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兴奋和抑制的平衡决定了神经元网络中的 1/f 幂律谱。

Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks.

机构信息

Institute of Computational Physics for Engineering Materials, ETH, Zurich, Switzerland.

Department of Industrial and Information Engineering, University of Campania "Luigi Vanvitelli," INFN sez. Naples, Gr. Coll. Salerno, Aversa(CE), Italy.

出版信息

Chaos. 2017 Apr;27(4):047402. doi: 10.1063/1.4979043.

DOI:10.1063/1.4979043
PMID:28456161
Abstract

The 1/f-like decay observed in the power spectrum of electro-physiological signals, along with scale-free statistics of the so-called neuronal avalanches, constitutes evidence of criticality in neuronal systems. Recent in vitro studies have shown that avalanche dynamics at criticality corresponds to some specific balance of excitation and inhibition, thus suggesting that this is a basic feature of the critical state of neuronal networks. In particular, a lack of inhibition significantly alters the temporal structure of the spontaneous avalanche activity and leads to an anomalous abundance of large avalanches. Here, we study the relationship between network inhibition and the scaling exponent β of the power spectral density (PSD) of avalanche activity in a neuronal network model inspired in Self-Organized Criticality. We find that this scaling exponent depends on the percentage of inhibitory synapses and tends to the value β = 1 for a percentage of about 30%. More specifically, β is close to 2, namely, Brownian noise, for purely excitatory networks and decreases towards values in the interval [1, 1.4] as the percentage of inhibitory synapses ranges between 20% and 30%, in agreement with experimental findings. These results indicate that the level of inhibition affects the frequency spectrum of resting brain activity and suggest the analysis of the PSD scaling behavior as a possible tool to study pathological conditions.

摘要

在电生理信号的功率谱中观察到的 1/f 样衰减,以及所谓的神经元爆发的无标度统计,构成了神经元系统处于临界状态的证据。最近的体外研究表明,临界状态下的爆发动力学对应于兴奋和抑制的某种特定平衡,因此表明这是神经元网络临界状态的基本特征。特别是,缺乏抑制会显著改变自发爆发活动的时间结构,并导致大爆发的异常丰富。在这里,我们研究了网络抑制与爆发活动的功率谱密度 (PSD) 的标度指数 β 之间的关系,这是在受自组织临界启发的神经元网络模型中研究的。我们发现,这个标度指数取决于抑制性突触的百分比,并且当抑制性突触的百分比约为 30%时,趋于 β=1 的值。更具体地说,β接近于 2,即布朗噪声,对于纯兴奋性网络,并且随着抑制性突触的百分比在 20%到 30%之间变化,β 值逐渐降低到[1,1.4]之间的区间内,与实验结果一致。这些结果表明抑制水平会影响静息大脑活动的频谱,并表明分析 PSD 标度行为可能是研究病理状况的一种工具。

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