The Neurodata Without Borders (NWB) team is holding a tutorial on the DANDI Archive and NWB data standard and on using PyNWB and MatNWB at the COSYNE 2023 tutorial session.
The DANDI Archive now has 100+ publicly available neurophysiology datasets stored using the NWB data standard.
The NWB project is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy-barrier to applying data analytics both within and across labs. NWB is more than just a file format but it defines an ecosystem of tools, methods, and standards for storing, sharing, and analyzing complex neurophysiology data.
At this tutorial, we’ll teach you how to:
find relevant data on the DANDI Archive and use the DANDI compute resources
stream NWB data from DANDI and read an NWB file in Python and MATLAB
process NWB data using popular tools such as SpikeInterface and suite2p
analyze NWB data using tools such as Pynapple, SSM, or your own scripts
Bring your laptop to work along with the demonstration. To get familiar with NWB and DANDI prior to attending, please refer to this documentation.
There is NO additional fee to attend. When registering for the main meeting, select the Dandi Archive for Neurophysiology Data and the Neurodata Without Borders Data Standard Tutorial.
8:00 - 8:30: Introduction to the NWB data standard and DANDI Archive
8:30 - 8:55: How to find relevant data on the DANDI archive and use the DANDI Hub
8:55 - 9:00: Break
9:00 - 9:20: How to read and explore an NWB file in Python and MATLAB
9:20 - 9:50: How to analyze NWB data using popular data processing and visualization tools
using SpikeInterface to sort raw extracellular electrophysiology recording data streamed from DANDI & write the output back to NWB
storing DeepLabCut and SLEAP pose estimation data in NWB
using calcium imaging analysis tools, such as CaImAn and suite2p to process and segment raw imaging data and write the output to NWB
If you attended the tutorial, please fill out this 2-minute survey to give us feedback on what your data needs are and how did this tutorial go for you. Thank you.