The Controllability Analysis of Brain Networks During Rhythmic Propagation

被引:1
|
作者
Li, Renjie [1 ]
Sun, Chengxia [2 ]
Dong, Miao [1 ]
Wang, Meijuan [1 ]
Gao, Qing [1 ]
Liu, Xian [1 ]
机构
[1] Yanshan Univ, Inst Elect Engn, State Key Lab Intelligent Rehabil & Neuromodulat H, Qinhuangdao 066099, Peoples R China
[2] Hebei Normal Univ Sci & Technol, Mech & Elect Engn Coll, Qinhuangdao 066004, Peoples R China
基金
中国国家自然科学基金;
关键词
Controllability; complex network; brain rhythmic propagation; neural mass model; NEURAL OSCILLATIONS; FUNCTIONAL NETWORK; SYSTEMS; FREQUENCY; COGNITION; GAMMA;
D O I
10.1109/TNSE.2024.3386949
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The association between pathological states and aberrant brain rhythms underscores the potential of brain rhythm modulation to facilitate the transition from pathological states back to physiological norms. It is important to ensure the feasibility of the brain rhythm modulation strategy. The concept of system controllability, a cornerstone of control science, serves as a crucial prerequisite for the creation of state feedback mechanisms designed to achieve desired system performance. Investigating the controllability of brain networks from a control standpoint lays a theoretical foundation for the practicality and strategic planning of neuromodulation. This study delves into the controllability of brain networks composed of neural mass models with four distinct rhythms RcR-alpha , RcR-beta , RcR-theta and RcR-gamma. Through the examination of how various inputs, model parameters, and the interplay between neural mass models influence controllability, we can observe the intricate relationship between brain networks controllability and rhythmic activity. Our findings suggest that the controllability of brain networks is particularly sensitive to changes in the external inputs or the strength of internal connections of RcR-alpha and RcR-gamma , in contrast to RcR-beta and RcR-theta. We hope that this research not only advances the understanding of neural regulation's feasibility but also informs the optimization of network dynamics and connectivity in neuromodulation strategy development.
引用
收藏
页码:3812 / 3823
页数:12
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