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

被引:28
|
作者
Siegle, Joshua H. [1 ]
Hale, Gregory J. [1 ]
Newman, Jonathan P. [1 ]
Voigts, Jakob [1 ]
机构
[1] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
基金
美国国家科学基金会;
关键词
DENSITY MICROELECTRODE ARRAY; OPTICAL CONTROL; DATA-ACQUISITION; DYNAMICS; TOOLBOX; NEURONS; REPLAY; CODE;
D O I
10.1016/j.conb.2014.11.004
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
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.
引用
收藏
页码:53 / 59
页数:7
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