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多层休伯-布劳恩(HB)神经元模型中障碍物诱导的螺旋波

Obstacle induced spiral waves in a multilayered Huber-Braun (HB) neuron model.

作者信息

Rajagopal Karthikeyan, Ramadoss Janarthanan, He Shaobo, Duraisamy Prakash, Karthikeyan Anitha

机构信息

Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, India.

Centre for Artificial Intelligence, Chennai Institute of Technology, Chennai, India.

出版信息

Cogn Neurodyn. 2023 Feb;17(1):277-291. doi: 10.1007/s11571-022-09785-3. Epub 2022 Apr 20.

Abstract

Various dynamical properties of four-dimensional mammalian cold receptor model have been discussed widely in the literature considering noise and temperature as important parameters of discussion. Though various spiking and bursting behaviors of the neuron under various noise and temperature conditions studied for a single neuron, no much discussions have been done on the collective behavior. We investigate the collective behavior of these temperature dependent stochastic neurons and unlike the neuron models when forced by periodic external force there is no wave reentry or spiral waves in the network. Hence, we introduce obstacle in the network and depending on the orientation and size of the introduced obstacle, we could show their effects on the wave reentry in the network. Various significant discussions are produced in this paper to confirm that obstacles placed parallel to the wave entry affects the excitability of the tissues significantly compared to those obstacles place perpendicular. We could also show that those obstacles which are lesser in dimensions doesn't affect the excitabilities and hence doesn't contribute for wave reentry. We introduce a new technique to identify wave reentry and spiral waves using the period of individual nodes is proposed. This technique could help us identify even the lowest of excitability change which cannot be seen when using spatiotemporal snapshots.

摘要

在将噪声和温度作为重要讨论参数的文献中,已经广泛探讨了四维哺乳动物冷感受器模型的各种动力学特性。尽管针对单个神经元研究了其在各种噪声和温度条件下的各种尖峰和爆发行为,但对于集体行为的讨论却不多。我们研究了这些温度依赖性随机神经元的集体行为,与受周期性外力作用时的神经元模型不同,网络中不存在波再入或螺旋波。因此,我们在网络中引入障碍物,并根据引入障碍物的方向和大小,展示它们对网络中波再入的影响。本文进行了各种重要讨论,以证实与垂直放置的障碍物相比,平行于波入射方向放置的障碍物对组织兴奋性的影响更为显著。我们还可以表明,尺寸较小的障碍物不会影响兴奋性,因此不会促成波再入。我们提出了一种利用单个节点的周期来识别波再入和螺旋波的新技术。这项技术可以帮助我们识别即使是使用时空快照时也无法看到的最低兴奋性变化。

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