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rTMS Improves Cognitive Function and Brain Network Connectivity in Patients With Alzheimer’s Disease
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作者 XU Gui-Zhi LIU Lin +4 位作者 GUO Miao-Miao WANG Tian GAO Jiao-Jiao JI Yong WANG Pan 《生物化学与生物物理进展》 北大核心 2025年第8期2131-2145,共15页
Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,n... Objective Repetitive transcranial magnetic stimulation(rTMS)has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease(AD),but the neurobiological mechanisms linking synaptic pathology,neural oscillatory dynamics,and brain network reorganization remain unclear.This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments,molecular profiling,and neurophysiological monitoring.Methods In this prospective double-blind trial,12 AD patients underwent a 14-day protocol of 20 Hz rTMS,with comprehensive multimodal assessments performed pre-and postintervention.Cognitive functioning was quantified using the mini-mental state examination(MMSE)and Montreal cognitive assessment(MOCA),while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living(ADL)scale and combined neuropsychiatric inventory(NPI)-Hamilton depression rating scale(HAMD).Peripheral blood biomarkers,specifically Aβ1-40 and phosphorylated tau(p-tau181),were analyzed to investigate the effects of rTMS on molecular metabolism.Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients,while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization.Furthermore,systematic assessment of correlations between cognitive scale scores,blood biomarkers,and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically,MMSE and MOCA scores improved significantly(P<0.05).Biomarker showed that Aβ1-40 level increased(P<0.05),contrasting with p-tau181 reduction.Moreover,the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores.Post-intervention analyses revealed significant modulations in oscillatory power,characterized by pronounced reductions in delta(P<0.05)and theta bands(P<0.05),while concurrent enhancements were observed in alpha,beta,and gamma band activities(all P<0.05).Network analysis revealed frequency-specific reorganization:clustering coefficients were significantly decreased in delta,theta,and alpha bands(P<0.05),while global efficiency improvement was exclusively detected in the delta band(P<0.05).The alpha band demonstrated concurrent increases in average nodal degree(P<0.05)and characteristic path length reduction(P<0.05).Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181.Additionally,the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band.However,the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex(DLPFC)significantly improves cognitive function and enhances the metabolic clearance ofβ-amyloid and tau proteins in AD patients.This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation,which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks.These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales,blood biomarkers,and EEG——in understanding and monitoring the progression of AD.This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment. 展开更多
关键词 transcranial magnetic stimulation Alzheimer’s disease power spectral density ELECTROENCEPHALOGRAM brain functional network
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基于替代模型和贝叶斯推理的EIT电阻率反演
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作者 李颖 郝虎鹏 +2 位作者 王贤哲 林坤强 何益人 《天津大学学报(自然科学与工程技术版)》 EI CAS CSCD 北大核心 2024年第11期1187-1199,共13页
在生物组织电阻抗成像(EIT)技术中,介质电特性分布具有不确定性,因而研究概率框架下的重建方法具有重要意义.针对EIT中电阻率的不确定性反演及正问题调用过程中计算负荷庞大的问题,提出了基于替代模型和贝叶斯推理的参数反演方法.首先,... 在生物组织电阻抗成像(EIT)技术中,介质电特性分布具有不确定性,因而研究概率框架下的重建方法具有重要意义.针对EIT中电阻率的不确定性反演及正问题调用过程中计算负荷庞大的问题,提出了基于替代模型和贝叶斯推理的参数反演方法.首先,针对4层同心圆头模型,采用拉丁超立方抽样方法进行训练,建立了EIT正问题计算的Kriging模型、BP神经网络模型和径向基函数(RBF)神经网络模型,并且甄别出精度最高的RBF神经网络替代模型.结果表明,替代模型在保证计算精度的条件下大幅提高了计算效率.然后,基于贝叶斯推理框架下的差分进化自适应多链并行DREAM_zs算法和在此基础上加入卡尔曼激励建议分布的DREAM_kzs算法,对EIT中的电阻率进行反演.结果表明,两种算法均能进行有效反演,DREAM_kzs算法有着更快的收敛速度和更高的识别精度,且灵敏度越高的参数反演效果越好,即头皮的反演效果最好,其次依次为颅骨、大脑和脑脊液.进一步,构造了基于真实CT图像的胸腔仿真模型,采用RBF模型作为正问题替代模型,利用DREAM_zs算法和DREAM_kzs算法对正常肺部组织和两种病变情况进行电阻率分布的图像重构.结果表明,两种方法均能有效反演,DREAM_kzs算法的性能均优于DREAM_zs算法,且外层单元的反演效果整体上要优于内层单元.仿真实验结果表明,基于替代模型和贝叶斯推理的方法可实现EIT电阻率的有效反演,可望为临床应用提供依据. 展开更多
关键词 电阻抗成像 替代模型 贝叶斯推理 电阻率反演 DREAM_kzs算法
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基于K-L散度和深度聚类的自适应EEGNet-T分布解码算法研究 被引量:2
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作者 李梦凡 宋智勇 +3 位作者 郭苗苗 邓豪东 张鹏飞 徐桂芝 《信号处理》 CSCD 北大核心 2023年第8期1465-1477,共13页
脑机接口是脑与外界不通过神经或肌肉建立的交流通路,脑电解码通过归类脑电特征解读输出大脑意图,是影响性能的关键之一。由于脑电信号存在非平稳特性,即使在同一实验过程中脑电信号的特征也会随时间发生变化,导致事先训练好的解码模型... 脑机接口是脑与外界不通过神经或肌肉建立的交流通路,脑电解码通过归类脑电特征解读输出大脑意图,是影响性能的关键之一。由于脑电信号存在非平稳特性,即使在同一实验过程中脑电信号的特征也会随时间发生变化,导致事先训练好的解码模型精度常常会随时间逐渐降低,不利于脑机接口的长期稳定运行。本研究提出基于K-L散度和深度聚类的自适应EEGNet-T分布解码算法,根据脑电特征变化前后T分布的K-L散度评估脑电的非平稳性并构建基于平稳性差值的目标函数,并以此目标函数调整EEGNet网络参数通过改变非线性映射的方式缩小平稳性差值,从而动态调整融合深度网络与聚类的EEGNet-T分布模型,实现对非平稳脑电的自适应解码。10名被试参与了视觉-听觉的脑机接口实验,并进行较长时间的脑电解码预测。与传统算法相比,本算法在连续128个试次组的任务中获得最高的平均准确率87.85%(p<0.05),并且在前半段实验和后半段实验对比中表现出最强的稳定性,表明该算法能够通过深度网络调整数据特征分布更好地适应脑电信号特征变化,具有更强的解码稳定性,能够保证脑机接口长时间工作的解码精度,为脑机接口实用化提供基础。 展开更多
关键词 脑机接口 脑电非平稳性 自适应算法 深度聚类 EEGNet T分布
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