U.S. research institutes target standard neuroscience data format

Amid all the controversies generated by the big neuroscience initiatives getting underway on either side of the Atlantic, areas of common ground such as the need to standardize and share data have emerged. Now, a group of U.S. research institutions have teamed up to establish a unified data format to facilitate the sharing of information.

Christof Koch

The Allen Institute for Brain Science, California Institute of Technology, New York University School of Medicine, the Howard Hughes Medical Institute and the University of California, Berkeley, are the organizations behind the project. Within one year the collaborators hope to have agreed on a standard for neurophysiology, a subset of neuroscience data used to build models of how the brain works. The availability of data is a constraint on such modeling projects.

"Neuroscientists aren't limited by memory storage anymore; we're limited by our ingenuity, the availability of data and our ability to talk to each other. This pilot program is an effort to help us speak the same language," Allen Institute Chief Scientific Officer Christof Koch said in a statement. Koch and his collaborators are now seeking feedback from the broader neuroscience community ahead of a November hackathon at which researchers will test the format.

Some of the challenges are clear at the outset. As well as storing the electrical and optical recordings of neural activity that make up neurophysiology data, the format must also record the conditions in which the tests were run. Metadata such as the age, sex and species of the test animal is needed to understand the data, but are often lost. The collaborators plan to work with software developers and vendors to overcome the metadata issue and other challenges.

With big neuroscience projects getting underway on both sides of the Atlantic, the collaborators think now is the time to fix the long-standing data standardization problem. "These new initiatives are going to produce masses of data, but if it isn't interchangeable and comparable, it's just not going to be useful," Koch said.

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