目的探讨不同程度新生儿缺氧缺血性脑病(hypoxic-ischemic encephalopathy,HIE)患儿脑功能网络的变化,了解该变化对脑功能的影响。方法收集从2017年1月至2020年5月于常州儿童医院新生儿科住院的足月HIE患儿的临床资料,共44例,均进行常...目的探讨不同程度新生儿缺氧缺血性脑病(hypoxic-ischemic encephalopathy,HIE)患儿脑功能网络的变化,了解该变化对脑功能的影响。方法收集从2017年1月至2020年5月于常州儿童医院新生儿科住院的足月HIE患儿的临床资料,共44例,均进行常规和功能磁共振(functional magnetic resonance image,fMRI)成像扫描,有24例符合入组标准,其中轻度患者(PT1组)11例,中重度患者(PT2组)13例。采用低频振幅(amplitude of low frequency fluctuation,ALFF)比较PT1组和PT2组全脑的ALFF值的差异,并采用脑网络连边分析的方法比较PT1组和PT2组脑功能连接(functional connectivity,FC)的差异。结果在连边分析中,与PT1组相比,PT2组大脑中的右侧辅助运动区与右侧中央前回(Z1=0.39,Z2=-0.08)、右侧舌回与右侧海马(Z1=0.61,Z2=0.20)、左侧距状裂皮层与右侧杏仁核(Z1=0.30,Z2=-0.02)、右侧苍白球与右侧后扣带皮层(Z1=0.33,Z2=0.05)的FC减弱(均P<0.001,未校正)。在低频振幅分析中,PT1组和PT2组全脑的ALFF值差异无统计学意义(P>0.05,FDR校正)。结论中重度组HIE患儿在部分脑区的功能连接存在变化,这些功能连接与运动功能、情绪处理、语言发育、认知功能及学习记忆等有关。展开更多
Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s func...Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore t展开更多
Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore func...Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.展开更多
精准功能磁共振成像(precision functional magnetic resonance imaging,pfMRI)是指在单个个体中收集大量fMRI数据的一种数据采集策略,相较于传统fMRI研究中针对每个被试采集少量数据,之后通过组平均揭示认知过程的脑功能规律或是特定...精准功能磁共振成像(precision functional magnetic resonance imaging,pfMRI)是指在单个个体中收集大量fMRI数据的一种数据采集策略,相较于传统fMRI研究中针对每个被试采集少量数据,之后通过组平均揭示认知过程的脑功能规律或是特定人群共享的脑功能特征的方法,该方法的优势在于能够揭示每个个体的大脑特征,因此日益受到研究者的重视和应用。迄今为止,众多研究采用该方法从功能网络组织的个体差异、个体识别、局部区域的功能定位、个体网络枢纽的识别、个体功能网络的发展与可塑性和临床应用六个角度系统揭示了个体化的脑功能网络组织,这些研究成果对未来脑科学研究具有重要启发。未来研究应该重点探讨现有研究所揭示的个体功能网络组织特点与行为表现的关系,通过对数据分析和成像技术的改进减少该方法所需的扫描时间,并尝试将该方法应用到任务态fMRI和多模态数据的融合研究中。展开更多
人脑活动是在秒级与毫秒级动态变化的,因此采用静态连接方式构建的功能性脑网络,会造成部分与时间相关有效特征的缺失。该文旨在研究情绪变化期间不同大脑区域之间相互作用的时空变化,提出了一个系统的分析框架。该框架包括相关性度量,...人脑活动是在秒级与毫秒级动态变化的,因此采用静态连接方式构建的功能性脑网络,会造成部分与时间相关有效特征的缺失。该文旨在研究情绪变化期间不同大脑区域之间相互作用的时空变化,提出了一个系统的分析框架。该框架包括相关性度量,脑状态分割,代表性时间片段提取以及动态网络构建和分析。首先,利用皮尔逊相关系数量化不同脑区之间的功能连通性。其次,计算两相邻时间点的相关性矩阵之间的奇异值分解(singular value decomposition, SVD)矢量空间距离,确定情绪转换点并对非平稳脑状态进行时间片分割,提取代表性时间片段。最后,基于相关性和频带功率分布构建不同网络模式,利用滑动窗口法估计动态相关模式和动态功率分布变化,然后提取脑动力学的多变量特征并进行分类识别。在SEED数据集上进行的相关实验验证了基于动态功能连接的情感评估方法的可行性,为不同情绪状态下建立脑动态模型开辟了新的途径。展开更多
