UNASSIGNED: Spatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male-female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis.
UNASSIGNED: The proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients.
UNASSIGNED: The proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience.
■时空多层FCN通过将滑动时间窗方法与图论和超图理论相结合,实现了脑网络时空动态特性的高阶表示。提出的四个丰富俱乐部尺度是基于丰富俱乐部节点身份的动态变化,提供了从时间和空间角度对脑网络的拓扑动态特性的参数化描述。在三个独立差异分析实验中验证了所提出的方法:男女性别差异分析,自闭症谱系障碍(ASD)患者的异常分析,和个体差异分析。
■所提出的方法产生的结果与先前的相关研究一致,并揭示了一些创新的发现。例如,特定白质区域的动态拓扑特征有效地反映了个体差异。基底神经节内部功能连接异常的增加可能是ASD患者重复或限制性行为发生的原因。
■所提出的方法为构建全脑时空多层FCN并对其动态拓扑结构进行分析提供了有效的方法。时空多层FCN的动态拓扑特征可能为神经科学中的生理变异和病理异常提供新的见解。