Cortical thickness reveals sex differences in verbal and visuospatial memory.

Although previous studies have reported the sex differences in behavior/cognition and the brain, the sex difference in the relationship between memory abilities and the underlying neural basis in the aging process remains unclear. In this study, we used a machine learning model to estimate the association between cortical thickness and verbal/visuospatial memory in females and males and then explored the sex difference of these associations based on a community-elderly cohort (n = 1153, age ranged from 50.42 to 86.67 years). We validated that females outperformed males in verbal memory, while males outperformed females in visuospatial memory. The key regions related to verbal memory in females include the medial temporal cortex, orbitofrontal cortex, and some regions around the insula. Further, those regions are more located in limbic, dorsal attention, and default-model networks, and are associated with face recognition and perception. The key regions related to visuospatial memory include the lateral prefrontal cortex, anterior cingulate gyrus, and some occipital regions. They overlapped more with dorsal attention, frontoparietal and visual networks, and were associated with object recognition. These findings imply the memory performance advantage of females and males might be related to the different memory processing tendencies and their associated network.

Age-related enhancement of the association between episodic memory and gray matter volume in medial temporal and frontal lobes.

BACKGROUND: Episodic memory (EM) deteriorates as a result of normal aging as well as Alzheimer's disease. The neural underpinnings of such age-related memory impairments in older individuals are not well-understood. Although previous research has unveiled the association between gray matter volume (GMV) and EM in the elderly population, such findings exhibit variances across distinct age cohorts. Consequently, an investigation into the dynamic evolution of this relationship with advancing age is imperative. RESULT: The present study utilized a sliding window approach to examine how the correlation between EM and GMV varied with age in a cross-sectional sample of 926 Chinese older adults. We found that both verbal EM (VEM) and spatial EM (SEM) exhibited positive correlations with GMV in extensive areas primarily in the temporal and frontal lobes and that these correlations typically became stronger with older age. Moreover, there were variations in the strength of the correlation between EM and GMV with age, which differed based on sex and the specific type of EM. Specifically, the association between VEM and GMVs in the insula and parietal regions became stronger with age for females but not for males, whereas the association between SEM and GMVs in the parietal and occipital regions became stronger for males but not for females. At the brain system level, there is a significant age-related increase in the correlations between both types of EM and the GMV of both the anterior temporal (AT) system and the posterior medial (PM) system in male group. In females, both types of EM show stronger age-related correlations with the GMV of the AT system compared to males. CONCLUSIONS: Our study revealed a significant positive correlation between GMV in most regions associated with EM and age, particularly in the frontal and temporal lobes. This discovery offers new insights into the connection between brain structure and the diminishing episodic memory function among older individuals.

Joint contributions from brain activity and activity-independent functional connectivity to working memory aging.

Working memory (WM) impairment has been well characterized in normal aging. Various studies have explored changes in either the regional activity or the interregional connectivity underlying the aging process of WM. We proposed that brain activity and connectivity would independently alter with aging and affect WM performance. WM was assessed with a classical N-back task during functional magnetic resonance imaging in a community-based sample comprising 168 elderly subjects (aged 55-86 years old). Following the rationale of background functional connectivity, we assessed age-related alterations in brain activity and seed-based interregional connectivity independently. Analyses revealed age-related decrease in positive activity of the inferior parietal lobule (IPL) and an increase in the negative activity of the ventral anterior cingulate cortex (ACC), and the local functional dysfunctions were accompanied by alterations in their connectivity to other cortical regions. Importantly, regional activity impairments in the IPL and ACC could mediate age-related effects on accuracy rate and reaction time, respectively, and those effects were further counterbalanced by enhancement of their background functional connectivity. We thus claimed that age-induced alterations in regional activity and interregional connectivity occurred independently and contributed to WM changes in aging. Our findings presented the way brain activity and functional connectivity interact in the late adulthood, thus providing a new perspective for understanding WM and cognitive aging.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly.

