Loren Frank’s Howard Hughes Medical Institute (HHMI) lab at UC San Francisco has pioneered a data-sharing framework called Spyglass.
The ambitious framework offers a new way to share large neuroscience datasets and complicated analysis methods. The researchers see Spyglass as a means to move the scientific community toward more effective collaboration.
Frank’s lab collects data from arrays of electrodes in the regions of rat brains that are involved in behavior, learning, and imagination. That data is combined with detailed information on the rats’ behavior in a format called Neurodata Without Borders (NWB).
Spyglass provides software code in Python that allows sharing and analysis of the raw data and also of the results from every step in the complex analysis.