AUTHOR=Takemiya Makoto , Majima Kei , Tsukamoto Mitsuaki , Kamitani Yukiyasu TITLE=BrainLiner: A Neuroinformatics Platform for Sharing Time-Aligned Brain-Behavior Data JOURNAL=Frontiers in Neuroinformatics VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2016.00003 DOI=10.3389/fninf.2016.00003 ISSN=1662-5196 ABSTRACT=

Data-driven neuroscience aims to find statistical relationships between brain activity and task behavior from large-scale datasets. To facilitate high-throughput data processing and modeling, we created BrainLiner as a web platform for sharing time-aligned, brain-behavior data. Using an HDF5-based data format, BrainLiner treats brain activity and data related to behavior with the same salience, aligning both behavioral and brain activity data on a common time axis. This facilitates learning the relationship between behavior and brain activity. Using a common data file format also simplifies data processing and analyses. Properties describing data are unambiguously defined using a schema, allowing machine-readable definition of data. The BrainLiner platform allows users to upload and download data, as well as to explore and search for data from the web platform. A WebGL-based data explorer can visualize highly detailed neurophysiological data from within the web browser, and a data-driven search feature allows users to search for similar time windows of data. This increases transparency, and allows for visual inspection of neural coding. BrainLiner thus provides an essential set of tools for data sharing and data-driven modeling.