Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA.
Front Neural Circuits. 2013 Jan 18;6:98. doi: 10.3389/fncir.2012.00098. eCollection 2012.
Single neuron feedback control techniques, such as voltage clamp and dynamic clamp, have enabled numerous advances in our understanding of ion channels, electrochemical signaling, and neural dynamics. Although commercially available multichannel recording and stimulation systems are commonly used for studying neural processing at the network level, they provide little native support for real-time feedback. We developed the open-source NeuroRighter multichannel electrophysiology hardware and software platform for closed-loop multichannel control with a focus on accessibility and low cost. NeuroRighter allows 64 channels of stimulation and recording for around US $10,000, along with the ability to integrate with other software and hardware. Here, we present substantial enhancements to the NeuroRighter platform, including a redesigned desktop application, a new stimulation subsystem allowing arbitrary stimulation patterns, low-latency data servers for accessing data streams, and a new application programming interface (API) for creating closed-loop protocols that can be inserted into NeuroRighter as plugin programs. This greatly simplifies the design of sophisticated real-time experiments without sacrificing the power and speed of a compiled programming language. Here we present a detailed description of NeuroRighter as a stand-alone application, its plugin API, and an extensive set of case studies that highlight the system's abilities for conducting closed-loop, multichannel interfacing experiments.
单神经元反馈控制技术,如电压钳位和动态钳位,使我们能够深入了解离子通道、电化学信号和神经动力学。虽然商业上可用的多通道记录和刺激系统常用于研究网络级别的神经处理,但它们对实时反馈的原生支持很少。我们开发了开源的 NeuroRighter 多通道电生理硬件和软件平台,用于闭环多通道控制,重点是可访问性和低成本。NeuroRighter 允许进行 64 个通道的刺激和记录,成本约为 10,000 美元,同时还能够与其他软件和硬件集成。在这里,我们对 NeuroRighter 平台进行了重大改进,包括重新设计的桌面应用程序、允许任意刺激模式的新刺激子系统、用于访问数据流的低延迟数据服务器,以及用于创建可作为插件程序插入 NeuroRighter 的闭环协议的新应用程序编程接口 (API)。这大大简化了复杂实时实验的设计,而不会牺牲编译编程语言的功能和速度。在这里,我们详细介绍了作为独立应用程序的 NeuroRighter、其插件 API 以及一系列广泛的案例研究,这些案例研究突出了该系统进行闭环、多通道接口实验的能力。