Robust design of polyrhythmic neural circuits.
Robust design of polyrhythmic neural circuits.
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DOI：
10.1103/physreve.90.022715
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发表时间：
2014-08
期刊：
影响因子：
--
通讯作者：
J. Schwabedal;A. Neiman;A. Shilnikov
中科院分区：
文献类型：
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作者：
J. Schwabedal;A. Neiman;A. Shilnikov
神经回路图案产生共存的节奏模式被视为多功能神经元网络的积木。我们研究了这种抑制性模型神经元基序的鲁棒性，以在随机扰动下可靠地维持爆发性多节律。在没有噪声的情况下，每个共存节律的指数稳定性随着突触耦合的加强而增加，从而指示增加的鲁棒性。相反，在添加噪声后，我们发现，如果耦合强度增加超过临界值，噪声引起的节奏切换加剧，这表明鲁棒性降低。我们分析了这种随机心律失常，并制定了一个通用的描述其动力学机制。基于我们的机制的见解，我们展示了如何平衡神经元动力学和网络耦合的生理参数，以提高节奏对噪声的鲁棒性。我们的研究结果适用于广泛的弛豫振荡器网络，包括Fitzhugh-Nagumo和其他Hodgkin-Huxley型网络。
Neural circuit motifs producing coexistent rhythmic patterns are treated as building blocks of multifunctional neuronal networks. We study the robustness of such a motif of inhibitory model neurons to reliably sustain bursting polyrhythms under random perturbations. Without noise, the exponential stability of each of the coexisting rhythms increases with strengthened synaptic coupling, thus indicating an increased robustness. Conversely, after adding noise we find that noise-induced rhythm switching intensifies if the coupling strength is increased beyond a critical value, indicating a decreased robustness. We analyze this stochastic arrhythmia and develop a generic description of its dynamic mechanism. Based on our mechanistic insight, we show how physiological parameters of neuronal dynamics and network coupling can be balanced to enhance rhythm robustness against noise. Our findings are applicable to a broad class of relaxation-oscillator networks, including Fitzhugh-Nagumo and other Hodgkin-Huxley-type networks.