基于图谱的神经元相互作用群体中的嵌合态和信息传递

V. J. Márquez-Rodríguez, K. Tucci, M. G. Cosenza
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引用次数: 0

摘要

我们研究了由两个相互作用的、具有类似混沌神经动力学的图群组成的系统中的同步行为和嵌合体状态的出现。我们描述了系统耦合参数空间上的四种集体状态:完全同步、广义同步、嵌合体状态和不连贯。我们量化了嵌合态中两个神经元群之间的信息交换。我们发现,在嵌合体状态下,信息流的方向是明确的,即从非同步群体流向同步群体。在嵌合态中,不连贯神经元群是连贯神经元群的驱动力,这一特征与神经元群的大小或神经元群的分区无关。我们的研究结果有助于深入了解与嵌合态相关的单半球睡眠和癫痫发作等大脑过程中产生的交流机制。
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Chimera states and information transfer in interacting populations of map-based neurons
We investigate the synchronization behavior and the emergence of chimera states in a system of two interacting populations of maps possessing chaotic neural-like dynamics. We characterize four collective states on the space of coupling parameters of the system: complete synchronization, generalized synchronization, chimera states, and incoherence. We quantify the information exchange between the two neuron populations in chimera states. We have found a well-defined direction of the flow of information in chimera states, from the desynchronized population to the synchronized one. The incoherent population functions as a driver of the coherent neuron population in a chimera state. This feature is independent of the population sizes or population partitions. Our results yield insight into the communication mechanisms arising in brain processes such as unihemispheric sleep and epileptic seizures that have been associated to chimera states.
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