Background:Working memory deficits,one of the earliest hallmarks of Alzheimer’s disease(AD),are closely linked to abnormal neural activity in the dorsolateral prefrontal cortex(DLPFC).Transcranial direct current stim...Background:Working memory deficits,one of the earliest hallmarks of Alzheimer’s disease(AD),are closely linked to abnormal neural activity in the dorsolateral prefrontal cortex(DLPFC).Transcranial direct current stimulation(tDCS),a non-invasive neuromodulation therapy,has been shown to ameliorate early AD working memory deficits by modulating excitatory activity in the DLPFC,yet the underlying mechanisms remain incompletely understood.Methods:This investigation was structured around three experimental phases.We initially applied tDCS to stimulate the left prefrontal cortex(PFC)of transgenic mice with 5 familial AD(5×FAD)5 d per week for 4 weeks.Subsequently,we employed optogenetic(Opt)techniques to modulate left PFC glutamatergic neurons.Finally,we inhibited soluble N-ethylmaleimide-sensitive factor attachment receptor(SNARE)expression in the left PFC to elucidate the essential function of SNARE complex assembly with chaperone molecules in orchestrating synaptic vesicle release.Results:tDCS treatment improved working memory deficits in early-stage AD mice.This was accompanied by increased cerebral blood flow,enhanced neuronal excitability,amelioration of neurochemical metabolic disorders,and reduced amyloidβ-protein(Aβ)deposition in the left PFC.Opt stimulation of PFC glutamatergic neurons similarly improved working memory,indicating the association between tDCS’s therapeutic effects and synaptic plasticity of excitatory neurons.Crucially,tDCS facilitated synaptic vesicle fusion and release,evidenced by increased vesicle numbers,enhanced release probability,improved synaptic transmission efficacy,and upregulation of the SNARE complex,Snap25,and Syt1.Inhibiting SNARE expression in the left PFC attenuated the tDCS-induced improvements in synaptic vesicle release and working memory.Conclusion:These findings collectively demonstrate that left PFC-targeted tDCS modulates interactions between the SNARE complex and chaperone molecules,thereby promoting synaptic vesicle fusion and release.This mechanism underlies the amelioration of early AD-like working memory impairment by tDCS.展开更多
目的:探究新神经发育(Bobath技术)结合tDCS技术对老年缺血性脑卒中偏瘫患者步行能力及炎性因子水平的影响。方法:选取131例老年缺血性脑卒中偏瘫患者,根据随机数字表法分为两组。对照组65例给予经颅直流电刺激(tDCS)技术,观察组66例增加...目的:探究新神经发育(Bobath技术)结合tDCS技术对老年缺血性脑卒中偏瘫患者步行能力及炎性因子水平的影响。方法:选取131例老年缺血性脑卒中偏瘫患者,根据随机数字表法分为两组。对照组65例给予经颅直流电刺激(tDCS)技术,观察组66例增加新Bobath技术,3个月后,对比两组患者步行能力:Fugl-Meyer运动评分量表(FMA)、功能性步行量表(FAC)、10 m最大步行速度(10 m MWS)、步频、步幅;炎性因子水平:超敏C反应蛋白(hs-CRP)、超氧化物歧化酶(SOD)、白介素10(IL-10)、丝氨酸蛋白酶抑制剂水平。结果:治疗后观察组FMA、FAC评分、10 m MWS、步频、步幅、SOD、丝氨酸蛋白酶抑制剂均高于对照组,hs-CRP、IL-10低于对照组,两组比较差异有统计学意义(P<0.05)。结论:新Bobath技术结合tDCS技术对老年缺血性脑卒中偏瘫患者康复治疗,可降低患者炎症反应,提升步行能力。展开更多
