Selective Aberrant Functional–Structural Coupling of Multiscale Brain Networks in Subcortical Vascular Mild Cognitive Impairment

Subcortical vascular mild cognitive impairment(svMCI)is a common prodromal stage of vascular dementia.Although mounting evidence has suggested abnormalities in several single brain network metrics,few studies have explored the consistency between functional and structural connectivity networks in svMCI.Here,we constructed such networks using resting-state f MRI for functional connectivity and diffusion tensor imaging for structural connectivity in 30 patients with svMCI and 30 normal controls.The functional networks were then parcellated into topological modules,corresponding to several well-defined functional domains.The coupling between the functional and structural networks was finally estimated and compared at the multiscale network level(whole brain and modular level).We found no significant intergroup differences in the functional–structural coupling within the whole brain;however,there was significantly increased functional–structural coupling within the dorsal attention module and decreased functional–structural coupling within the ventral attention module in the svMCI group.In addition,the svMCI patients demonstrated decreased intramodular connectivity strength in the visual,somatomotor,and dorsal attention modules as well as decreased intermodular connectivity strength between several modules in the functional network,mainly linking the visual,somatomotor,dorsal attention,ventral attention,and frontoparietal control modules.There was no significant correlation between the altered module-level functional–structural coupling and cognitive performance in patients with svMCI.These findings demonstrate for the first time that svMCI is reflected in a selective aberrant topological organization in multiscale brain networks and may improve our understanding of the pathophysiological mechanisms underlying svMCI.

Identification and classification of traditional Chinese medicine syndrome types among senior patients with vascular mild cognitive impairment using latent tree analysis

OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.