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Data-oriented neuron classification from their parts

机译:从其部件取向数据的神经元分类

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The shape of a neuron can reveal many interesting properties about its function. Therefore, organizing neuronal cells into appropriate classes according to their respective shape is a fundamental endeavor in neuroscience. Available online datasets allow new data-oriented approaches to solve such neuroscience problems. Here we analyze the feasibility of classifying neurons according not to their respective wholes, but to its constituent parts. Such a study may reveal interesting insights, including whether parts of the neuronal dendritic arborization preserve proper information about the morphology of the whole neuron. Experimental results using open datasets are reported, thus corroborating our approach.
机译:神经元的形状可以揭示关于其功能的许多有趣的特性。因此,根据其各自的形状将神经元细胞组织成适当的类是神经科学的基本努力。可用的在线数据集允许新的数据导向方法来解决此类神经科学问题。在这里,我们根据各自的惠尔分析了神经元的可行性,而是对其组成部分进行分析。这样的研究可能会揭示有趣的见解,包括神经元树突树突族族的部分是否保留了关于整个神经元的形态的适当信息。报告了使用开放数据集的实验结果,从而证实了我们的方法。

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