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Introduction to Neurodata Without Borders (NWB) for Python users II

The Neurodata Without Borders: Neurophysiology project (NWB:N, https://www.nwb.org/) 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. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB. The community needs to join for es to achieve data standardization in neurophysiology.

 

This course will provide an introduction to NWB and walk through tutorials on how to use NWB software tools to store different types of data in NWB. This part 2 of the course which intended for Python users.  It is recommended that users view Introduction to Neurodata Without Borders (NWB) for MATLAB users I before viewing this course. There is also a version of this course for Python users.

Lessons of this Course
1
6
Duration:
27:18

Learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm

2
7
Duration:
20:29
Speaker:

Learn how to build and share extensions in NWB

3
8
Duration:
25:40
Speaker:

Learn how to build custom APIs for extension

4
9
Duration:
26:50
Speaker:

Learn how to handle writing very large data in PyNWB

5
10
Duration:
44:37

Overview of the CaImAn package, and demonstration of usage with NWB

6
11
Duration:
1:10:28

Overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters

7
12
Duration:
47:15
Speaker:

Overview of the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework