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起搏器与节律产生的网络机制:合作与竞争。

Pacemaker and network mechanisms of rhythm generation: cooperation and competition.

作者信息

Ivanchenko Mikhail V, Selverston Allen I, Rabinovich Mikhail I

机构信息

Department of Applied Mathematics, University of Leeds, Leeds LS2 9JT, UK.

出版信息

J Theor Biol. 2008 Aug 7;253(3):452-61. doi: 10.1016/j.jtbi.2008.04.016. Epub 2008 Apr 26.

Abstract

The origin of rhythmic activity in brain circuits and CPG-like motor networks is still not fully understood. The main unsolved questions are (i) What are the respective roles of intrinsic bursting and network based dynamics in systems of coupled heterogeneous, intrinsically complex, even chaotic, neurons? (ii) What are the mechanisms underlying the coexistence of robustness and flexibility in the observed rhythmic spatio-temporal patterns? One common view is that particular bursting neurons provide the rhythmogenic component while the connections between different neurons are responsible for the regularisation and synchronisation of groups of neurons and for specific phase relationships in multi-phasic patterns. We have examined the spatio-temporal rhythmic patterns in computer-simulated motif networks of H-H neurons connected by slow inhibitory synapses with a non-symmetric pattern of coupling strengths. We demonstrate that the interplay between intrinsic and network dynamics features either cooperation or competition, depending on three basic control parameters identified in our model: the shape of intrinsic bursts, the strength of the coupling and its degree of asymmetry. The cooperation of intrinsic dynamics and network mechanisms is shown to correlate with bistability, i.e., the coexistence of two different attractors in the phase space of the system corresponding to different rhythmic spatio-temporal patterns. Conversely, if the network mechanism of rhythmogenesis dominates, monostability is observed with a typical pattern of winnerless competition between neurons. We analyse bifurcations between the two regimes and demonstrate how they provide robustness and flexibility to the network performance.

摘要

脑回路和类中枢模式发生器运动网络中节律性活动的起源仍未完全明确。主要未解决的问题包括:(i)在耦合的异质性、内在复杂性甚至混沌的神经元系统中,内在爆发和基于网络的动力学各自发挥着什么作用?(ii)在观察到的节律性时空模式中,稳健性和灵活性共存的潜在机制是什么?一种普遍观点认为,特定的爆发神经元提供节律生成成分,而不同神经元之间的连接负责神经元群的规整和同步以及多相模式中的特定相位关系。我们研究了通过具有非对称耦合强度模式的慢速抑制性突触连接的H-H神经元计算机模拟基序网络中的时空节律模式。我们证明,内在动力学和网络动力学之间的相互作用表现为合作或竞争,这取决于我们模型中确定的三个基本控制参数:内在爆发的形状、耦合强度及其不对称程度。内在动力学和网络机制的合作与双稳态相关,即在系统相空间中对应于不同节律性时空模式的两种不同吸引子的共存。相反,如果节律生成的网络机制占主导,则会观察到单稳态,神经元之间存在典型的无胜者竞争模式。我们分析了两种状态之间的分岔,并展示了它们如何为网络性能提供稳健性和灵活性。

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