目的:探讨经颅直流电刺激(transcranial direct current stimulation,tDCS)对甲基苯丙胺成瘾者认知功能、焦虑及抑郁的治疗效果。方法:于2018年7-10月,采用分层整群随机抽样的方法,抽取辽宁省3个强制隔离戒毒所264例甲基苯丙胺成瘾戒毒...目的:探讨经颅直流电刺激(transcranial direct current stimulation,tDCS)对甲基苯丙胺成瘾者认知功能、焦虑及抑郁的治疗效果。方法:于2018年7-10月,采用分层整群随机抽样的方法,抽取辽宁省3个强制隔离戒毒所264例甲基苯丙胺成瘾戒毒人员为研究对象,随机分为试验组与对照组,每组各132例患者,试验组采用tDCS治疗,对照组采用假tDCS治疗;采用简易智力状态检查量表(MMSE)、蒙特利尔认知评估量表(MoCA)、汉密尔顿抑郁量表(HAMD)和汉密尔顿焦虑量表(HAMA)评价两组戒毒人员的认知功能、焦虑和抑郁情况。结果:tDCS治疗后试验组MMSE和MoCA得分均较治疗前显著升高(P<0.05);治疗后试验组HAMD和HAMA得分均较治疗前显著降低(P<0.05);试验组治疗后MMSE、MoCA、HAMD和HAMA得分与对照组之间差异有统计学意义(P<0.05)。结论:tDCS治疗可改善甲基苯丙胺成瘾者认知功能,并减轻其焦虑、抑郁症状。展开更多
针对变换域通信系统(Transform Domain Communication System,TDCS)信号难以检测的问题,设计了基于功率谱二次处理的检测方法。通过数学建模,理论推导了TDCS信号的自相关函数,并由此推出了TDCS信号的两次功率谱函数,证明了TDCS信号的二...针对变换域通信系统(Transform Domain Communication System,TDCS)信号难以检测的问题,设计了基于功率谱二次处理的检测方法。通过数学建模,理论推导了TDCS信号的自相关函数,并由此推出了TDCS信号的两次功率谱函数,证明了TDCS信号的二次功率谱存在周期性谱峰的特征,并给出了谱峰周期与基函数周期的数学关系。据此设计了一种TDCS信号检测算法,该算法能够检测TDCS信号并对基函数周期给予估计。理论分析了高斯白噪声对检测算法的影响,通过计算机仿真,验证了该算法在低信噪比下的性能,对比了二次功率谱法与时域相关法的检测性能,验证了采样数据长度对检测性能的影响。仿真结果表明在低信噪比条件下,本文算法对基函数周期估计仍有效,且算法性能相较于自相关法提高了约1.5 dB,增加采样数据长度可进一步提高二次功率谱算法的准确性。展开更多
为了解决变换域通信系统(transformed domain communication system, TDCS)信号检测及参数估计问题,通过对TDCS信号自相关函数的推导分析,提出了一种基于二次自相关的TDCS信号检测及基函数估计的方法。分析发现,TDCS信号的自相关函数会...为了解决变换域通信系统(transformed domain communication system, TDCS)信号检测及参数估计问题,通过对TDCS信号自相关函数的推导分析,提出了一种基于二次自相关的TDCS信号检测及基函数估计的方法。分析发现,TDCS信号的自相关函数会出现周期性谱峰,且峰峰间距为基函数周期的二分之一,故以谱峰间隔是否呈现周期性作为TDCS信号的存在性判据,并根据峰峰距离进一步估计TDCS信号的基函数周期。但单次自相关处理得到的局部谱峰受信道噪声影响大,为此提出了二次自相关法,该方法使得局部峰值特征进一步加强,相较于单次自相关,二次自相关可在更低的信噪比下实现TDCS信号检测并对基函数周期进行有效估计。展开更多
Various types of interference signals limit the practical application of transform domain communication systems(TDCSs)in the severe electromagnetic field,an orthogonal basis learning method of transformation analysis(...Various types of interference signals limit the practical application of transform domain communication systems(TDCSs)in the severe electromagnetic field,an orthogonal basis learning method of transformation analysis(OBL-TA)is proposed to effectively address the problem of obtaining an optimal transform domain based on sparse representation.Then,the sparse availability is utilized to obtain the optimal transformation analysis by the iterative methods,which yields the sparse representation for transform domain(SRTD)in unrestricted form.In addition,the iterative version of SRTD(I-SRTD)in unrestricted form is obtained by decomposing the SRTD problem into three sub-problems and each sub-problem is iteratively solved by learning the best orthogonal basis.Furthermore,orthogonal basis learning via cost function minimization process is conducted by stochastic descent,which is assured to converge to a local minimum at least.Finally,the optimal transformation analysis is developed by the effectiveness of different transform domains according to the accuracy of the sparse representation and an optimal transformation analysis separately(OPTAS)is applied to the synthesized signal forms with conic alternatives,dualization,and smoothing.Simulation results demonstrate that the superiorities of the proposed methods achieve the optimal recovery and separation more rapidly and accurately than conventional methods.展开更多