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-ß accumulation and cognition. The study explored the relationship between regional amyloid-ß accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-ß accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-ß accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-ß accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

Altered functional coupling between the cerebellum and cerebrum in patients with amnestic mild cognitive impairment.

Cognitive processing relies on the functional coupling between the cerebrum and cerebellum. However, it remains unclear how the 2 collaborate in amnestic mild cognitive impairment (aMCI) patients. With functional magnetic resonance imaging techniques, we compared cerebrocerebellar functional connectivity during the resting state (rsFC) between the aMCI and healthy control (HC) groups. Additionally, we distinguished coupling between functionally corresponding and noncorresponding areas across the cerebrum and cerebellum. The results demonstrated decreased rsFC between both functionally corresponding and noncorresponding areas, suggesting distributed deficits of cerebrocerebellar connections in aMCI patients. Increased rsFC was also observed, which were between functionally noncorresponding areas. Moreover, the increased rsFC was positively correlated with attentional scores in the aMCI group, and this effect was absent in the HC group, supporting that there exists a compensatory mechanism in patients. The current study contributes to illustrating how the cerebellum adjusts its coupling with the cerebrum in individuals with cognitive impairment.

The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: relationship with executive function performance.

BACKGROUND: Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults. OBJECTIVE: This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults. METHODS: We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance. RESULTS: The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits. CONCLUSIONS: Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.

From local properties to brain-wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data.

Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level-dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner.

Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease.

The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aß, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aß, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aß were unique and the regions affected by hypometabolism were widely distributed. Unlike Aß, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aß. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aß (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aß and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.

Prebiotics modulate the microbiota-gut-brain axis and ameliorate cognitive impairment in APP/PS1 mice.

PURPOSE: Prebiotics, including fructo-oligosaccharides (FOS) and galacto-oligosaccharides (GOS), stimulate beneficial gut bacteria and may be helpful for patients with Alzheimer's disease (AD). This study aimed to compare the effects of FOS and GOS, alone or in combination, on AD mice and to identify their underlying mechanisms. METHODS: Six-month-old APP/PS1 mice and wild-type mice were orally administered FOS, GOS, FOS + GOS or water by gavage for 6 weeks and then subjected to relative assays, including behavioral tests, biochemical assays and 16S rRNA sequencing. RESULTS: Through behavioral tests, we found that GOS had the best effect on reversing cognitive impairment in APP/PS1 mice, followed by FOS + GOS, while FOS had no effect. Through biochemical techniques, we found that GOS and FOS + GOS had effects on multiple targets, including diminishing Aß burden and proinflammatory IL-1ß and IL-6 levels, and changing the concentrations of neurotransmitters GABA and 5-HT in the brain. In contrast, FOS had only a slight anti-inflammatory effect. Moreover, through 16S rRNA sequencing, we found that prebiotics changed composition of gut microbiota. Notably, GOS increased relative abundance of Lactobacillus, FOS increased that of Bifidobacterium, and FOS + GOS increased that of both. Furthermore, prebiotics downregulated the expression levels of proteins of the TLR4-Myd88-NF-κB pathway in the colons and cortexes, suggesting the involvement of gut-brain mechanism in alleviating neuroinflammation. CONCLUSION: Among the three prebiotics, GOS was the optimal one to alleviate cognitive impairment in APP/PS1 mice and the mechanism was attributed to its multi-target role in alleviating Aß pathology and neuroinflammation, changing neurotransmitter concentrations, and modulating gut microbiota.

Methodological evaluation of individual cognitive prediction based on the brain white matter structural connectome.