文摘目的探讨不同程度新生儿缺氧缺血性脑病(hypoxic-ischemic encephalopathy,HIE)患儿脑功能网络的变化,了解该变化对脑功能的影响。方法收集从2017年1月至2020年5月于常州儿童医院新生儿科住院的足月HIE患儿的临床资料,共44例,均进行常规和功能磁共振(functional magnetic resonance image,fMRI)成像扫描,有24例符合入组标准,其中轻度患者(PT1组)11例,中重度患者(PT2组)13例。采用低频振幅(amplitude of low frequency fluctuation,ALFF)比较PT1组和PT2组全脑的ALFF值的差异,并采用脑网络连边分析的方法比较PT1组和PT2组脑功能连接(functional connectivity,FC)的差异。结果在连边分析中,与PT1组相比,PT2组大脑中的右侧辅助运动区与右侧中央前回(Z1=0.39,Z2=-0.08)、右侧舌回与右侧海马(Z1=0.61,Z2=0.20)、左侧距状裂皮层与右侧杏仁核(Z1=0.30,Z2=-0.02)、右侧苍白球与右侧后扣带皮层(Z1=0.33,Z2=0.05)的FC减弱(均P<0.001,未校正)。在低频振幅分析中,PT1组和PT2组全脑的ALFF值差异无统计学意义(P>0.05,FDR校正)。结论中重度组HIE患儿在部分脑区的功能连接存在变化,这些功能连接与运动功能、情绪处理、语言发育、认知功能及学习记忆等有关。
文摘Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore t
基金supported by the National Natural Science Foundation of China,No.60905024
文摘Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.
文摘精准功能磁共振成像(precision functional magnetic resonance imaging,pfMRI)是指在单个个体中收集大量fMRI数据的一种数据采集策略,相较于传统fMRI研究中针对每个被试采集少量数据,之后通过组平均揭示认知过程的脑功能规律或是特定人群共享的脑功能特征的方法,该方法的优势在于能够揭示每个个体的大脑特征,因此日益受到研究者的重视和应用。迄今为止,众多研究采用该方法从功能网络组织的个体差异、个体识别、局部区域的功能定位、个体网络枢纽的识别、个体功能网络的发展与可塑性和临床应用六个角度系统揭示了个体化的脑功能网络组织,这些研究成果对未来脑科学研究具有重要启发。未来研究应该重点探讨现有研究所揭示的个体功能网络组织特点与行为表现的关系,通过对数据分析和成像技术的改进减少该方法所需的扫描时间,并尝试将该方法应用到任务态fMRI和多模态数据的融合研究中。
文摘人脑活动是在秒级与毫秒级动态变化的,因此采用静态连接方式构建的功能性脑网络,会造成部分与时间相关有效特征的缺失。该文旨在研究情绪变化期间不同大脑区域之间相互作用的时空变化,提出了一个系统的分析框架。该框架包括相关性度量,脑状态分割,代表性时间片段提取以及动态网络构建和分析。首先,利用皮尔逊相关系数量化不同脑区之间的功能连通性。其次,计算两相邻时间点的相关性矩阵之间的奇异值分解(singular value decomposition, SVD)矢量空间距离,确定情绪转换点并对非平稳脑状态进行时间片分割,提取代表性时间片段。最后,基于相关性和频带功率分布构建不同网络模式,利用滑动窗口法估计动态相关模式和动态功率分布变化,然后提取脑动力学的多变量特征并进行分类识别。在SEED数据集上进行的相关实验验证了基于动态功能连接的情感评估方法的可行性,为不同情绪状态下建立脑动态模型开辟了新的途径。
