Collaborating and sharing data in epilepsy research.
Collaborating and sharing data in epilepsy research.
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DOI：
10.1097/wnp.0000000000000159
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
Schulze-Bonhage A
中科院分区：
文献类型：
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作者：
Wagenaar JB;Worrell GA;Ives Z;Dümpelmann M;Litt B;Schulze-Bonhage A
技术进步正在极大地推进癫痫的转化研究。神经生理学、成像和元数据现在在大多数中心都以数字方式记录，从而能够进行定量分析。使用这些数据的基础和转化研究机会正在爆炸，但学术和资助文化阻碍了这种潜力的实现。如果能够组织协作来消化这些“大神经数据”，那么对癫痫网络、抗癫痫设备和生物标志物的研究将迅速取得进展。更高的时间和空间分辨率数据正在推动对新型多维可视化和分析工具的需求。推动计算机科学创新的众包科学，如果不是因为资金、归属和缺乏标准数据格式和平台的竞争，可以很容易地为这些任务调动起来。随着这些努力的成熟，有很大的机会通过数据共享来推进癫痫研究，并增加国际研究界之间的合作。
Technological advances are dramatically advancing translational research in Epilepsy. Neurophysiology, imaging and meta-data are now recorded digitally in most centers, enabling quantitative analysis. Basic and translational research opportunities to use these data are exploding, but academic and funding cultures a preventing this potential from being realized. Research on epileptogenic networks, anti-epileptic devices and biomarkers could progress rapidly, if collaborative efforts to digest this “big neuro data” could be organized. Higher temporal and spatial resolution data are driving the need for novel multi-dimensional visualization and analysis tools. Crowd-sourced science, the same that drives innovation in computer science, could easily be mobilized for these tasks, were it not for competition for funding, attribution and lack of standard data formats and platforms. As these efforts mature, there is a great opportunity to advance Epilepsy research through data sharing, and increase collaboration between within the international research community.