Network Connectivity Strength Research Articles

Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum

Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.

Visual stimulation and frequency of focal neurological symptoms engage distinctive neurocognitive resources in migraine with aura patients: a study of resting-state functional networks

IntroductionSeveral functional neuroimaging studies on healthy controls and patients with migraine with aura have shown that the activation of functional networks during visual stimulation is not restricted to the striate system, but also includes several extrastriate networks.MethodsBefore and after 4 min of visual stimulation with a checkerboard pattern, we collected functional MRI in 21 migraine with aura (MwA) patients and 18 healthy subjects (HS). For each recording session, we identified independent resting-state networks in each group and correlated network connection strength changes with clinical disease features.ResultsBefore visual stimulation, we found reduced connectivity between the default mode network and the left dorsal attention system (DAS) in MwA patients compared to HS. In HS, visual stimulation increases functional connectivity between the independent components of the bilateral DAS and the executive control network (ECN). In MwA, visual stimulation significantly improved functional connectivity between the independent component pairs salience network and DAS, and between DAS and ECN. The ECN Z-scores after visual stimulation were negatively related to the monthly frequency of aura.ConclusionsIn individuals with MwA, 4 min of visual stimulation had stronger cognitive impact than in healthy people. A higher frequency of aura may lead to a diminished ability to obtain cognitive resources to cope with transitory but important events like aura-related focal neurological symptoms.

Altered dynamic functional network connectivity within default mode network of epileptic children with generalized tonic-clonic seizures

ObjectiveGeneralized tonic-clonic seizures (GTCS) is a group of epileptic disorders characterized by widespread generalized spike-and-waves discharges along with unresponsiveness and convulsions. Abnormal connectivity in the DMN is the common findings in children with generalized epilepsy. However, the neural mechanisms underlying the altered brain connectivity of DMN in children with GTCS remain unclear. The aim of the current study was to explore the temporal properties of functional connectivity states by dynamic functional connectivity (dFC) within the DMN of GTCS children. MethodsWe collected resting-state functional MRI data from 22 GTCS children and 29 age-matched healthy controls. Sliding window approach and k-mean clustering analysis were applied to analyze the dFC and identify transient states of the DMN. Furthermore, the relationship between the dynamic properties and clinical features was assessed. ResultsThe dFC analyses identified two reoccurring states: a more frequent and weak connected state (State 1) and a less frequent and strong connected state (State 2). Relative to the normal control, GTCS children spent more time in State 1 showing weak connections and spent less time in State 2 showing strong connections. Dynamic functional network connectivity strength within the DMN showed both increase and decrease in patient group. In addition, the changes of dynamic metric were found to be correlated with epilepsy duration. SignificantOur findings imply abnormal interactions and the state dynamics in DMN of the children with GTCS. These disruptions of temporal dynamic in DMN may provide significance for understanding the neural mechanism underlying the GTCS in children and suggest that dFC method can be considered as a valuable tool in children with epilepsy.

Changes in specific and nonspecific psychopathology network structure after intensive cognitive behavior therapy in patients with anorexia nervosa.

This study aimed to compare eating disorder-specific and nonspecific clinical features in patients with anorexia nervosa before and after intensive enhanced cognitive behavior therapy (CBT-E) via network analysis. All consecutive patients admitted to intensive CBT-E were eligible, and the sample comprised patients aged ≥16 years who completed a 20-week intensive CBT-E program. Body mass index (BMI), Eating Disorder Examination Questionnaire and Brief Symptoms Inventory responses were gathered at baseline and end of treatment, and used to generate statistical networks of the connections between symptoms (nodes) and the strength and centrality thereof. A total of 214 patients were included. Most nodes had relatively similar centrality compared to other nodes in the networks. "Eating concern" and "phobic anxiety" showed the greatest bridge centrality at both time points. No differences were found between baseline and the end of treatment in either global network or individual connection strengths. These findings suggest that some clinical expressions not specific to eating-disorder psychopathology remain strongly connected in the generalized network of patients with anorexia nervosa after CBT-E. Future research should examine whether additional procedures specifically designed to target these symptoms should be integrated into this and other treatments.

