Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland.
Nencki Institute of Experimental Biology, Polish Academy of Sciences, ul. Pasteura 3, 02-093 Warszawa, Poland.
Sensors (Basel). 2021 Jun 28;21(13):4423. doi: 10.3390/s21134423.
In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat's brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.
在本文中,我们提出了一种用于同时进行脑电刺激和记录的模块化数据采集(DAQ)系统。该 DAQ 系统旨在与称为 Neurostim-3 的定制专用集成电路(ASIC)和各种市售多电极阵列(MEA)一起使用。该系统最多可以同时控制 512 个独立的双向(即输入-输出)通道。我们深入探讨了硬件和软件架构,并讨论了该系统中协作部分之间的关系。本研究的特别重点是探索高效的软件设计,以便它能够使用标准个人计算机(PC)实时执行所有任务,而无需进行数据预计算,即使对于最苛刻的实验场景也是如此。我们不仅展示了基本的性能指标,还使用该软件对 Neurostim-3 的信号处理能力进行了特征描述(例如,增益线性度、传输带宽),以便了解它在实际应用中处理神经信号的能力。结果表明,Neurostim-3 的每个通道在输入信号幅度的宽范围内都表现出信号增益的线性度。此外,其高通截止频率接近 0.6Hz,使其适合记录局部场电位(LFP)和尖峰脑活动信号。此外,还检查了电流刺激电路在复制复杂模式的能力方面。最后,我们展示了使用我们的系统从活体大鼠大脑实验中获得的数据,这证明我们从未刺激和刺激组织中获得了生理数据。所呈现的结果使我们得出结论,我们的硬件和软件可以有效地协同工作,深入了解大脑如何处理信息。