基金supported by the National "Ten Thousand People Plan" Young Top Talents Programthe Chinese Society of Rehabilitation Medicine (KFKT-2022-011)
摘要Background:Working memory deficits,one of the earliest hallmarks of Alzheimer’s disease(AD),are closely linked to abnormal neural activity in the dorsolateral prefrontal cortex(DLPFC).Transcranial direct current stimulation(tDCS),a non-invasive neuromodulation therapy,has been shown to ameliorate early AD working memory deficits by modulating excitatory activity in the DLPFC,yet the underlying mechanisms remain incompletely understood.Methods:This investigation was structured around three experimental phases.We initially applied tDCS to stimulate the left prefrontal cortex(PFC)of transgenic mice with 5 familial AD(5×FAD)5 d per week for 4 weeks.Subsequently,we employed optogenetic(Opt)techniques to modulate left PFC glutamatergic neurons.Finally,we inhibited soluble N-ethylmaleimide-sensitive factor attachment receptor(SNARE)expression in the left PFC to elucidate the essential function of SNARE complex assembly with chaperone molecules in orchestrating synaptic vesicle release.Results:tDCS treatment improved working memory deficits in early-stage AD mice.This was accompanied by increased cerebral blood flow,enhanced neuronal excitability,amelioration of neurochemical metabolic disorders,and reduced amyloidβ-protein(Aβ)deposition in the left PFC.Opt stimulation of PFC glutamatergic neurons similarly improved working memory,indicating the association between tDCS’s therapeutic effects and synaptic plasticity of excitatory neurons.Crucially,tDCS facilitated synaptic vesicle fusion and release,evidenced by increased vesicle numbers,enhanced release probability,improved synaptic transmission efficacy,and upregulation of the SNARE complex,Snap25,and Syt1.Inhibiting SNARE expression in the left PFC attenuated the tDCS-induced improvements in synaptic vesicle release and working memory.Conclusion:These findings collectively demonstrate that left PFC-targeted tDCS modulates interactions between the SNARE complex and chaperone molecules,thereby promoting synaptic vesicle fusion and release.This mechanism underlies the amelioration of early AD-like working memory impairment by tDCS.
摘要目的:探究新神经发育(Bobath技术)结合tDCS技术对老年缺血性脑卒中偏瘫患者步行能力及炎性因子水平的影响。方法:选取131例老年缺血性脑卒中偏瘫患者,根据随机数字表法分为两组。对照组65例给予经颅直流电刺激(tDCS)技术,观察组66例增加新Bobath技术,3个月后,对比两组患者步行能力:Fugl-Meyer运动评分量表(FMA)、功能性步行量表(FAC)、10 m最大步行速度(10 m MWS)、步频、步幅;炎性因子水平:超敏C反应蛋白(hs-CRP)、超氧化物歧化酶(SOD)、白介素10(IL-10)、丝氨酸蛋白酶抑制剂水平。结果:治疗后观察组FMA、FAC评分、10 m MWS、步频、步幅、SOD、丝氨酸蛋白酶抑制剂均高于对照组,hs-CRP、IL-10低于对照组,两组比较差异有统计学意义(P<0.05)。结论:新Bobath技术结合tDCS技术对老年缺血性脑卒中偏瘫患者康复治疗,可降低患者炎症反应,提升步行能力。
