Characteristic Path Research Articles

Individual-based morphological brain network changes in children with Rolandic epilepsy

ObjectiveTo investigate the local cortical morphology and individual-based morphological brain networks (MBNs) changes in children with Rolandic epilepsy (RE). MethodsBased on the structural MRI data of 56 children with RE and 56 healthy controls (HC), we constructed four types of individual-based MBNs using morphological indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]). The global and nodal properties of the brain networks were analyzed using graph theory. The between-group difference in local morphology and network topology was estimated, and partial correlation analysis was further analyzed. ResultsCompared with the HC, children with RE showed regional GI increases in the right posterior cingulate gyrus and SD increases in the right anterior cingulate gyrus and medial prefrontal cortex. Regarding the network level, RE exhibited increased characteristic path length in CT-based and FD-based networks, while decreased FD-based network node efficiency in the right inferior frontal gyrus. No significant correlation between altered morphological features and clinical variables was found in RE. ConclusionsThese findings indicated that children with RE have disrupted morphological brain network organization beyond local morphology changes. SignificanceThe present study could provide more theoretical basis for exploring the neuropathological mechanisms in RE.

Structural characteristics and spatiotemporal changes of a reticular river network based on complex network theory

eticular river networks, characterized by a dense pattern of rivers and loop structures, are primarily found in lower river delta plains and are being modified due to rapid population growth and urbanization. This change impacts the distribution of water resources and could result in more frequent and severe floods. Therefore, accurately characterizing the structure of river networks is crucial. In this study, the structure and its changes of a typical plain reticular river network in the Lixia River hinterland area (LRHA), China, were evaluated in the 1960s, 1970s, 1980s, 2009, and 2016 using complex network theory tools at global and local scales. First, we constructed a complex network model by generalizing river sources, outlets, and confluences as nodes and channels as edges. By comparing with the equivalent random networks, it is found that the river networks of LRHA have large clustering coefficients and short characteristic path lengths. These characteristics classify it as a small-world network within complex networks, which is notably efficient for water and material transportation. Second, at the global scale, the global efficiency in complex network theory considers the interconnectivity between nodes and assesses the potential paths between them, effectively reflecting the connectivity status of the river network. At the local scale, the betweenness centrality of a complex network can reflect the control ability of water and material transportation at river nodes. After the 1970s, constructing several new mainstem rivers gradually shifted nodes with high betweenness centrality towards the north–south flowing rivers. In addition, we used Moran’s I to quantify the spatial clustering of the network’s indicators and found that degree and betweenness centrality exhibited higher spatial clustering, with mean Moran’s I values of 0.398 and 0.300, respectively. Finally, we compared the structure of river networks in urban versus rural areas and the mainstem versus tributary streams. We found that urban river networks and mainstem rivers exhibit a higher degree of betweenness centrality, resulting in a greater capacity to regulate water and material cycles within the river network. According to the research findings, complex network theory has been proven to effectively evaluate the structure of reticular river networks at various scales. It enhances our comprehension of the river network’s structure and assists managers in gaining a deeper understanding of how the river network structure influences the distribution of water resources.

Deciphering the key factors affecting pesticide residue risk in vegetable ecosystem

Soil contamination, particularly from pesticide residues, presents a significant challenge to the sustainable development of agricultural ecosystems. Identifying the key factors influencing soil pesticide residue risk and implementing effective measures to mitigate their risks at the source are essential. Here, we collected soil samples and conducted a comprehensive survey among local farmers in the Three Gorges Reserve Area, a major agricultural production region in Southwest China. Subsequently, employing a dual analytical approach combining structural equation modeling (SEM) and random forest modeling (RFM), we examined the effects of various factors on pesticide residue accumulation in vegetable ecosystems. Our SEM analysis revealed that soil characteristics (path coefficient 0.85) and cultivation factor (path coefficient 0.84) had the most significant effect on pesticide residue risk, while the farmer factors indirectly influenced pesticide residues by impacting both cultivation factors and soil characteristics. Further exploration using RFM identified the three most influential factors contributing to pesticide residue risk as cation exchange capacity (CEC) (account for 18.84%), cultivation area (account for 14.12%), and clay content (account for 13.01%). Based on these findings, we carried out experimental trials utilizing Integrated Pest Management (IPM) technology, resulting in a significant reduction in soil pesticide residues and notable improvements in crop yields. Therefore, it is recommended that governmental efforts should prioritize enhanced training for vegetable farmers, promotion of eco-friendly plant protection methods, and regulation of agricultural environments to ensure sustainable development.

