Choi Myoung-Hwan, Ahn Jungryul, Park Dae Jin, Lee Sang Min, Kim Kwangsoo, Cho Dong-Il Dan, Senok Solomon S, Koo Kyo-In, Goo Yong Sook
Department of Biomedical Engineering, University of Ulsan, Ulsan, Korea.
J Neural Eng. 2017 Feb;14(1):016017. doi: 10.1088/1741-2552/aa5646. Epub 2017 Jan 3.
Direct stimulation of retinal ganglion cells in degenerate retinas by implanting epi-retinal prostheses is a recognized strategy for restoration of visual perception in patients with retinitis pigmentosa or age-related macular degeneration. Elucidating the best stimulus-response paradigms in the laboratory using multielectrode arrays (MEA) is complicated by the fact that the short-latency spikes (within 10 ms) elicited by direct retinal ganglion cell (RGC) stimulation are obscured by the stimulus artifact which is generated by the electrical stimulator.
We developed an artifact subtraction algorithm based on topographic prominence discrimination, wherein the duration of prominences within the stimulus artifact is used as a strategy for identifying the artifact for subtraction and clarifying the obfuscated spikes which are then quantified using standard thresholding.
We found that the prominence discrimination based filters perform creditably in simulation conditions by successfully isolating randomly inserted spikes in the presence of simple and even complex residual artifacts. We also show that the algorithm successfully isolated short-latency spikes in an MEA-based recording from degenerate mouse retinas, where the amplitude and frequency characteristics of the stimulus artifact vary according to the distance of the recording electrode from the stimulating electrode. By ROC analysis of false positive and false negative first spike detection rates in a dataset of one hundred and eight RGCs from four retinal patches, we found that the performance of our algorithm is comparable to that of a generally-used artifact subtraction filter algorithm which uses a strategy of local polynomial approximation (SALPA).
We conclude that the application of topographic prominence discrimination is a valid and useful method for subtraction of stimulation artifacts with variable amplitudes and shapes. We propose that our algorithm may be used as stand-alone or supplementary to other artifact subtraction algorithms like SALPA.
通过植入视网膜外假体直接刺激退化视网膜中的视网膜神经节细胞，是恢复色素性视网膜炎或年龄相关性黄斑变性患者视觉感知的一种公认策略。在实验室中使用多电极阵列（MEA）来阐明最佳刺激-反应范式很复杂，因为直接刺激视网膜神经节细胞（RGC）所引发的短潜伏期尖峰（10毫秒内）会被电刺激器产生的刺激伪迹所掩盖。
我们开发了一种基于地形突出度判别法的伪迹减法算法，其中刺激伪迹内突出度的持续时间被用作识别要减去的伪迹并澄清被掩盖的尖峰的策略，然后使用标准阈值化对这些尖峰进行量化。
我们发现基于突出度判别的滤波器在模拟条件下表现良好，能在存在简单甚至复杂的残余伪迹时成功分离随机插入的尖峰。我们还表明，该算法在基于MEA的退化小鼠视网膜记录中成功分离出短潜伏期尖峰，其中刺激伪迹的幅度和频率特征会根据记录电极与刺激电极的距离而变化。通过对来自四个视网膜区域的108个RGC数据集的假阳性和假阴性首次尖峰检测率进行ROC分析，我们发现我们算法的性能与使用局部多项式逼近策略（SALPA）的常用伪迹减法滤波器算法相当。
我们得出结论，地形突出度判别法的应用是一种有效且有用的方法，可用于减去具有可变幅度和形状的刺激伪迹。我们提出，我们的算法可单独使用或作为其他伪迹减法算法（如SALPA）的补充。
