Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome.

ArXiv Pub Date : 2024-05-03
Bryant Avila, Pedro Augusto, Manuel Zimmer, Matteo Serafino, Hernán A Makse
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Abstract

Capturing how the Caenorhabditis elegans connectome structure gives rise to its neuron functionality remains unclear. It is through fiber symmetries found in its neuronal connectivity that synchronization of a group of neurons can be determined. To understand these we investigate graph symmetries and search for such in the symmetrized versions of the forward and backward locomotive sub-networks of the Caenorhabditi elegans worm neuron network. The use of ordinarily differential equations simulations admissible to these graphs are used to validate the predictions of these fiber symmetries and are compared to the more restrictive orbit symmetries. Additionally fibration symmetries are used to decompose these graphs into their fundamental building blocks which reveal units formed by nested loops or multilayered fibers. It is found that fiber symmetries of the connectome can accurately predict neuronal synchronization even under not idealized connectivity as long as the dynamics are within stable regimes of simulations.

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秀丽隐杆线虫连接体中的纤维对称性和簇同步性。
目前尚不清楚秀丽隐杆线虫连接体结构是如何产生其神经元功能的。正是通过在神经元连接中发现的纤维对称性,才能确定一组神经元的同步性。为了理解这些,我们研究了图的对称性,并在秀丽隐杆线虫蠕虫神经元网络的前向和后向机车子网络的对称化版本中寻找这种对称性。使用可用于这些图的常微分方程模拟来验证这些纤维对称性的预测,并与更严格的轨道对称性进行比较。此外,纤维对称性被用来将这些图分解为它们的基本构建块,这些构建块揭示了由嵌套环或多层纤维形成的单元。研究发现,即使在非理想连接的情况下,只要动力学处于稳定的模拟范围内,连接体的纤维对称性也可以准确预测神经元同步。
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