The log-dynamic brain: how skewed distributions affect network operations.

The log-dynamic brain: how skewed distributions affect network operations.
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DOI:
10.1038/nrn3687
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发表时间:
2014-04
影响因子:
34.7
通讯作者:
Mizuseki, Kenji
Mizuseki, Kenji
中科院分区:
医学1区
文献类型:
--
作者:
Buzsaki, Gyoergy;Mizuseki, Kenji

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我们经常假设大脑功能和结构参数的变量--如突触重量、单个神经元的放电率、神经群体的同步放电、神经元之间突触接触的数量和树突终扣的大小--具有钟形分布。然而,在大脑的许多生理和解剖水平上,许多参数的分布实际上是严重偏斜的,具有厚尾,这表明偏斜(通常为对数正态)分布是结构和功能性大脑组织的基础。这种见解不仅对我们应该如何收集和分析数据有影响,它还可以帮助我们理解从突触到认知的不同水平的偏斜分布是如何相互关联的。
We often assume that the variables of functional and structural brain parameters — such as synaptic weights, the firing rates of individual neurons, the synchronous discharge of neural populations, the number of synaptic contacts between neurons and the size of dendritic boutons — have a bell-shaped distribution. However, at many physiological and anatomical levels in the brain, the distribution of numerous parameters is in fact strongly skewed with a heavy tail, suggesting that skewed (typically lognormal) distributions are fundamental to structural and functional brain organization. This insight not only has implications for how we should collect and analyse data, it may also help us to understand how the different levels of skewed distributions — from synapses to cognition — are related to each other.
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