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Neural ensemble communities: Open-source approaches to hardware for large-scale electrophysiology

机译:神经集成社区:大规模电生理学的开源硬件方法

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摘要

One often-overlooked factor when selecting a platform for large-scale electrophysiology is whether or not a particular data acquisition system is “open” or “closed”: that is, whether or not the system’s schematics and source code are available to end users. Open systems have a reputation for being difficult to acquire, poorly documented, and hard to maintain. With the arrival of more powerful and compact integrated circuits, rapid prototyping services, and web-based tools for collaborative development, these stereotypes must be reconsidered. We discuss some of the reasons why multichannel extracellular electrophysiology could benefit from open-source approaches and describe examples of successful community-driven tool development within this field. In order to promote the adoption of open-source hardware and to reduce the need for redundant development efforts, we advocate a move toward standardized interfaces that connect each element of the data processing pipeline. This will give researchers the flexibility to modify their tools when necessary, while allowing them to continue to benefit from the high-quality products and expertise provided by commercial vendors.
机译:选择大规模电生理学平台时,经常被忽略的一个因素是特定的数据采集系统是“开放”还是“封闭”:即该系统的示意图和源代码是否可供最终用户使用。开放系统因难以获取,文档记录差且难以维护而享有盛誉。随着功能更强大,更紧凑的集成电路,快速原型服务以及基于Web的协作开发工具的出现,必须重新考虑这些定型观念。我们讨论了多通道细胞外电生理学可以从开源方法中受益的一些原因,并描述了该领域内成功的社区驱动工具开发的示例。为了促进采用开放源代码硬件并减少对冗余开发工作的需求,我们提倡采用标准化接口来连接数据处理管道的每个元素。这将使研究人员能够在必要时灵活地修改其工具,同时使他们能够继续受益于商业供应商提供的高质量产品和专业知识。

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