to develop and expand the NWB2.0 Matlab API MatNWB to allow for adoption by a larger portion of the neuroscience community.
The Simons Foundation is funding projects (2017 – present) that directly address individual labs needs with respect to adopting NWB2.0, developing needed tools in NWB:N, and lowering barriers to use.
The National Institutes of Health, through project 1R24MH116922, funded Oliver Rübel (Lawrence Berkeley National Laboratory) and Lydia Ng (Allen Institute for Brain Science) to continue development of the NWB data format and software ecosystem to enable standardization, sharing, and reuse of neurophysiology data and analyses, enhancing discovery and reproducibility. This funding is part of the NIH’s BRAIN Initiative support to develop standards.(September 2018-May 2020). For updates on this project see our Progress Reports page.
The National Institutes of Health, through project 1R44MH115731, funded William Schroeder (Kitware, Inc.) to create software tools to browse, process, analyze, and visualize NWB data. This funding is part of the NIH’s BRAIN Initiative Small Business Innovation Research (SBIR) grant program. (July 2017-June 2020).
The National Institutes of Health, through project 1R24MH117295, funded Satrajit Ghosh (Massachusetts Institute of Technology) and Yaroslav Halchenko (Center for Open Neuroscience) to create the DANDI archive for Neurophysiology Data. DANDI will:
- Provide a cloud platform for versioned neurophysiology data storage for the purposes of collaboration, archiving, and preservation.
- Provide easy to use tools for neurophysiology data submission and access in the archive
- Facilitate adoption of NWB via standardized applications for data ingestion, visualization and processing.
The Kavli Foundation provided support (2016-2018) to Kristofer Bouchard at the Lawrence Berkeley National Lab for the continued development of the NWB 2.0 data format by creating a modern software architecture and high-performance computing (HPC) enabled data analysis tools utilizing NWB formatted data.