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On analysis of inputs triggering large nonlinear neural responses Slow-fast dynamics in the Wendling neural mass model

机译:温德林神经质量模型中触发大型非线性神经反应的输入的分析慢速动力学

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Many applications in neuroscience, such as electrical and magnetic stimulation, can be modelled as short transient input to non-linear dynamical systems. In excitable systems, small input yields more or less linear responses, while for increasing stimulation strength large non-linear responses may show up suddenly. A challenging task is to determine the transition between the two different response types.In this work we consider such a transition between normal and pathological responses in a model of coupled Wendling neural masses as we encountered in a previous study. First, the different timescales of inhibition in this model allow a slow-fast analysis. This reveals two different dynamical regimes for the systems' response. Second, the two response types are separated by a high-dimensional stable manifold of a saddle slow manifold. Large pathological responses appear if the fast subsystem escapes from this manifold to another attractor. The typical fast oscillations seen during the pathological responses are explained by the bifurcation diagram of the fast subsystem. Under normal conditions these oscillations are suppressed by slow inhibition. External stimulation temporarily releases the fast subsystem from this slow inhibition. The critical response can be formulated as a boundary value problem with one free parameter and can be used to study the dependency of the transition between the two response types upon the system parameters. (C) 2019 Elsevier B.V. All rights reserved.
机译:可以将神经科学中的许多应用(例如电刺激和磁刺激)建模为非线性动力系统的短瞬态输入。在可激励系统中,小的输入会产生或多或少的线性响应,而为了增加刺激强度,可能会突然出现大的非线性响应。一项艰巨的任务是确定两种不同反应类型之间的转换。在这项工作中,我们考虑了在先前的研究中遇到的温德林耦合神经质耦合模型中正常反应与病理反应之间的这种转换。首先,此模型中抑制的不同时间尺度允许进行慢速快速分析。这揭示了系统响应的两种不同的动力学机制。其次,两个响应类型由鞍形慢歧管的高维稳定歧管分隔。如果快速子系统从该歧管逃逸到另一个吸引子,则会出现较大的病理反应。快速子系统的分叉图解释了在病理反应期间出现的典型快速振荡。在正常情况下,通过缓慢抑制可以抑制这些振荡。外部刺激从这种缓慢的抑制作用中暂时释放了快速子系统。临界响应可以表述为具有一个自由参数的边值问题,并且可以用于研究两种响应类型之间的过渡对系统参数的依赖性。 (C)2019 Elsevier B.V.保留所有权利。

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