An emerging trend is to use regression-based machine learning approaches to predict cognitive functions at the individual level from neuroimaging data. However, individual prediction models are inherently influenced by the vast options for network construction and model selection in machine learning pipelines. In particular, the brain white matter (WM) structural connectome lacks a systematic evaluation of the effects of different options in the pipeline on predictive performance. Here, we focused on the methodological evaluation of brain structural connectome-based predictions. For network construction, we considered two parcellation schemes for defining nodes and seven strategies for defining edges. For the regression algorithms, we used eight regression models. Four cognitive domains and brain age were targeted as predictive tasks based on two independent datasets (Beijing Aging Brain Rejuvenation Initiative [BABRI]: 633 healthy older adults; Human Connectome Projects in Aging [HCP-A]: 560 healthy older adults). Based on the results, the WM structural connectome provided a satisfying predictive ability for individual age and cognitive functions, especially for executive function and attention. Second, different parcellation schemes induce a significant difference in predictive performance. Third, prediction results from different data sets showed that dMRI with distinct acquisition parameters may plausibly result in a preference for proper fiber reconstruction algorithms and different weighting options. Finally, deep learning and Elastic-Net models are more accurate and robust in connectome-based predictions. Together, significant effects of different options in WM network construction and regression algorithms on the predictive performances are identified in this study, which may provide important references and guidelines to select suitable options for future studies in this field.

Sex Differences in Cortical Morphometry and White Matter Microstructure During Brain Aging and Their Relationships to Cognition.

Changes in brain structure are associated with aging, and accompanied by the gradual deterioration of cognitive functions, which manifests differently in males and females. Here, we quantify the age-related spatial aging patterns of brain gray and white matter structures, their volume reduction rate, their relationships with specific cognitive functions, as well as differences between males and females in a cross-sectional nondementia dataset. We found that both males and females showed extensive age-related decreases in the volumes of most gray matter and white matter regions. Females have larger regions where the volume decreases with age and a greater slope (females: 0.199%, males: 0.183%) of volume decrease in gray matter. For white matter, no significant sex differences were found in age-related regions, and the slope of volume decrease. More significant associations were identified between brain structures and cognition in males during aging than females. This study explored the age-related regional variations in gray matter and white matter, as well as the sex differences in a nondemented elderly population. This study helps to further understand the aging of the brain structure and sex differences in the aging of brain structures and provides new evidence for the aging of nondemented individuals.

Contributions of early-life cognitive reserve and late-life leisure activity to successful and pathological cognitive aging.

BACKGROUND: The identification of factors that specifically influence pathological and successful cognitive aging is a prerequisite for implementing disease prevention and promoting successful aging. However, multi-domain behavioral factors that characterize the difference between successful and pathological cognitive aging are not clear yet. METHODS: A group of community-dwelling older adults (N = 1347, aged 70-88 years) in Beijing was recruited in this cross-sectional study, and a sub-cohort was further divided into successful cognitive aging (SCA, N = 154), mild cognitive impairment (MCI, N = 256), and cognitively normal control (CNC, N = 173) groups. Analyses of variance, regression models with the Shapley value algorithm, and structural equation model (SEM) analyses were conducted to determine specific influencing factors and to evaluate their relative importance and interacting relationships in altering cognitive performance. RESULTS: We found that abundant early-life cognitive reserve (ECR, including the level of education and occupational attainment) and reduced late-life leisure activity (LLA, including mental, physical, and social activities) were distinct characteristics of SCA and MCI, respectively. The level of education, age, mental activity, and occupational attainment were the top four important factors that explained 31.6% of cognitive variability. By SEM analyses, we firstly found that LLA partially mediated the relationship between ECR and cognition; and further multi-group SEM analyses showed ECR played a more direct role in the SCA group than in the MCI group: in the SCA group, only the direct effect of ECR on cognition was significant, and in the MCI group, direct effects between ECR, LLA and cognition were all significant. CONCLUSIONS: Results of this large-sample community-based study suggest it is important for older adults to have an abundant ECR for SCA, and to keep a high level of LLA to prevent cognitive impairment. This study clarifies the important rankings of behavioral characteristics of cognitive aging, and the relationship that ECR has a long-lasting effect on LLA and finally on cognition, providing efficient guidance for older adults to improve their cognitive function and new evidence to explain the heterogeneity of cognitive aging.

Quantum Correlation Swapping between Two Werner States Undergoing Local and Nonlocal Unitary Operations.