Robustness analysis of cyber-coupled power systems with considerations of interdependence of structures, operations and dynamic behaviors

The failure propagation of a networked system is profoundly affected by the operation and dynamic behavior of its constituent systems. In this paper, we propose a novel network-based model to investigate the cascading failure of cyber-coupled power systems. Unlike existing models that assume oversimplified network functions, operational characteristics and failure evolution, our proposed model considers the practical differences between a communication network and a power network in terms of network structure, physical operation and dynamic behavior. A practical trip mechanism is derived according to the instantaneous data transmission overload and the stochastic power flow overload. The effects of communication network connection strength and coupling patterns on the robustness of interdependent systems are also studied. Our study shows that the thermal memory effect of power lines aggravates the failure propagation, and that the robustness of the interdependent system is strongly related to the coupled communication network’s tolerance. Furthermore, coupling patterns based on network similarity have better inhibition effects on cascading failure under random attacks, and node destructiveness is a suitable coupling similarity index that can be used to improve the robustness of the system. However, the strategy is inapplicable when the system is under intentional attacks.

Adaptive rewiring in nonuniform coupled oscillators.

Structural plasticity of the brain can be represented in a highly simplified form as adaptive rewiring, the relay of connections according to the spontaneous dynamic synchronization in network activity. Adaptive rewiring, over time, leads from initial random networks to brain-like complex networks, that is, networks with modular small-world structures and a rich-club effect. Adaptive rewiring has only been studied, however, in networks of identical oscillators with uniform or random coupling strengths. To implement information-processing functions (e.g., stimulus selection or memory storage), it is necessary to consider symmetry-breaking perturbations of oscillator amplitudes and coupling strengths. We studied whether nonuniformities in amplitude or connection strength could operate in tandem with adaptive rewiring. Throughout network evolution, either amplitude or connection strength of a subset of oscillators was kept different from the rest. In these extreme conditions, subsets might become isolated from the rest of the network or otherwise interfere with the development of network complexity. However, whereas these subsets form distinctive structural and functional communities, they generally maintain connectivity with the rest of the network and allow the development of network complexity. Pathological development was observed only in a small proportion of the models. These results suggest that adaptive rewiring can robustly operate alongside information processing in biological and artificial neural networks.

Disruptions of the Human Connectome Associated With Hemispatial Neglect.

Background and ObjectivesHemispatial neglect is a heterogeneous and complex disorder that can be classified by frame of reference for “left” vs “right,” including viewer-centered neglect (VCN, affecting the contralesional side of the view), stimulus-centered neglect (SCN, affecting the contralesional side of the stimulus, irrespective of its location with respect to the viewer), or both. We investigated the effect of acute stroke lesions on the connectivity of neural networks that underlie VCN or SCN.MethodsA total of 174 patients within 48 hours of acute right hemispheric infarct underwent a detailed hemispatial neglect assessment that included oral reading, scene copy, line cancellation, gap detection, horizontal line bisection tests, and MRI. Each patient's connectivity map was generated. We performed a linear association analysis between network connectivity strength and continuous measures of neglect to identify lesion-induced disconnections associated with the presence or severity of VCN and SCN. Results were corrected for multiple comparisons.ResultsAbout 42% of the participants with right hemisphere stroke had at least one type of neglect. The presence of any type of neglect was associated with lesions to tracts connecting the right inferior parietal cortex, orbitofrontal cortex, and right thalamus to other right-hemispheric structures. VCN only was strongly associated with tracts connecting the right putamen to other brain regions and tracts connecting right frontal regions with other brain regions. The presence of both types of neglect was most strongly associated with tracts connecting the right inferior and superior parietal cortex to other brain regions and those connecting left or right mesial temporal cortex to other brain regions.DiscussionOur study provides new evidence for the specific white matter tracts where disruption can cause hemispatial neglect in a relatively large number of participants and homogeneous time after onset. We obtained MRI and behavioral testing acutely, before the opportunity for rehabilitation or substantial recovery.Classification of EvidenceThis study provides Class II evidence that damage to specific white matter tracts identified on MRI are associated with the presence of neglect following right hemispheric stroke.

