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Controllability of Networks of Multiple Coupled Neural Populations: An Analytical Method for Neuromodulation’s Feasibility
International Journal of Neural Systems ( IF 8 ) Pub Date : 2019-10-29 , DOI: 10.1142/s012906572050001x
Xian Liu 1 , Cheng-Xia Sun 1 , Jing Gao 1 , Shi-Yun Xu 2, 3
Affiliation  

Neuromodulation plays a vital role in the prevention and treatment of neurological and psychiatric disorders. Neuromodulation’s feasibility is a long-standing issue because it provides the necessity for neuromodulation to realize the desired purpose. A controllability analysis of neural dynamics is necessary to ensure neuromodulation’s feasibility. Here, we present such a theoretical method by using the concept of controllability from the control theory that neuromodulation’s feasibility can be studied smoothly. Firstly, networks of multiple coupled neural populations with different topologies are established to mathematically model complicated neural dynamics. Secondly, an analytical method composed of a linearization method, the Kalman controllable rank condition and a controllability index is applied to analyze the controllability of the established network models. Finally, the relationship between network dynamics or topological characteristic parameters and controllability is studied by using the analytical method. The proposed method provides a new idea for the study of neuromodulation’s feasibility, and the results are expected to guide us to better modulate neurodynamics by optimizing network dynamics and network topology.

中文翻译:

多耦合神经群体网络的可控性:神经调节可行性的分析方法

神经调节在预防和治疗神经和精神疾病方面发挥着至关重要的作用。神经调节的可行性是一个长期存在的问题,因为它为神经调节提供了实现预期目的的必要性。神经动力学的可控性分析对于确保神经调节的可行性是必要的。在这里,我们利用控制理论中的可控性概念提出了这样一种理论方法,可以顺利地研究神经调节的可行性。首先,建立具有不同拓扑结构的多个耦合神经群体网络,对复杂的神经动力学进行数学建模。其次,由线性化方法组成的分析方法,应用卡尔曼可控秩条件和可控性指标分析所建立网络模型的可控性。最后,利用解析法研究了网络动力学或拓扑特征参数与可控性的关系。该方法为研究神经调节的可行性提供了新思路,结果有望指导我们通过优化网络动力学和网络拓扑来更好地调节神经动力学。
更新日期:2019-10-29
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