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Dynamics of a hybrid system of a brain neural network and an artificial nonlinear oscillator

机译:脑神经网络和人工非线性振荡器混合系统的动力学

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摘要

In the brain, many functional modules interact with each other to execute complex information processing. Understanding the nature of these interactions is necessary for understanding how the brain functions. In this study, to mimic interacting modules in the brain, we constructed a hybrid system mutually coupling a hippocampal CA3 network as an actual brain module and a radial isochron clock (RIC) simulated by a personal computer as an artificial module. Return map analysis of the CA3-RIC system's dynamics showed the mutual entrainment and complex dynamics dependent on the coupling modes. The phase response curve of CA3 was modeled regarding the CA3 as a nonlinear oscillator. Using the phase response curves of CA3 and RIG, we reconstructed return maps of the hybrid system's dynamics. Although the reconstructed return maps almost agreed with the experimental data, there were deviations dependent on the coupling mode. In particular, we noted that the deviation was smaller under the bidirectional coupling conditions than during the one-way coupling from RIC to CA3. These results suggest that brain modules may flexibly change their dynamical properties through interaction with other modules. (C) 2000 Elsevier Science Ireland Ltd. All rights reserved. [References: 11]
机译:在大脑中,许多功能模块相互交互以执行复杂的信息处理。了解这些相互作用的本质对于了解大脑的功能非常必要。在这项研究中,为了模拟大脑中的交互模块,我们构建了一个混合系统,将海马CA3网络作为实际的大脑模块与由个人计算机模拟的径向等时时钟(RIC)相互耦合。对CA3-RIC系统动力学的返回图分析表明,相互耦合和复杂动力学取决于耦合模式。将CA3作为非线性振荡器,对CA3的相位响应曲线进行建模。使用CA3和RIG的相位响应曲线,我们重构了混合系统动力学的返回图。尽管重建后的返回图几乎与实验数据一致,但仍存在取决于耦合模式的偏差。特别是,我们注意到,在双向耦合条件下,该偏差比从RIC到CA3的单向耦合期间的偏差小。这些结果表明,大脑模块可以通过与其他模块的交互来灵活地改变其动力学特性。 (C)2000 Elsevier Science Ireland Ltd.保留所有权利。 [参考:11]

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