神经元网络模型中的螺旋波动动力学

IF 2.6 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Diogo L M Souza, Fernando S Borges, Enrique C Gabrick, Lucas E Bentivoglio, Paulo R Protachevicz, Vagner dos Santos, Ricardo L Viana, Ibere L Caldas, Kelly C Iarosz, Antonio M Batista and Jürgen Kurths
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引用次数: 0

摘要

螺旋波是一种空间-时间模式,可在心脏组织、化学振荡器、生态网络和大脑等不同系统中出现。这些波在海龟、大鼠和人类的新皮层中被发现,尤其是在类似睡眠的状态下。虽然它们在认知活动中的功能至今仍鲜为人知,但这些模式与大脑皮层的活动调节有关,并有助于大脑皮层的处理过程。在这项研究中,我们根据锥体神经元的空间分布构建了一个神经元网络层。我们的主要目标是研究局部连通性和耦合强度如何与螺旋波的出现相关联。因此,我们根据局部和全局相序参数,提出了一种能够检测不同波形的可信方法。结果,我们发现连接半径(R)的范围对螺旋波的出现起着至关重要的作用。当 R < 20 µm 时,由于连接数量较少,只能观察到异步活动。耦合强度( )对较高 R 的模式转换有很大影响,在螺旋波和非螺旋波中都能观察到尖峰和脉冲发射模式。最后,我们表明,在某些 R 值下,可以获得波形的双稳态状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spiral wave dynamics in a neuronal network model
Spiral waves are spatial-temporal patterns that can emerge in different systems as heart tissues, chemical oscillators, ecological networks and the brain. These waves have been identified in the neocortex of turtles, rats, and humans, particularly during sleep-like states. Although their functions in cognitive activities remain until now poorly understood, these patterns are related to cortical activity modulation and contribute to cortical processing. In this work, ,we construct a neuronal network layer based on the spatial distribution of pyramidal neurons. Our main goal is to investigate how local connectivity and coupling strength are associated with the emergence of spiral waves. Therefore, we propose a trustworthy method capable of detecting different wave patterns, based on local and global phase order parameters. As a result, we find that the range of connection radius (R) plays a crucial role in the appearance of spiral waves. For R < 20 µm, only asynchronous activity is observed due to small number of connections. The coupling strength ( ) greatly influences the pattern transitions for higher R, where spikes and bursts firing patterns can be observed in spiral and non-spiral waves. Finally, we show that for some values of R and bistable states of wave patterns are obtained.
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来源期刊
Journal of Physics Complexity
Journal of Physics Complexity Computer Science-Information Systems
CiteScore
4.30
自引率
11.10%
发文量
45
审稿时长
14 weeks
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