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Toward Functional Classification of Neuronal Types

机译:走向神经元类型的功能分类

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摘要

How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological, or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on their role in encoding sensory stimuli? Here, theoretical arguments are outlined for how this can be achieved using information theory by looking at optimal numbers of cell types and paying attention to two key properties: correlations between inputs and noise in neural responses. This theoretical framework could help to map the hierarchical tree relating different neuronal classes within and across species.
机译:大脑中有几种类型的神经元?尽管进行了数十年的研究,这个基本的神经科学问题仍未解决。已经基于解剖学,电生理学或分子特性提出了分类方案。但是,不同的方案并不总是彼此一致。这就提出了一个问题,即人们是否可以直接根据神经元的功能对其进行分类。例如,在感觉神经元中,是否可以基于其在编码感觉刺激中的作用设计分类方案?在这里,概述了有关如何使用信息论通过观察最佳细胞类型数量并注意两个关键特性(输入与神经反应中的噪声之间的相关性)的理论论点。这种理论框架可以帮助绘制与物种内部和物种之间的不同神经元类别相关的层次树。

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