KMID : 0892920200290060433
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Experimental Neurobiology 2020 Volume.29 No. 6 p.433 ~ p.452
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Spike-triggered Clustering for Retinal Ganglion Cell Classification
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Ahn Jung-Ryul
Yoo Yong-Seok Goo Yong-Sook
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Abstract
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Retinal ganglion cells (RGCs), the retina¡¯s output neurons, encode visual information through spiking. The RGC receptive field (RF) represents the basic unit of visual information processing in the retina. RFs are commonly estimated using the spike-triggered average (STA), which is the average of the stimulus patterns to which a given RGC is sensitive. Whereas STA, based on the concept of the average, is simple and intuitive, it leaves more complex structures in the RFs undetected. Alternatively, spike-triggered covariance (STC) analysis provides information on second-order RF statistics. However, STC is computationally cumbersome and difficult to interpret. Thus, the objective of this study was to propose and validate a new computational method, called spike-triggered clustering (STCL), specific for multimodal RFs. Specifically, RFs were fit with a Gaussian mixture model, which provides the means and covariances of multiple RF clusters. The proposed method recovered bipolar stimulus patterns in the RFs of ON-OFF cells, while the STA identified only ON and OFF RGCs, and the remaining RGCs were labeled as unknown types. In contrast, our new STCL analysis distinguished ON-OFF RGCs from the ON, OFF, and unknown RGC types classified by STA. Thus, the proposed method enables us to include ON-OFF RGCs prior to retinal information analysis.
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KEYWORD
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Receptive fields, Retinal ganglion cells, Spike-triggered clustering, Spike-triggered average, Spike-triggered covariance
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