个性化闭环电刺激治疗自发性颞叶癫痫的靶点选择。

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Yufang Yang, Haoqi Ni, Yuting Sun, Yanjie Xing, Chang Wang, Jianmin Zhang, Junming Zhu, Kedi Xu
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引用次数: 0

摘要

闭环神经调节在治疗难治性癫痫方面具有重要的前景,但缺乏特异性和个体化极大地限制了其临床疗效。考虑到癫痫固有的复杂性,它涉及多个大脑区域和显著的个体间变异性,一种网络引导的个性化方法是必不可少的。本研究旨在利用独特的大脑网络特征,开发精确的、个性化的神经调节策略。采用闭环系统对慢性颞叶癫痫(cTLE)大鼠的连续神经信号进行分析,通过Granger因果关系(GC)方法确定最佳刺激靶点。结果表明,大脑网络连接在短期内保持稳定,但随着时间的推移发生了显著变化。气相色谱引导刺激可有效缩短癫痫发作时间,增强θ和α频段活动,抑制γ活动。此外,有针对性的刺激可以短暂地抑制发作期间的间隔尖峰和抑制高频振荡。这些发现强调了个性化神经调节改善癫痫治疗结果的潜力,并加深了对其潜在机制的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Individualized Target Selection of Closed-loop Electrical Stimulation for the Treatment of Spontaneous Temporal Lobe Epilepsy.

Closed-loop neuromodulation holds significant promise for treating refractory epilepsy, but the lack of specificity and individualization considerably limits its clinical efficacy. Given the inherent complexity of epilepsy, which involves multiple brain regions and significant interindividual variability, a network-guided, personalized approach is essential. This study aims to develop precise, individualized neuromodulation strategies by leveraging unique brain network characteristics. Using a closed-loop system in chronic temporal lobe epilepsy (cTLE) rats, continuous neural signals were analyzed to identify optimal stimulation targets via the Granger causality (GC) method. Results showed that brain network connectivity remained stable in the short term but changed significantly over time. GC-guided stimulation effectively reduced seizure duration, enhancing θ and α frequency band activity while suppressing γ activity. Additionally, targeted stimulation briefly inhibited interictal spikes and suppressed high-frequency oscillations during seizures. These findings highlight the potential for personalized neuromodulation to improve epilepsy treatment outcomes and deepen understanding of its underlying mechanisms.

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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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