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タイトル: | Brainliner: A neuroinformatics platform for sharing time-aligned brain-behavior data |
著者: | Takemiya, Makoto Majima, Kei https://orcid.org/0000-0002-2405-4113 (unconfirmed) Tsukamoto, Mitsuaki Kamitani, Yukiyasu https://orcid.org/0000-0002-9300-8268 (unconfirmed) |
著者名の別形: | 神谷, 之康 |
キーワード: | data sharing database search neuroscience neuroinformatics web service machine learning neural decoding |
発行日: | 26-Jan-2016 |
出版者: | Frontiers Media SA |
誌名: | Frontiers in Neuroinformatics |
巻: | 10 |
論文番号: | 3 |
抄録: | 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. |
著作権等: | © 2016 Takemiya, Majima, Tsukamoto and Kamitani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
URI: | http://hdl.handle.net/2433/214302 |
DOI(出版社版): | 10.3389/fninf.2016.00003 |
PubMed ID: | 26858636 |
出現コレクション: | 学術雑誌掲載論文等 |
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