Deciphering the non-linear impact of Al on chemical durability of silicate glass

The role of Al in aluminosilicate glasses remains somewhat a mystery: at low concentrations, it increases the resistance to hydrolysis of the glass, whereas at high concentrations an opposite effect is observed. To understand the origin of the phenomenon on a fundamental atomistic scale, we performed 577 MD simulations and applied potential mean force (PMF) calculations to estimate the activation barriers for hydrolysis and to statistically correlate them with local structural features of the glass. Models of pure silicate and aluminosilicate glasses are constructed and investigated. PMF simulation results are further validated by the experimental measurements and revealed that Al is very easy to dissociate, but it also increases the glass chemical durability through significantly increasing both the strength of Si and network connectivity of the glass. In contrast, at high Al concentration, preferential dissolution of Al weakens the silicate network, which it supposes to strengthen, and so the glass resistance becomes poor. Through PMF calculations, we evaluated the activation barriers for dissociating bonds around Al as 0.49 eV, which is less than a half of the energy to dissociate bonds around Si in pure silicate (1.22 eV) and around Si in aluminosilicate glass (1.34 eV), all these energy differences being statistically significant. Molecular structural level investigation revealed that Si with Al as a second neighbor in the glass network has a significantly higher activation energy for dissociation than Si in pure silicate glass. The proposed approach opens the way to the development of quantitative predictive models of glass durability.

Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy.

Background/Introduction:Widespread network disruption has been hypothesized to be an important predictor of outcomes in patients with refractory temporal lobe epilepsy (TLE). Most studies examining functional network disruption in epilepsy have largely focused on the symmetric bidirectional metrics of the strength of network connections. However, a more complete description of network dysfunction impacts in epilepsy requires an investigation of the potentially more sensitive directional metrics of information flow.Methods:This study describes a whole-brain magnetoencephalography-imaging approach to examine resting-state directional information flow networks, quantified by phase-transfer entropy (PTE), in patients with TLE compared with healthy controls (HCs). Associations between PTE and clinical characteristics of epilepsy syndrome are also investigated.Results:Deficits of information flow were specific to alpha-band frequencies. In alpha band, while HCs exhibit a clear posterior-to-anterior directionality of information flow, in patients with TLE, this pattern of regional information outflow and inflow was significantly altered in the frontal and occipital regions. The changes in information flow within the alpha band in selected brain regions were correlated with interictal spike frequency and duration of epilepsy.Conclusions:Impaired information flow is an important dimension of network dysfunction associated with the pathophysiological mechanisms of TLE.Impact statementA complete description of network dysfunction in temporal lobe epilepsy (TLE) requires investigation of the flow of information in brain networks. In this whole-brain magnetoencephalography imaging study, using an information theory measure, phase-transfer entropy, we examine the strength and directionality of information flow in patients with TLE. Abnormal information flow was documented and was associated with clinical measures related to epilepsy in certain brain regions. The approach described here may provide a useful framework to investigate network dysfunction in other neurological and psychiatric disorders.

Different effects of the DRD4 genotype on intrinsic brain network connectivity strength in drug-na\xefve children with ADHD and healthy controls

The dopamine D4 receptor gene (DRD4) has been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). Recent studies have linked DRD4 to functional connectivity among specific brain regions. The current study aimed to compare the effects of the DRD4 genotype on functional integrity in drug-naïve ADHD children and healthy children. Resting-state functional MRI images were acquired from 49 children with ADHD and 37 healthy controls (HCs). We investigated the effects of the 2-repeat allele of DRD4 on brain network connectivity in both groups using a parameter called the degree of centrality (DC), which indexes local functional relationships across the entire brain connectome. A voxel-wise two-way ANCOVA was performed to examine the diagnosis-by-genotype interactions on DC maps. Significant diagnosis-by-genotype interactions with DC were found in the temporal lobe, including the left inferior temporal gyrus (ITG) and bilateral middle temporal gyrus (MTG) (GRF corrected at voxel level p < 0.001 and cluster level p < 0.05, two-tailed). With the further subdivision of the DC network according to anatomical distance, additional brain regions with significant interactions were found in the long-range DC network, including the left superior parietal gyrus (SPG) and right middle frontal gyrus (MFG). The post-hoc pairwise analysis found that altered network centrality related to DRD4 differed according to diagnostic status (p < 0.05). This genetic imaging study suggests that the DRD4 genotype regulates the functional integration of brain networks in children with ADHD and HCs differently. This may have important implications for our understanding of the role of DRD4 in altering functional connectivity in ADHD subjects.

Change in eating-disorder psychopathology network structure in patients with anorexia nervosa treated with intensive cognitive behavior therapy.

