Department of Physics, Universidade Federal do Paraná, 81531-980 Curitiba, PR, Brazil.
Department of Physics, Universidade do Estado de Santa Catarina, 89219-710 Joinville, SC, Brazil.
Neural Netw. 2021 May;137:97-105. doi: 10.1016/j.neunet.2021.01.019. Epub 2021 Jan 29.
The partial phase synchronization (sometimes called cooperation) of neurons is fundamental for the understanding of the complex behavior of the brain. The lack or the excess of synchronization can generate brain disorders like Parkinson's disease and epilepsy. The phase synchronization phenomenon is strongly related to the regular or chaotic dynamics of individual neurons. The individual dynamics themselves are a function of the ion channel conductances, turning the conductances into important players in the process of neuron synchronized health depolarization/repolarization processes. It is well known that many diseases are related to alterations of the ion-channel conductance properties. To normalize their functioning, drugs are used to block or activate specific channels, changing their conductances. We investigate the synchronization process of a Hodgkin-Huxley-type neural network as a function of the values of the individual neuron conductances, showing the dynamics of the neurons must be taken into account in the synchronization process. Particular sets of conductances lead to non-chaotic individual neuron dynamics allowing synchronization states for very weak coupling and resulting in a non-monotonic transition to synchronized states, as the coupling strength among neurons is varied. On the other hand, a monotonic transition to synchronized states is observed for individual chaotic dynamics of the neurons. We conclude the analysis of the individual dynamics of isolated neurons allows the prediction of the synchronization process of the network. We provide alternative ways to achieve the desired network state (phase synchronized or desynchronized) without any changes in the synaptic current of neurons but making just small changes in the neuron ion-channel conductances. The mechanism behind the control is the close relation between ion-channel conductance and the regular or chaotic dynamics of neurons. Finally, we show that by changing at least two conductances simultaneously the control may be much more efficient since the second conductance makes the synchronization possible just by performing a small change in the first. The study presented here may have an impact on new drug development research.
神经元的部分相位同步(有时称为合作)是理解大脑复杂行为的基础。同步的缺乏或过度都会导致帕金森病和癫痫等脑部疾病。相位同步现象与单个神经元的规则或混沌动力学密切相关。单个动力学本身就是离子通道电导的函数,使电导成为神经元同步健康去极化/复极化过程的重要参与者。众所周知,许多疾病都与离子通道电导特性的改变有关。为了使它们的功能正常化,药物被用来阻断或激活特定的通道,从而改变它们的电导。我们研究了 Hodgkin-Huxley 型神经网络的同步过程作为单个神经元电导值的函数,表明在同步过程中必须考虑神经元的动力学。特定的电导集导致非混沌的单个神经元动力学,允许在非常弱的耦合下实现同步状态,并导致非单调过渡到同步状态,因为神经元之间的耦合强度发生变化。另一方面,对于神经元的个体混沌动力学,观察到到同步状态的单调过渡。我们得出结论,孤立神经元的个体动力学分析可以预测网络的同步过程。我们提供了在不改变神经元突触电流的情况下实现所需网络状态(相位同步或去同步)的替代方法,而只是对神经元离子通道电导进行微小改变。控制背后的机制是离子通道电导与神经元规则或混沌动力学之间的密切关系。最后,我们表明通过同时改变至少两个电导,控制可能更加有效,因为第二个电导仅通过对第一个电导进行微小改变就可以实现同步。这里呈现的研究可能会对新的药物开发研究产生影响。