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Differences between morphological and electrophysiological retinal ganglion cell classes

机译:形态和电生理性视网膜神经节细胞类型之间的差异

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Retinal prostheses work by delivering electrical pulses to the surviving retinal neurons. A pattern of electrical stimulation can generate a perception of vision in blind patients. To improve efficacy of retinal implants, it is important to understand how different classes of retinal neurons respond to electrical stimulation and if a classification can be made based on the electrophysiological properties of neurons. We use previously recorded patch clamp data from retinal ganglion cells classified into morphological classes (A,B,C, D) and functional types (ON, OFF, ON-OFF). We use a machine learning technique to separate data based on the recorded electrophysiological parameters. Results show that the clusters discovered using the machine learning technique do not correspond to the morphological or functional classes used by neuroscientists.
机译:视网膜假体通过向存活的视网膜神经元传递电脉冲来工作。电刺激的模式可以在盲人患者中产生视觉感知。为了提高视网膜植入物的功效,重要的是要了解不同类别的视网膜神经元对电刺激的反应以及是否可以基于神经元的电生理特性进行分类。我们使用以前记录的来自视网膜神经节细胞的膜片钳数据,这些数据被分类为形态学类别(A,B,C,D)和功能类型(ON,OFF,ON-OFF)。我们使用机器学习技术根据记录的电生理参数来分离数据。结果表明,使用机器学习技术发现的簇与神经科学家使用的形态或功能类别不符。

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