This study was designed to compare the change in eating-disorder feature networks in patients with anorexia nervosa after treatment with intensive enhanced cognitive behavior therapy (CBT-E). Patients seeking treatment for anorexia nervosa were consecutively recruited from January 2016 to September 2020. All patients aged ≥16 years who completed a 20-week intensive CBT-E program (13 weeks of inpatient followed by 7 weeks of day-hospital treatment) were included in the study. Body mass index (BMI) was measured, and the Eating Disorder Examination Questionnaire completed for each patient, both at baseline and the end of treatment. The sample comprised 214 patients with anorexia nervosa. Treated patients showed significant improvements in BMI and eating-disorder psychopathology. Network analysis revealed a significant reduction in the network global and connection strengths at the end of treatment. The most central and highly interconnected nodes in the network at baseline were related to the drive for thinness, but at the end of treatment to body image concerns. Some edge connections were significantly stronger at baseline than at the end of treatment, while others were significantly stronger at the end of treatment than at baseline. CBT-E reduces the psychopathology network connectivity over time in patients with anorexia nervosa. The differences in central nodes and edge connections between baseline and end of treatment, not detected by classical inferential analysis, may be informative for understanding the centrality of symptoms in the psychopathology network, and how a specific treatment may act to reduce symptoms and change their connections over time.

Design and Research of Wuhan Urban Railway Network Simulation Calculation Information System Utilizing Big Data

Based on the big data-assisted algorithm, the paper uses the dynamic relationship data of railway passenger flow as a research case, adopts the urban network chain model, and uses the mobility and agglomeration of railway passenger flow between cities as the research entry point to analyse the network connection strength of provincial cities and spatial organization structure characteristics. At the same time, it puts forward the idea of using Wuhan’s rich railway resources as the framework of urban railway network passenger flow intensity simulation calculation system, demonstrates the necessity and feasibility of its construction, and puts forward an implementation plan based on the characteristics of the railway network and urban development for the reference of relevant decision makers.

Influence of Heart Rate Variability on Abstinence-Related Changes in Brain State in Everyday Drinkers

Alcohol consumption is now common practice worldwide, and functional brain networks are beginning to reveal the complex interactions observed with alcohol consumption and abstinence. The autonomic nervous system (ANS) has a well-documented relationship with alcohol use, and a growing body of research is finding links between the ANS and functional brain networks. This study recruited everyday drinkers in an effort to uncover the relationship between alcohol abstinence, ANS function, and whole brain functional brain networks. Participants (n = 29), 24–60 years-of-age, consumed moderate levels of alcohol regularly (males 2.4 (±0.26) drinks/day, females 2.3 (±0.96) drinks/day). ANS function, specifically cardiac vagal tone, was assessed using the Porges-Bohrer method for calculating respiratory sinus arrhythmia (PBRSA). Functional brain networks were generated from resting-state MRI scans obtained following 3-day periods of typical consumption and abstinence. A multi-task mixed-effects regression model determined the influences of HRV and drinking state on functional network connectivity. Results showed differences in the relationship between the strength of network connections and clustering coefficients across drinking states, moderated by PBRSA. Increases in connection strength between highly clustered nodes during abstinence as PBRSA increases demonstrates a greater possible range of topological configurations at high PBRSA values. This novel finding begins to shed light on the complex interactions between typical alcohol abstinence and physiological responses of the central and autonomic nervous system.

Altered brain network centrality in patients with mild cognitive impairment: an fMRI study using a voxel-wise degree centrality approach.

Purpose: Previous studies in patients with Alzheimer’s disease have shown amyloid beta accumulation in the brain and abnormal brain activity, with mild cognitive impairment (MCI) in early stages of the disease. The aim of the current study was to investigate functional connectivity in patients with MCI.Methods: We recruited 24 subjects in total, including 12 patients with MCI (6 men and 6 women) and 12 healthy controls (HCs) (6 men and 6 women), matched for age, gender, and lifestyle factors. All subjects underwent resting-state functional magnetic resonance imaging scans and voxel-wise degree centrality (DC) was used to evaluate alterations in the strength of brain network connectivity.Results: The DC value of the left inferior temporal gyrus was lower in MCI but significantly higher in the right fusiform gyrus and the left supplementary motor area, compared with HCs. The DC value in left inferior temporal gyrus correlated positively with disease duration and negatively with Mini-Mental State Examination. ROC curve analysis of brain regions showed acceptable specificity and accuracy of DC values between MCIs and HCs in the area under the curve (right fusiform gyrus, 0.955; left supplementary motor area, 0.992; left inferior temporal gyrus, 1.000).Conclusions: Abnormal functional connectivity in brain regions of patients with MCI may reflect the pathological process of Alzheimer’s disease development and could prove useful in clinical diagnosis and treatment.

