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一种呈现不规则放电的小脑浦肯野细胞和分子层中间神经元的脉冲网络模型。

A spiking network model of cerebellar Purkinje cells and molecular layer interneurons exhibiting irregular firing.

作者信息

Lennon William, Hecht-Nielsen Robert, Yamazaki Tadashi

机构信息

Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.

Graduate School of Informatics and Engineering, The University of Electro-Communications Chofu, Japan.

出版信息

Front Comput Neurosci. 2014 Dec 1;8:157. doi: 10.3389/fncom.2014.00157. eCollection 2014.

Abstract

While the anatomy of the cerebellar microcircuit is well-studied, how it implements cerebellar function is not understood. A number of models have been proposed to describe this mechanism but few emphasize the role of the vast network Purkinje cells (PKJs) form with the molecular layer interneurons (MLIs)-the stellate and basket cells. We propose a model of the MLI-PKJ network composed of simple spiking neurons incorporating the major anatomical and physiological features. In computer simulations, the model reproduces the irregular firing patterns observed in PKJs and MLIs in vitro and a shift toward faster, more regular firing patterns when inhibitory synaptic currents are blocked. In the model, the time between PKJ spikes is shown to be proportional to the amount of feedforward inhibition from an MLI on average. The two key elements of the model are: (1) spontaneously active PKJs and MLIs due to an endogenous depolarizing current, and (2) adherence to known anatomical connectivity along a parasagittal strip of cerebellar cortex. We propose this model to extend previous spiking network models of the cerebellum and for further computational investigation into the role of irregular firing and MLIs in cerebellar learning and function.

摘要

虽然小脑微回路的解剖结构已得到充分研究,但其如何实现小脑功能仍不清楚。已经提出了许多模型来描述这一机制,但很少有模型强调浦肯野细胞(PKJs)与分子层中间神经元(MLIs)——星状细胞和篮状细胞形成的庞大网络的作用。我们提出了一个由简单脉冲发放神经元组成的MLI-PKJ网络模型,该模型纳入了主要的解剖学和生理学特征。在计算机模拟中,该模型再现了体外观察到的PKJs和MLIs中的不规则发放模式,以及在抑制性突触电流被阻断时向更快、更规则发放模式的转变。在该模型中,PKJ发放之间的时间平均显示与来自MLI的前馈抑制量成正比。该模型的两个关键要素是:(1)由于内源性去极化电流而自发活动的PKJs和MLIs,以及(2)沿小脑皮质矢状旁带遵循已知的解剖学连接。我们提出这个模型是为了扩展先前的小脑脉冲发放网络模型,并进一步通过计算研究不规则发放和MLIs在小脑学习和功能中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b2/4249458/cb64f95315ac/fncom-08-00157-g0001.jpg

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