In this paper, quantum correlation (QC) swapping between two Werner-like states, which are transformed from Werner states undergoing local and nonlocal unitary operations, are studied. Bell states measures are performed in the middle node to realize the QC swapping and correspondingly final correlated sates are obtained. Two different QC quantifiers, i.e., measurement-induced disturbance (MID) and ameliorated MID, are employed to characterize and quantify all the concerned QCs in the swapping process. All QCs in the concerned states are evaluated analytically and numerically. Correspondingly, their characteristics and properties are exposed in detail. It is exposed that, through the QC swapping process, one can obtain the long-distance QC indeed. Moreover, the similarities of monotony features of MID and AMID between the initial states and final states are exposed and analyzed.

Relationship between the disrupted topological efficiency of the structural brain connectome and glucose hypometabolism in normal aging.

Normal aging is accompanied by structural degeneration and glucose hypometabolism in the human brain. However, the relationship between structural network disconnections and hypometabolism in normal aging remains largely unknown. In the present study, by combining MRI and PET techniques, we investigated the metabolic mechanism of the structural brain connectome and its relationship with normal aging in a cross-sectional, community-based cohort of 42 cognitively normal elderly individuals aged 57-84 years. The structural connectome was constructed based on diffusion MRI tractography, and the network efficiency metrics were quantified using graph theory analyses. FDG-PET scanning was performed to evaluate the glucose metabolic level in the cortical regions of the individuals. The results of this study demonstrated that both network efficiency and cortical metabolism decrease with age (both p < 0.05). In the subregions of the bilateral thalamus, significant correlations between nodal efficiency and cortical metabolism could be observed across subjects. Individual-level analyses indicated that brain regions with higher nodal efficiency tend to exhibit higher metabolic levels, implying a tight coupling between nodal efficiency and glucose metabolism (r = 0.56, p = 1.15 × 10-21). Moreover, efficiency-metabolism coupling coefficient significantly increased with age (r = 0.44, p = 0.0046). Finally, the main findings were also reproducible in the ADNI dataset. Together, our results demonstrate a close coupling between structural brain connectivity and cortical metabolism in normal elderly individuals and provide new insight that improve the present understanding of the metabolic mechanisms of structural brain disconnections in normal aging.

Disrupted anterior and posterior hippocampal structural networks correlate impaired verbal memory and spatial memory in different subtypes of mild cognitive impairment.

BACKGROUND AND PURPOSE: The anterior and posterior hippocampal networks represent verbal and spatial memory, respectively, and may play different roles in the pathological mechanism of amnestic mild cognitive impairment (aMCI) and non-amnestic MCI (naMCI), which has not been explored. METHODS: A total of 990 older adults with 791 normal controls (NCs) (65 ± 6 years, 502 women), 140 aMCI (66 ± 7 years, 84 women) and 59 naMCI (66 ± 7 years, 38 women) were included. A multivariate method, partial least squares, was used to assess the structural covariance networks of the anterior hippocampus (aHC) and posterior hippocampus (pHC), and their relationships with verbal memory and spatial memory in the three groups. RESULTS: Three aHC and pHC structural covariance network patterns emerged: (1) the age pattern; (2) the specific aMCI pattern; and (3) the spatial memory pattern. Furthermore, aMCI patients had more extensive and severe damage in the three patterns, and correlated with greater decline in verbal memory, which was mainly characterized by the aHC network. CONCLUSIONS: The aMCI and naMCI showed different patterns and damage in the structural covariance networks, and functional segregation of the aHC and pHC networks still exists in the process of pathological aging. A potential neural explanation is provided for the conversion of aMCI and naMCI into different types of dementia in the future.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients.

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Age-Related Decline in the Topological Efficiency of the Brain Structural Connectome and Cognitive Aging.

