With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus on how the molecular properties of anesthetic agents lead to the observed macroscopic property that defines the anesthetic state, that is, lack of responsiveness to noxious stimuli. In this paper, we use dynamical system theory to develop a mechanistic mean field model for neural activity to study the abrupt transition from consciousness to unconsciousness as the concentration of the anesthetic agent increases. The proposed synaptic drive firing-rate model predicts the conscious-unconscious transition as the applied anesthetic concentration increases, where excitatory neural activity is characterized by a Poincaré-Andronov-Hopf bifurcation with the awake state transitioning to a stable limit cycle and then subsequently to an asymptotically stable unconscious equilibrium state. Furthermore, we address the more general question of synchronization and partial state equipartitioning of neural activity without mean field assumptions. This is done by focusing on a postulated subset of inhibitory neurons that are not themselves connected to other inhibitory neurons. Finally, several numerical experiments are presented to illustrate the different aspects of the proposed theory.

中文翻译：

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麻醉如何抑制意识的机械神经场理论：突触驱动动力学，分叉，吸引子和部分状态均分。

随着生物化学，分子生物学和神经化学的进步，在理解麻醉剂分子特性方面取得了令人印象深刻的进步。然而，很少关注麻醉剂的分子特性如何导致观察到的限定麻醉状态的宏观特性，即对有害刺激物缺乏反应性。在本文中，我们使用动力学系统理论为神经活动建立了一个机械平均场模型，以研究随着麻醉剂浓度的增加从意识到无意识的突然转变。拟议的突触驱动射击率模型可预测随着麻醉药浓度的增加，有意识-无意识过渡，其中兴奋性神经活动的特征是庞加莱-安德罗诺夫-霍夫夫分叉，清醒状态过渡到稳定的极限循环，然后过渡到渐近稳定的无意识平衡状态。此外，我们解决了没有平均场假设的神经活动的同步和部分状态均分这一更普遍的问题。这是通过集中于假定的抑制神经元子集完成的，这些子集本身并不与其他抑制神经元相连。最后，通过几个数值实验来说明所提出理论的不同方面。我们解决了没有活动场假设的神经活动同步和部分状态均分这一更普遍的问题。这是通过集中于假定的抑制神经元子集完成的，这些子集本身并不与其他抑制神经元相连。最后，通过几个数值实验来说明所提出理论的不同方面。我们解决了没有活动场假设的神经活动同步和部分状态均分这一更普遍的问题。这是通过集中于假定的抑制神经元子集完成的，这些子集本身并不与其他抑制神经元相连。最后，通过几个数值实验来说明所提出理论的不同方面。