Risk Assessment of Knowledge Transfer in Green Building Based on ISM-MICMAC

Green buildings have made a significant contribution to low-carbon and energy-saving. However, green construction projects will face greater risks than traditional construction projects due to their high cost and complex technology. Having important information or knowledge can help the project organization to stifle the risk at the source. This paper intends to improve the efficiency and effectiveness of knowledge transfer by studying the risk assessment in the process of knowledge transfer between project organizations, thereby helping to reduce the risk of green building projects. This paper first explores the influencing factors of knowledge transfer and the interrelationship between the influencing factors by analyzing the existing literature; then uses ISM method and the MICMAC analysis method, to sort out the order and hierarchy of the influencing factors in knowledge transfer, and analyze at the same time their forces of driving and dependences. Then author proposes countermeasures to the risk of knowledge transfer between project organizations. The results show that the two types of risks, low network connection strength and lack of transfer mechanisms, have a greater impact on knowledge transfer, but they are easy to manage. Therefore, construction project managers should identify these factors first and take certain measures to avoid these risks.

Low-Intensity Focused Ultrasound-Mediated Attenuation of Acute Seizure Activity Based on EEG Brain Functional Connectivity.

(1) Background: Ultrasound has been used for noninvasive stimulation and is a promising technique for treating neurological diseases. Epilepsy is a common neurological disorder, that is attributed to uncontrollable abnormal neuronal hyperexcitability. Abnormal synchronized activities can be observed across multiple brain regions during a seizure. (2) Methods: we used low-intensity focused ultrasound (LIFU) to sonicate the brains of epileptic rats, analyzed the EEG functional brain network to explore the effect of LIFU on the epileptic brain network, and continued to explore the mechanism of ultrasound neuromodulation. LIFU was used in the hippocampus of epileptic rats in which a seizure was induced by kainic acid. (3) Results: By comparing the brain network characteristics before and after sonication, we found that LIFU significantly impacted the functional brain network, especially in the low-frequency band. The brain network connection strength across multiple brain regions significantly decreased after sonication compared to the connection strength in the control group. The brain network indicators (the path length, clustering coefficient, small-worldness, local efficiency and global efficiency) all changed significantly in the low-frequency. (4) Conclusions: These results revealed that LIFU could reduce the network connections of epilepsy circuits and change the structure of the brain network at the whole-brain level.

Functional Realignment of Frontoparietal Subnetworks during Divergent Creative Thinking.

Creative cognition has been consistently associated with functional connectivity between frontoparietal control and default networks. However, recent research identified distinct connectivity dynamics for subnetworks within the larger frontoparietal system-one subnetwork (FPCNa) shows positive coupling with the default network and another subnetwork (FPCNb) shows negative default coupling-raising questions about how these networks interact during creative cognition. Here we examine frontoparietal subnetwork functional connectivity in a large sample of participants (n = 171) who completed a divergent creative thinking task and a resting-state scan during fMRI. We replicated recent findings on functional connectivity of frontoparietal subnetworks at rest: FPCNa positively correlated with the default network and FPCNb negatively correlated with the default network. Critically, we found that divergent thinking evoked functional connectivity between both frontoparietal subnetworks and the default network, but in different ways. Using community detection, we found that FPCNa regions showed greater coassignment to a default network community. However, FPCNb showed overall stronger functional connectivity with the default network-reflecting a reversal of negative connectivity at rest-and the strength of FPCNb-default network connectivity correlated with individual creative ability. These findings provide novel evidence of a behavioral benefit to the cooperation of typically anticorrelated brain networks.