Brain disconnection model has been proposed as a possible neural mechanism for cognitive aging. However, the relationship between structural connectivity degeneration and cognitive decline with normal aging remains unclear. In the present study, using diffusion MRI and tractography techniques, we report graph theory-based analyses of the brain structural connectome in a cross-sectional, community-based cohort of 633 cognitively healthy elderly individuals. Comprehensive neuropsychological assessment of the elderly subjects was performed. The association between age, brain structural connectome, and cognition across elderly individuals was examined. We found that the topological efficiency, modularity, and hub integration of the brain structural connectome exhibited a significant decline with normal aging, especially in the frontal, parietal, and superior temporal regions. Importantly, network efficiency was positively correlated with attention and executive function in elderly subjects and had a significant mediation effect on the age-related decline in these cognitive functions. Moreover, nodal efficiency of the brain structural connectome showed good performance for the prediction of attention and executive function in elderly individuals. Together, our findings revealed topological alterations of the brain structural connectome with normal aging, which provides possible structural substrates underlying cognitive aging and sensitive imaging markers for the individual prediction of cognitive functions in elderly subjects.

Early prevention of cognitive impairment in the community population: The Beijing Aging Brain Rejuvenation Initiative.

Facing considerable challenges associated with aging and dementia, China urgently needs an evidence-based health-care system for prevention and management of dementia. The Beijing Aging Brain Rejuvenation Initiative (BABRI) is a community-based cohort study initiated in 2008 that focuses on asymptomatic stages of dementia, aims to develop community-based prevention strategies for cognitive impairment, and provides a platform for scientific research and clinical trials. Thus far, BABRI has recruited 10,255 participants (aged 50 and over, 60.3% female), 2021 of whom have been followed up at least once at a 2- or 3-year interval. This article presents aims and study design of BABRI; summarizes preliminary behavioral and neuroimaging findings on mild cognitive impairment (MCI) and results of clinical trials on MCI; and discusses issues concerning early prevention in community, MCI diagnosis methods, and applications of database of aging and dementia. BABRI is proposed to build a systematic framework on brain health in old age.

Increasing Quantum Correlations Based on Measurement-Induced Disturbance via a Swapping Procedure with Two-Qubit Mixed States.

In this paper, quantum correlation (QC) swapping for certain separable two-qubit mixed states is treated. A QC quantifier, measurement-induced disturbance (MID) (Luo in Phys Rev A 77:022301, 2008), is employed to characterize and quantify QCs in the relevant states. Properties of all QCs in the swapping process are revealed. Particularly, it is found that MID can be increased through QC swapping for certain separable two-qubit mixed states.

Network topology and machine learning analyses reveal microstructural white matter changes underlying Chinese medicine Dengzhan Shengmai treatment on patients with vascular cognitive impairment.

With the increasing incidence of cerebrovascular diseases and dementia, considerable efforts have been made to develop effective treatments on vascular cognitive impairment (VCI), among which accumulating practice-based evidence has shown great potential of the traditional Chinese medicine (TCM). Current randomized double-blind controlled trial has been designed to evaluate the 6-month treatment effects of Dengzhan Shengmai (DZSM) capsules, one TCM herbal preparations on VCI, and to explore the underlying neural mechanisms with graph theory-based analysis and machine learning method based on diffusion tensor imaging (DTI) data. A total of 82 VCI patients were recruited and randomly assigned to drug (45 with DZSM) and placebo (37 with placebo) groups, and neuropsychological and neuroimaging data were acquired at baseline and after 6-month treatment. After treatment, compared to the placebo group, the drug groups showed significantly improved performance in Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-cog) score (p < 0.001) and the other cognitive domains. And with the reconstruction of white matter structural network, there were more streamlines connecting the left thalamus and right hippocampus in the drug groups (p < 0.001 uncorrected), with decreasing nodal efficiency of the right olfactory associated with slower decline in the general cognition (r = -0.364, p = 0.048). Moreover, support vector machine classification analyses revealed significant white matter network alterations after treatment in the drug groups (accuracy of baseline vs. 6-month later, 68.18 %). Taking together, the present study showed significant efficacy of DZSM treatment on VCI, which might result from white matter microstructure alterations and the topological changes in brain structural network.