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

被引:650
作者
Buzsaki, Gyoergy [1 ,2 ]
Mizuseki, Kenji [1 ,3 ]
机构
[1] NYU, Inst Neurosci, Langone Med Ctr, New York, NY 10016 USA
[2] NYU, Ctr Neural Sci, New York, NY 10003 USA
[3] Allen Inst Brain Sci, Seattle, WA 98103 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
COMPARTMENTALIZED DENDRITIC PLASTICITY; LONG-TERM DYNAMICS; RAT BARREL CORTEX; FIRING RATES; PYRAMIDAL CELLS; NEURONAL OSCILLATIONS; SYNAPTIC CONNECTIONS; THETA OSCILLATIONS; CORTICAL-NEURONS; REPRESENTATION;
D O I
10.1038/nrn3687
中图分类号
Q189 [神经科学];
学科分类号
071006 [神经生物学];
摘要
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.
引用
收藏
页码:264 / 278
页数:15
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