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神经场理论中的神经爆发指数。

Neural field theory of neural avalanche exponents.

机构信息

School of Physics, The University of Sydney, Sydney, New South Wales, 2006, Australia.

Center of Excellence for Integrative Brain Function, The University of Sydney, Sydney, New South Wales, 2006, Australia.

出版信息

Biol Cybern. 2021 Jun;115(3):237-243. doi: 10.1007/s00422-021-00875-9. Epub 2021 May 3.

DOI:10.1007/s00422-021-00875-9
PMID:33939016
Abstract

The power-law exponents of observed size and lifetime distributions of near-critical neural avalanches are calculated from neural field theory using diagrammatic methods. This brings neural avalanches within the ambit of neural field theory, which has also previously explained near-critical 1/f spectra and many other observed features of neural activity. This strengthens the case for near-criticality of the brain and opens the way for these other phenomena to be interrelated with avalanches and their dynamics.

摘要

运用图表方法,从神经场理论出发,计算出近临界神经爆发的观测大小和寿命分布的幂律指数。这使得神经爆发处于神经场理论的范围之内,该理论此前还解释了近临界 1/f 谱和许多其他观察到的神经活动特征。这进一步证明了大脑的近临界性,并为这些其他现象与爆发及其动力学相关联开辟了道路。

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The scale-invariant, temporal profile of neuronal avalanches in relation to cortical γ-oscillations.神经元爆发的标度不变的时间特征与皮层γ振荡的关系。
Sci Rep. 2019 Nov 11;9(1):16403. doi: 10.1038/s41598-019-52326-y.
2
Second type of criticality in the brain uncovers rich multiple-neuron dynamics.大脑中的第二种临界状态揭示了丰富的多神经元动力学。
Proc Natl Acad Sci U S A. 2019 Jun 25;116(26):13051-13060. doi: 10.1073/pnas.1818972116. Epub 2019 Jun 12.
3
Determination of effective brain connectivity from activity correlations.
与神经波和血液动力学波传播子相关的积分和级数。
R Soc Open Sci. 2021 Dec 1;8(12):211562. doi: 10.1098/rsos.211562. eCollection 2021 Dec.
从活动相关性中确定有效的大脑连接。
Phys Rev E. 2019 Apr;99(4-1):042404. doi: 10.1103/PhysRevE.99.042404.
4
Physical brain connectomics.物理脑连接组学。
Phys Rev E. 2019 Jan;99(1-1):012421. doi: 10.1103/PhysRevE.99.012421.
5
Simple unified view of branching process statistics: Random walks in balanced logarithmic potentials.分支过程统计的简单统一观点:平衡对数势中的随机游走。
Phys Rev E. 2017 Mar;95(3-1):032115. doi: 10.1103/PhysRevE.95.032115. Epub 2017 Mar 7.
6
Phase transitions and self-organized criticality in networks of stochastic spiking neurons.随机发放脉冲的神经元网络中的相变与自组织临界性
Sci Rep. 2016 Nov 7;6:35831. doi: 10.1038/srep35831.
7
Efficient codes and balanced networks.高效编码与均衡网络。
Nat Neurosci. 2016 Mar;19(3):375-82. doi: 10.1038/nn.4243.
8
Scale-invariant neuronal avalanche dynamics and the cut-off in size distributions.尺度不变性神经元雪崩动力学与大小分布的截止
PLoS One. 2014 Jun 13;9(6):e99761. doi: 10.1371/journal.pone.0099761. eCollection 2014.
9
Brain organization into resting state networks emerges at criticality on a model of the human connectome.大脑组织成静息状态网络的出现是在人类连接组模型的临界点上。
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Neuronal avalanches in the resting MEG of the human brain.人类大脑静息态 MEG 中的神经元爆发。
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