The Neurodata without Borders – Neurophysiology initiative is a one-year project to produce a unified data format for cellular-based, neurophysiology data based on representative use cases initially from four laboratories – the Buzsaki group at NYU, the Svoboda group at Janelia Farm, the Meister group at Caltech, and the Allen Institute for Brain Science in Seattle. This ongoing one-year project was initiated by the Kavli Foundation and is supported by Kavli, GE, Janelia Farm, Allen Brain Institute and the INCF. The goal is to develop a common, integrated data format which is sufficiently flexible and extensible to incorporate present and future electrophysiological and optical physiology data (i.e., cellular imaging) and to include complex metadata related to stimuli and behavior.
More specifically the format will encompass:
- time series data (in particular voltages)
- 5d images (fluorescence channels, x,y,z,t)
- image sequences/video for behavioral analysis
- neuronal events (spikes, calcium transients)
- behavioral events
- stimulus data
- behavioral data
- other metadata required to interpret the experiment
The stored information will include metadata (experimental variables), processed data (e.g. spike times, behavioral events), intermediate level data (e.g. local field potential, spike waveforms, position data), and wide-band raw data for enabling reproducibility and cross-validation. The metadata will be based on an expansible, yet controlled vocabulary, using public neuro-ontologies NIF – NEUROLEX (neurolex.org). The HDF5 standard is a strong candidate for a structured data container, likely to be chosen as an element of the new common data format.
The NWB-CN project started in August 2014 and has three stages, each scheduled to last four months. Stage 1 is to: gather example data sets and making them available at CRCNS.org; develop requirements documents for the data sets; and to define metrics to evaluate performance of various data formats. Stage 2 is to invite proposals from data model designers, vendors of data formats, and developers to propose formats for storing data based on the example data sets; and to select a common format. Stage 3 is to develop software to implement and use the common format.