Department of Biomedical Engineering, Duke University, Durham, NC, United States of America.
Department of Neurobiology, Duke University School of Medicine, Durham, NC, United States of America.
J Neural Eng. 2024 Jul 9;21(4). doi: 10.1088/1741-2552/ad5762.
Intan Technologies' integrated circuits (ICs) are valuable tools for neurophysiological data acquisition, providing signal amplification, filtering, and digitization from many channels (up to 64 channels/chip) at high sampling rates (up to 30 kSPS) within a compact package (⩽9× 7 mm). However, we found that the analog-to-digital converters (ADCs) in the Intan RHD2000 series ICs can produce artifacts in recorded signals. Here, we examine the effects of these ADC artifacts on neural signal quality and describe a method to detect them in recorded data.We identified two types of ADC artifacts produced by Intan ICs: 1) jumps, resulting from missing output codes, and 2) flatlines, resulting from overrepresented output codes. We identified ADC artifacts in neural recordings acquired with Intan RHD2000 ICs and tested the repeated performance of 17 ICs. With the on-chip digital-signal-processing disabled, we detected the ADC artifacts in each test recording by examining the distribution of unfiltered ADC output codes.We found larger ADC artifacts in recordings using the Intan RHX data acquisition software versions 3.0-3.2, which did not run the necessary ADC calibration command when the inputs to the Intan recording controller were rescanned. This has been corrected in the Intan RHX software version 3.3. We found that the ADC calibration routine significantly reduced, but did not fully eliminate, the occurrence and size of ADC artifacts as compared with recordings acquired when the calibration routine was not run (< 0.0001). When the ADC calibration routine was run, we found that the artifacts produced by each ADC were consistent over time, enabling us to sort ICs by performance.Our findings call attention to the importance of evaluating signal quality when acquiring electrophysiological data using Intan Technologies ICs and offer a method for detecting ADC artifacts in recorded data.
英特丹科技公司的集成电路（IC）是神经生理学数据采集的有价值工具，可在紧凑的封装内（≦9×7 毫米）从多个通道（最多 64 个通道/芯片）以高采样率（高达 30 kSPS）进行信号放大、滤波和数字化。然而，我们发现英特丹 RHD2000 系列 IC 中的模数转换器（ADC）会在记录的信号中产生伪影。在这里，我们检查了这些 ADC 伪影对神经信号质量的影响，并描述了一种在记录数据中检测它们的方法。我们确定了英特丹 IC 产生的两种类型的 ADC 伪影：1）跳变，由缺少输出码引起，2） 平线，由过量的输出码引起。我们在使用英特丹 RHD2000 IC 采集的神经记录中识别出 ADC 伪影，并测试了 17 个 IC 的重复性能。在禁用片上数字信号处理的情况下，我们通过检查未滤波的 ADC 输出码的分布来检测每个测试记录中的 ADC 伪影。我们发现，在使用 Intan RHX 数据采集软件版本 3.0-3.2 进行记录时，ADC 伪影较大，当重新扫描 Intan 记录控制器的输入时，该软件不会运行必要的 ADC 校准命令。在 Intan RHX 软件版本 3.3 中已对此进行了纠正。我们发现，与未运行校准程序时采集的记录相比，ADC 校准程序大大减少了（但并未完全消除）ADC 伪影的发生和大小（<0.0001）。当运行 ADC 校准程序时，我们发现每个 ADC 产生的伪影随时间保持一致，使我们能够根据性能对 IC 进行排序。我们的研究结果提醒人们在使用英特丹科技公司的 IC 采集电生理数据时评估信号质量的重要性，并提供了一种在记录数据中检测 ADC 伪影的方法。
