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
脑小血管病(cerebral small vessel disease,CSVD)是导致VCI的最常见原因,VCI起病隐匿,渐进发展,早期表现为执行和信息处理速度减慢,晚期可累及记忆、语言、视空间等多个认知领域,最终可能发展为痴呆[1-2]。CSVD导致的皮质下型VCI是最...脑小血管病(cerebral small vessel disease,CSVD)是导致VCI的最常见原因,VCI起病隐匿,渐进发展,早期表现为执行和信息处理速度减慢,晚期可累及记忆、语言、视空间等多个认知领域,最终可能发展为痴呆[1-2]。CSVD导致的皮质下型VCI是最多见的VCI亚型,占VCI患病率的50%~70%,其病理机制目前仍不清楚,且缺乏特异性的治疗方法,因此早期识别、诊断和干预尤为重要[3]。VCI的诊断需依赖于多领域的神经心理学评估以及影像检查,2013年国际CSVD影像共识把新发皮质下小梗死、血管源性腔隙、血管源性脑白质高信号、血管周围间隙、脑微出血和脑萎缩作为CSV D的结构影像学标志物[4]。展开更多
The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resti...The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.展开更多
A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifet...A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.展开更多
A new wave of networks labeled Peer-to-Peer(P2P) networks attracts more researchers and rapidly becomes one of the most popular applications.In order to matching P2 P logical overlay network with physical topology,the...A new wave of networks labeled Peer-to-Peer(P2P) networks attracts more researchers and rapidly becomes one of the most popular applications.In order to matching P2 P logical overlay network with physical topology,the position-based topology has been proposed.The proposed topology not only focuses on non-functional characteristics such as scalability,reliability,fault-tolerance,selforganization,decentralization and fairness,but also functional characteristics are addressed as well.The experimental results show that the hybrid complex topology achieves better characteristics than other complex networks' models like small-world and scale-free models;since most of the real-life networks are both scale-free and small-world networks,it may perform well in mimicking the reality.Meanwhile,it reveals that the authors improve average distance,diameter and clustering coefficient versus Chord and CAN topologies.Finally,the authors show that the proposed topology is the most robust model,against failures and attacks for nodes and edges,versus small-world and scale-free networks.展开更多
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。
文摘脑小血管病(cerebral small vessel disease,CSVD)是导致VCI的最常见原因,VCI起病隐匿,渐进发展,早期表现为执行和信息处理速度减慢,晚期可累及记忆、语言、视空间等多个认知领域,最终可能发展为痴呆[1-2]。CSVD导致的皮质下型VCI是最多见的VCI亚型,占VCI患病率的50%~70%,其病理机制目前仍不清楚,且缺乏特异性的治疗方法,因此早期识别、诊断和干预尤为重要[3]。VCI的诊断需依赖于多领域的神经心理学评估以及影像检查,2013年国际CSVD影像共识把新发皮质下小梗死、血管源性腔隙、血管源性脑白质高信号、血管周围间隙、脑微出血和脑萎缩作为CSV D的结构影像学标志物[4]。
基金supported by China Scholarship Council(201306455001)the National Natural Science Foundation of China(61271407)the Fundamental Research Funds for the Central Universities(16CX06050A)
文摘The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.
基金Projects(61101104,61100213) supported by the National Natural Science Foundation of ChinaProject(NY211050) supported by Fund of Nanjing University of Posts and Telecommunications,China
文摘A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime.It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios.Besides,a self-healing scheme that enhances the robustness of the network was provided.It makes the topology tolerate more dead nodes than existing algorithms.Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.
文摘A new wave of networks labeled Peer-to-Peer(P2P) networks attracts more researchers and rapidly becomes one of the most popular applications.In order to matching P2 P logical overlay network with physical topology,the position-based topology has been proposed.The proposed topology not only focuses on non-functional characteristics such as scalability,reliability,fault-tolerance,selforganization,decentralization and fairness,but also functional characteristics are addressed as well.The experimental results show that the hybrid complex topology achieves better characteristics than other complex networks' models like small-world and scale-free models;since most of the real-life networks are both scale-free and small-world networks,it may perform well in mimicking the reality.Meanwhile,it reveals that the authors improve average distance,diameter and clustering coefficient versus Chord and CAN topologies.Finally,the authors show that the proposed topology is the most robust model,against failures and attacks for nodes and edges,versus small-world and scale-free networks.