Functional connectivity and upper limb function in patients after pediatric arterial ischemic stroke with contralateral corticospinal tract wiring

To develop individualized motor rehabilitation, knowledge of the relationship between neuroplastic reorganization and motor recovery after pediatric arterial ischemic stroke (AIS) is crucial. Thus, we investigated functional connectivity in patients after AIS with good motor outcome and in patients with hemiparesis compared with typically developing peers. We included 18 patients (n = 9 with hemiparesis, n = 9 with good motor outcome) with pediatric AIS in the chronic phase (≥ 2 years after diagnosis, diagnosed > 16 years) and 18 peers matched by age and gender. Participants underwent a standardized motor assessment, single-pulse transcranial magnetic stimulation to determine the type of corticospinal tract wiring, and resting-state functional magnetic resonance imaging to examine motor network connectivity. Corticospinal tract wiring was contralateral in all participants. Patients with hemiparesis had lower interhemispheric connectivity strength compared with patients with good clinical outcome and peers. Patients with good clinical outcome had higher intrahemispheric connectivity strength compared with peers. Further, higher intrahemispheric connectivity was related to better motor outcome in patients. Our findings suggest that better motor outcome after pediatric AIS is related to higher motor network connectivity strength. Thus, resting-state functional connectivity might be predictive for motor recovery after pediatric AIS.

Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration.

Based on the panel data of 41 cities in the Yangtze River Delta from 2008 to 2017, this paper constructs an evaluation indicators system for urban tourism eco-efficiency. By measuring the tourism eco-efficiency in the Yangtze River Delta urban agglomeration, we analyze its spatial-temporal evolution characteristics. Furthermore, the modified gravity model and social network analysis are introduced to explore the spatial network structure of tourism eco-efficiency and its evolution trend.The results show that:(1) The overall eco-efficiency of tourism in the Yangtze River Delta region presents a fluctuating downward trend, among which Jiangsu and Zhejiang have high eco-efficiency, Shanghai and Anhui are relatively low. The gap within the region first increased and then decreased. (2) During this decade, the spatial network structure of tourism eco-efficiency in the Yangtze River Delta has become increasingly loose. The weakening of the network connection strength has led to a decrease in the regional tourism eco-efficiency to a great extent. (3) The network centrality of cities such as Zhoushan, Huzhou, and Huangshan has always maintained a high level, and these cities have firmly occupied the core position of network. (4) The spatial association network of tourism eco-efficiency can be divided into four blocks: “two-way spillover”, “net spillover”, “net benefit” and “agent”. The synergy and spillover effect between various blocks are significant, and there is a spatial polarization trend centered on a few cities. Based on this, this paper puts forward optimization suggestions for the spatial network structure of the Yangtze River Delta urban agglomeration, in anticipation of promoting the improvement of regional tourism eco-efficiency.

The potential role of leukoaraiosis in remodeling the brain network to buffer cognitive decline: a Leukoaraiosis And Disability study from Alzheimer's Disease Neuroimaging Initiative.

Leukoaraiosis (LA) is a phenomenon of the brain that is often observed in elderly people. However, little is known about the role of LA in cognitive impairment in neurodegeneration and disease. This cross-sectional, retrospective Leukoaraiosis And Disability (LADIS) study aimed to characterize the relationship between brain white matter connectivity properties with LA ratings in patients with Alzheimer's disease (AD) as compared with age-matched cognitively normal controls. Patients with AD (n=76) and elderly individuals with normal cognitive (NC) function (n=82) were classified into 3 groups, LA1, LA2, and LA3, according to the rating of their white matter changes (WMCs). Diffusion tensor imaging (DTI) data were analyzed by quantifying and comparing the white matter connectivity properties and gray matter (GM) volume of brain regions of interest (ROIs). The rich-club network properties in the AD LA1 and LA2 groups showed significant patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA1 and LA2 groups, respectively. However, the rich-club network properties in the AD LA3 group showed similar patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA3 group, despite there being significant hippocampal and amygdala atrophic differences between AD patients and NC elders. Compared to the NC LA1 group, the characteristic path length of white matter fiber connectivity in the NC LA3 group was significantly increased, and the brain's global efficiency, clustering coefficient, and network connectivity strength were significantly reduced (P<0.05, respectively). However, no significant differences (P>0.05) were observed in characteristic path length, reduced global efficiency, or the clustering coefficient between the NC LA3 and AD LA1 groups, or between the NC LA3 and AD LA2 groups. Our findings offer some insights into a potential role of LA in cognitive impairment that may predict the development of disability in older adults. The occurrence of LA, an intermediate degenerative change, during neurodegeneration and disease may potentially lead to the remodeling of the brain network through brain plasticity. LA, therefore, representing a possible compensatory mechanism to buffer cognitive decline.