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尖峰、速率、场和混合方法治疗神经元动力学和相互作用。

Spike, rate, field, and hybrid methods for treating neuronal dynamics and interactions.

机构信息

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

出版信息

J Neurosci Methods. 2012 Apr 15;205(2):283-94. doi: 10.1016/j.jneumeth.2012.01.018. Epub 2012 Feb 7.

Abstract

Spike-, rate-, and field-based approaches to neural dynamics are adapted and hybridized to provide new methods of analyzing dynamics of single neurons and large neuronal systems, to elucidate the relationships and intermediate forms between these limiting cases, and to enable faster simulations with reduced memory requirements. At the single-neuron level, the new approaches involve reformulation of dynamics in synapses, dendrites, cell bodies, and axons to enable new types of analysis, longer numerical timesteps, and demonstration that rate-based methods can predict spike times. In multineuron systems, hybrids and intermediates between spike-based and field-based coupling between neurons are used to provide stepping stones between descriptions based on pairwise spike-based interactions between neurons and ones based on neural field-based interactions within and between populations, including arbitrary spatial structure and temporal delays in the connections in general. In particular, a new neuron-in-cell approach is introduced that is a hybrid between neural field theory and spiking-neuron models in analogy to particle-in-cell methods in plasma physics. This approach enables large speedups in computations while preserving spike shapes and times. Various approaches are illustrated numerically for specific cases.

摘要

基于尖峰、速率和场的神经动力学方法被改编和混合,以提供分析单个神经元和大型神经元系统动力学的新方法,阐明这些极限情况之间的关系和中间形式,并实现具有更少内存需求的更快模拟。在单神经元水平上,新方法涉及重新制定突触、树突、细胞体和轴突中的动力学,以实现新类型的分析、更长的数值时间步长,并证明基于速率的方法可以预测尖峰时间。在多神经元系统中,神经元之间基于尖峰和基于场的耦合的混合体和中间体用于提供基于神经元之间基于尖峰的成对相互作用的描述和基于神经元内和神经元间神经场相互作用的描述之间的垫脚石,包括连接中的任意空间结构和时间延迟。特别是,引入了一种新的细胞内神经元方法,它是神经场理论和尖峰神经元模型的混合,类似于等离子体物理学中的粒子在细胞内方法。该方法在保持尖峰形状和时间的同时,大大提高了计算速度。针对特定情况进行了数值说明。

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