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首页> 外文期刊>Physical Review X >Interacting Turing-Hopf Instabilities Drive Symmetry-Breaking Transitions in a Mean-Field Model of the Cortex: A Mechanism for the Slow Oscillation
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Interacting Turing-Hopf Instabilities Drive Symmetry-Breaking Transitions in a Mean-Field Model of the Cortex: A Mechanism for the Slow Oscillation

机译:相互作用的Turing-Hopf不稳定性驱动皮层平均场模型中的对称断裂跃迁:一种缓慢振荡的机制

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Electrical recordings of brain activity during the transition from wake to anesthetic coma show temporal and spectral alterations that are correlated with gross changes in the underlying brain state. Entry into anesthetic unconsciousness is signposted by the emergence of large, slow oscillations of electrical activity (?1??Hz) similar to the slow waves observed in natural sleep. Here we present a two-dimensional mean-field model of the cortex in which slow spatiotemporal oscillations arise spontaneously through a Turing (spatial) symmetry-breaking bifurcation that is modulated by a Hopf (temporal) instability. In our model, populations of neurons are densely interlinked by chemical synapses, and by interneuronal gap junctions represented as an inhibitory diffusive coupling. To demonstrate cortical behavior over a wide range of distinct brain states, we explore model dynamics in the vicinity of a general-anesthetic-induced transition from “wake” to “coma.” In this region, the system is poised at a codimension-2 point where competing Turing and Hopf instabilities coexist. We model anesthesia as a moderate reduction in inhibitory diffusion, paired with an increase in inhibitory postsynaptic response, producing a coma state that is characterized by emergent low-frequency oscillations whose dynamics is chaotic in time and space. The effect of long-range axonal white-matter connectivity is probed with the inclusion of a single idealized point-to-point connection. We find that the additional excitation from the long-range connection can provoke seizurelike bursts of cortical activity when inhibitory diffusion is weak, but has little impact on an active cortex. Our proposed dynamic mechanism for the origin of anesthetic slow waves complements—and contrasts with—conventional explanations that require cyclic modulation of ion-channel conductances. We postulate that a similar bifurcation mechanism might underpin the slow waves of natural sleep and comment on the possible consequences of chaotic dynamics for memory processing and learning.
机译:从苏醒到麻醉性昏迷过渡期间大脑活动的电记录显示出时间和频谱变化,这些变化与潜在的大脑状态的总体变化有关。类似于自然睡眠中观察到的缓慢波一样,电活动的大而缓慢的振荡(?1?Hz)的出现预示着进入麻醉性昏迷状态。在这里,我们介绍了一个皮质的二维平均场模型,其中缓慢的时空振荡通过由Hopf(时间)不稳定性调制的图灵(空间)对称性破坏分叉自发地出现。在我们的模型中,神经元群体通过化学突触和神经元间隙连接紧密相连,神经间隙间隙连接表现为抑制性扩散耦合。为了证明大脑皮层行为在各种不同的大脑状态中的表现,我们探索了全身麻醉药从“觉醒”到“昏迷”过渡过程中的模型动力学。在该区域,系统处于codimension-2点,图灵和Hopf不稳定性同时存在。我们将麻醉建模为抑制扩散的适度降低,以及抑制性突触后反应的增加,从而产生一种昏迷状态,其特征是出现了低频振荡,其时空动力学是混乱的。通过包含单个理想的点对点连接来探究远程轴突白质连接的影响。我们发现,当抑制性扩散较弱时,远程连接产生的额外兴奋会激发出癫痫样的皮层活动,但对活动皮层的影响很小。我们提出的用于麻醉慢波起源的动力学机制补充了传统解释,并与之形成对比,传统解释要求对离子通道电导进行循环调制。我们假设类似的分叉机制可能会支撑自然睡眠的慢波,并评论混沌动力学对记忆处理和学习的可能后果。

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