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Characterization of individual retinal ganglion cell responses using K-means clustering method

机译:使用K-均值聚类方法表征单个视网膜神经节细胞反应

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摘要

The information to be transmitted along the nervous system is encoded with the rate of fire of the neurons expressing the number of action potentials in a temporal range. Findings from experimental studies in the development of visual prosthetic systems, as a neuroprosthetic device, are of critical importance. The determination of the various working intervals required for the development of electronic units is carried out initially by experiments using animal subjects following acute experiments on human subjects. Current implantable retinal implants generate large volume data which is required to be sorted to simultaneously provide strong neural control signals from each electrode. Spike sorting refers to the process that raw electrophysiological data is transferred to interpretable presentation of neural spikes. The first step in the analysis of neural activity for sorting recorded in vitro from retinal tissue is the detection and isolation of the action potentials to be used for further processing stages. It provides to clarify the understanding of the retinal response to electrical stimulation. In this study, spike activity is detected and isolated using the neural activity recorded from in vitro retina experiment. Next, data is pre-processed and sorted using k-means clustering method to distinguish real spikes. Moreover, Davies-Bouldin index is used to determine optimal separation of spike activity, which efficiently results 4 clusters. One of these clusters refers artifacts caused by electrical stimulation and others are related to real spikes with different properties. It is concluded that neural activity could be successfully sorted and more efficient approaches developed.
机译:沿神经系统传输的信息以表示时间范围内动作电位数量的神经元的发射速率编码。在作为神经修复装置的视觉修复系统的开发中,来自实验研究的发现至关重要。电子设备开发所需的各种工作间隔的确定最初是通过对动物受试者进行急性实验之后,使用动物受试者进行的实验来进行的。当前的可植入视网膜植入物产生大量数据,需要对其进行分类以同时提供来自每个电极的强神经控制信号。尖峰排序是指将原始电生理数据传输到神经尖峰的可解释表示中的过程。在神经活性分析中,从视网膜组织体外记录的分类的第一步是检测和分离用于进一步加工阶段的动作电位。它提供澄清对电刺激的视网膜反应的理解。在这项研究中,使用从体外视网膜实验记录的神经活动检测并分离出刺突活动。接下来,使用k均值聚类方法对数据进行预处理和分类,以区分实际峰值。此外,Davies-Bouldin指数用于确定峰值活动的最佳分离,从而有效地产生4个簇。这些簇之一是指由电刺激引起的伪影,其他簇与具有不同属性的真实尖峰有关。结论是神经活动可以成功地进行分类,开发出更有效的方法。

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