R24 - Ghosh 1R24MH117295-01A1

DANDI: Distributed Archives for Neurophysiology Data Integration

DANDI is a Web platform for scientists to share, collaborate, and process data from cellular neurophysiology experiments. DANDI works with BICCN and other BRAIN Initiative awardees to curate data using community data standards such as NWB and BIDS, and to make data and software for cellular neurophysiology FAIR (Findable, Accessible, Interoperable, and Reusable). DANDI will store electrical and optical cellular neurophysiology recordings and associated MRI and/or optical imaging data. DANDI will provide:

  • A cloud platform for neurophysiology data storage for the purposes of collaboration and dissemination of data.
  • Easy to use tools for neurophysiology data submission, visualization, and access in the archive.
  • Standardized applications for data ingestion, visualization and processing, which facilitate adoption of NWB and other standards.

These data will help scientists uncover and understand cellular level mechanisms of brain function. Scientists will study the formation of neural networks, how cells and networks enable functions such as learning and memory, and how these functions are disrupted in neurological disorders.

Project Leadership

Satrajit S. Ghosh, Ph.D. (Multiple Principal Investigator)
Principal Research Scientist, McGovern Institute for Brain Research
Assistant Professor, Department of Otolaryngology – Head and Neck Surgery
Massachusetts Institute of Technology, Cambridge, MA, USA
Harvard Medical School, Boston, MA, USA


Yaroslav O. Halchenko, Ph.D. (Multiple Principal Investigator)
Research Associate Professor, Psychological and Brain Sciences
Adjunct Research Associate Professor, Computer Science
Dartmouth College, Hanover, NH, USA


Michael Grauer (Co-Investigator)
Technical Leader
Kitware, Inc.


Ben Dichter, Ph.D. (Consultant, Community Liaison)
Ben Dichter Consulting, LLC


Matt van der Meer, Ph.D. (Co-Investigator)
Assistant Professor, Psychological and Brain Sciences
Dartmouth College, Hanover, NH, USA


Mark Harnett, Ph.D. (Co-Investigator)
Assistant Professor, Department Of Brain & Cognitive Sciences
Massachusetts Institute of Technology, Cambridge, MA, USA


Jakob Voigts, Ph.D. (Co-Investigator)
Postdoctoral Fellow, Department Of Brain & Cognitive Sciences
Massachusetts Institute of Technology, Cambridge, MA, USA

Project Data Types

  • Cellular neurophysiology data including electrical and optical recording; any associated MRI and/or optical imaging data:
    • HDF - Hierarchical Data Format. HDF supports an unlimited variety of datatypes, and is designed for flexible, efficient I/O and for high volume and complex data.
    • NWB - Neurodata Without Borders. The NWB file specification can capture the entirety of heterogeneous data representing an experiment and is built on top of HDF.
    • NWB:N - NWB:Neurophysiology. NWB-N is a common file format that accommodates a wide variety of neurophysiology data as well as complex metadata related to stimulus and behavior. This is being developed under BRAIN award 1R24MH116922-01.
    • BIDS - Brain Imaging Data Structure A specification for a file system layout and associated metadata of neuroimaging (MRI, EEG, MEG, iEEG, eCOG) data. The specification enables human readability and accessibility of the metadata in a filesystem. BIDS is an INCF endorsed standard.
    • NIDM - Neuro Imaging Data Model. A W3C-PROV based specification for capturing experimental representation, workflow specification and execution, and analysis results for neuroimaging. Stitches metadata of objects through a directed graph model. BIDS and NIDM complement each other.

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