摘要目的:探讨经颅直流电刺激(transcranial direct current stimulation,tDCS)对甲基苯丙胺成瘾者认知功能、焦虑及抑郁的治疗效果。方法:于2018年7-10月,采用分层整群随机抽样的方法,抽取辽宁省3个强制隔离戒毒所264例甲基苯丙胺成瘾戒毒人员为研究对象,随机分为试验组与对照组,每组各132例患者,试验组采用tDCS治疗,对照组采用假tDCS治疗;采用简易智力状态检查量表(MMSE)、蒙特利尔认知评估量表(MoCA)、汉密尔顿抑郁量表(HAMD)和汉密尔顿焦虑量表(HAMA)评价两组戒毒人员的认知功能、焦虑和抑郁情况。结果:tDCS治疗后试验组MMSE和MoCA得分均较治疗前显著升高(P<0.05);治疗后试验组HAMD和HAMA得分均较治疗前显著降低(P<0.05);试验组治疗后MMSE、MoCA、HAMD和HAMA得分与对照组之间差异有统计学意义(P<0.05)。结论:tDCS治疗可改善甲基苯丙胺成瘾者认知功能,并减轻其焦虑、抑郁症状。
摘要针对变换域通信系统(Transform Domain Communication System,TDCS)信号难以检测的问题,设计了基于功率谱二次处理的检测方法。通过数学建模,理论推导了TDCS信号的自相关函数,并由此推出了TDCS信号的两次功率谱函数,证明了TDCS信号的二次功率谱存在周期性谱峰的特征,并给出了谱峰周期与基函数周期的数学关系。据此设计了一种TDCS信号检测算法,该算法能够检测TDCS信号并对基函数周期给予估计。理论分析了高斯白噪声对检测算法的影响,通过计算机仿真,验证了该算法在低信噪比下的性能,对比了二次功率谱法与时域相关法的检测性能,验证了采样数据长度对检测性能的影响。仿真结果表明在低信噪比条件下,本文算法对基函数周期估计仍有效,且算法性能相较于自相关法提高了约1.5 dB,增加采样数据长度可进一步提高二次功率谱算法的准确性。
摘要为了解决变换域通信系统(transformed domain communication system, TDCS)信号检测及参数估计问题,通过对TDCS信号自相关函数的推导分析,提出了一种基于二次自相关的TDCS信号检测及基函数估计的方法。分析发现,TDCS信号的自相关函数会出现周期性谱峰,且峰峰间距为基函数周期的二分之一,故以谱峰间隔是否呈现周期性作为TDCS信号的存在性判据,并根据峰峰距离进一步估计TDCS信号的基函数周期。但单次自相关处理得到的局部谱峰受信道噪声影响大,为此提出了二次自相关法,该方法使得局部峰值特征进一步加强,相较于单次自相关,二次自相关可在更低的信噪比下实现TDCS信号检测并对基函数周期进行有效估计。
基金supported by the University Cooperation Project Foundation of the Key Laboratory for Aerospace Information Technology(KX162600022).
摘要Various types of interference signals limit the practical application of transform domain communication systems(TDCSs)in the severe electromagnetic field,an orthogonal basis learning method of transformation analysis(OBL-TA)is proposed to effectively address the problem of obtaining an optimal transform domain based on sparse representation.Then,the sparse availability is utilized to obtain the optimal transformation analysis by the iterative methods,which yields the sparse representation for transform domain(SRTD)in unrestricted form.In addition,the iterative version of SRTD(I-SRTD)in unrestricted form is obtained by decomposing the SRTD problem into three sub-problems and each sub-problem is iteratively solved by learning the best orthogonal basis.Furthermore,orthogonal basis learning via cost function minimization process is conducted by stochastic descent,which is assured to converge to a local minimum at least.Finally,the optimal transformation analysis is developed by the effectiveness of different transform domains according to the accuracy of the sparse representation and an optimal transformation analysis separately(OPTAS)is applied to the synthesized signal forms with conic alternatives,dualization,and smoothing.Simulation results demonstrate that the superiorities of the proposed methods achieve the optimal recovery and separation more rapidly and accurately than conventional methods.