Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.
Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.
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DOI：
10.1088/1741-2552/ac310a
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发表时间：
2021-11-12
影响因子：
4
通讯作者：
Haussler D
中科院分区：
文献类型：
--
作者：
Voitiuk K;Geng J;Keefe MG;Parks DF;Sanso SE;Hawthorne N;Freeman DB;Currie R;Mostajo-Radji MA;Pollen AA;Nowakowski TJ;Salama SR;Teodorescu M;Haussler D
神经活动代表神经元的功能读数，在广泛的实验中监测变得越来越重要。细胞外记录已成为测量神经活动的强大技术，因为这些方法不会导致被测量细胞的破坏或降解。由于人工监督和昂贵的设备，当前的电生理学方法的实验吞吐量较低。这一瓶颈限制了通过大量长期记录样本可以实现的更广泛的推论。我们开发了 Piphys，这是一种廉价的开源神经生理学记录平台，由硬件和软件组成。它可以通过物联网 (IoT) 协议通过标准 Web 界面轻松访问和控制。我们使用 Raspberry Pi 作为主要处理设备以及 Intan 生物放大器。我们设计了硬件扩展电路板和软件来实现电压采样和用户交互。该独立系统经过初级人类神经元的验证，显示出近实时收集神经活动的可靠性。硬件模块和云软件允许远程控制神经记录实验以及水平可扩展性，从而能够大规模地长期观察发育、组织和神经活动。
Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples. We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols. We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time. The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.