{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T06:17:56Z","timestamp":1764656276601,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T00:00:00Z","timestamp":1700006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"],"award-info":[{"award-number":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"],"award-info":[{"award-number":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hebei Province Innovation Capability Improvement Plan Project","award":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"],"award-info":[{"award-number":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"]}]},{"name":"Science Research Foundation of Hebei Normal University of Science and Technology","award":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"],"award-info":[{"award-number":["62073278","61473245","61004050","F2017203218","F2021203020","22567619H","2023YB022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Neurostimulation can be used to modulate brain dynamics of patients with neuropsychiatric disorders to make abnormal neural oscillations restore to normal. The control schemes proposed on the bases of neural computational models can predict the mechanism of neural oscillations induced by neurostimulation, and then make clinical decisions that are suitable for the patient\u2019s condition to ensure better treatment outcomes. The present work proposes two closed-loop control schemes based on the improved incremental proportional integral derivative (PID) algorithms to modulate brain dynamics simulated by Wendling-type coupled neural mass models. The introduction of the genetic algorithm (GA) in traditional incremental PID algorithm aims to overcome the disadvantage that the selection of control parameters depends on the designer\u2019s experience, so as to ensure control accuracy. The introduction of the radial basis function (RBF) neural network aims to improve the dynamic performance and stability of the control scheme by adaptively adjusting control parameters. The simulation results show the high accuracy of the closed-loop control schemes based on GA-PID and GA-RBF-PID algorithms for modulation of brain dynamics, and also confirm the superiority of the scheme based on the GA-RBF-PID algorithm in terms of the dynamic performance and stability. This research of making hypotheses and predictions according to model data is expected to improve and perfect the equipment of early intervention and rehabilitation treatment for neuropsychiatric disorders in the biomedical engineering field.<\/jats:p>","DOI":"10.3390\/e25111544","type":"journal-article","created":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T10:51:37Z","timestamp":1700045497000},"page":"1544","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Design of Closed-Loop Control Schemes Based on the GA-PID and GA-RBF-PID Algorithms for Brain Dynamic Modulation"],"prefix":"10.3390","volume":"25","author":[{"given":"Chengxia","family":"Sun","sequence":"first","affiliation":[{"name":"Mechanical and Electrical Engineering College, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China"}]},{"given":"Lijun","family":"Geng","sequence":"additional","affiliation":[{"name":"Mechanical and Electrical Engineering College, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China"}]},{"given":"Xian","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China"}]},{"given":"Qing","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0079-6123(08)62055-5","article-title":"Introduction to Neurocybernetics","volume":"2","author":"Wiener","year":"1963","journal-title":"Prog. 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