Research on Lifting Path Planning Algorithms for Intelligent Cranes

Path planning algorithm is one of the key technologies in the study of intelligent cranes, and a good path planning algorithm can quickly plan a safe and collision-free path. The current research status of path planning technology in the field of crane lifting path planning is reviewed. The implementation principles of various types of algorithms are analysed, and the current research status of mainstream path planning algorithms is summarized. According to the characteristics of crane path planning algorithms, crane path planning algorithms are classified into traditional path planning algorithms, intelligent path planning algorithms and deep reinforcement learning algorithms. For each type of algorithm is analysed and summarized, and the development of crane path planning algorithms is looked forward to, hoping to provide reference for related research.

Fatigue in Parkinson's Disease Is Due to Decreased Efficiency of the Frontal Network: Quantitative EEG Analysis.

Fatigue is a common, debilitating nonmotor symptom of Parkinson's disease (PD), but its mechanism is poorly understood. We aimed to determine whether electroencephalography (EEG) could objectively measure fatigue and to explore the pathophysiology of fatigue in PD. We studied 32 de novo PD patients who underwent EEG. We compared brain activity between 19 PD patients without fatigue and 13 PD patients with fatigue via EEG power spectra and graphs, including the global efficiency, characteristic path length, clustering coefficient, small-worldness, local efficiency, degree centrality, closeness centrality, and betweenness centrality. No significant differences in absolute or relative power were detected between PD patients without or with fatigue (all p > 0.02, Bonferroni-corrected). According to our network analysis, brain network efficiency differed by frequency band. Generally, the brain network in the frontal area for theta and delta bands showed greater efficiency, and in the temporal area, the alpha1 band was less efficient in PD patients without fatigue (p < 0.0001, p = 0.0011, and p = 0.0007, respectively, Bonferroni-corrected). Our study suggests that PD patients with fatigue have less efficient networks in the frontal area than PD patients without fatigue. These findings may explain why fatigue is common in PD, a frontostriatal disorder. Increased efficiency in the temporal area in PD patients with fatigue is assumed to be compensatory. Brain network analysis using graph theory is more valuable than power spectrum analysis in revealing the brain mechanism related to fatigue.

BBR-based and fairness-guaranteed congestion control and packet scheduling for MPQUIC over heterogeneous networks

Multipath QUIC (MPQUIC) enables concurrent transmission over multiple paths, making it attractive to enhance the delivery performance of smartphones with multiple interfaces. Nevertheless, several issues in the current MPQUIC specification remain inadequately addressed. Congestion control in MPQUIC primarily relies on packet loss and favors paths with lower drop rates, which results in significant throughput degradation, especially in heterogeneous wireless networks with frequent random packet loss and varying path characteristics. Additionally, network fairness principles limits its performance, even in scenarios with independent and non-shared bottleneck paths. A final issue is that packet scheduling in dynamic and asymmetric paths poses a significant challenge, potentially causing out-of-order (OFO) arrivals and Head-of-Line (HoL) blocking if not appropriately managed. Inspired by Google’s BBR algorithm, this paper introduces a novel scheme called Shared Bottleneck and BBR-based Congestion Control (S2B2C) to address the above issues. It identifies subsets of subflows that share common bottlenecks within the MPQUIC connection based on the BBR’s internal mechanism. The scheme dynamically adjusts the pacing rate of these subflows to enhance goodput while preserving fairness with legacy single-path flows. Then, to mitigate inter-stream and intra-stream HoL blocking caused by OFO arrivals over asymmetric paths, we present a fine-grained Stream-path-bounded Priority-based Packet Scheduler (S2PS), which includes a stream dependency tree, a priority-based queuing, and a packet scheduling algorithm that uses a mixed-integer program formulation. Experimental results show that S2B2C achieves higher throughput while maintaining bottleneck fairness, and S2PS effectively mitigates HoL blocking with fewer OFO arrivals and shorter flow completion time compared to existing MPQUIC schemes in heterogeneous networks.

Splitting Tensile Mechanical Performance and Mesoscopic Failure Mechanisms of High-Performance Concrete under 10-Year Corrosion from Salt Lake Brine

In regions characterized by the challenging combination of brine corrosion in the salt lakes and river sand with alkali silica reaction (ASR) activity in areas of the Northwest, high-performance concrete (HPC) formulated with high-volume composite mineral admixtures as ASR suppression measures has been preferred for civil engineering structures in the region. This study investigates the splitting tensile strength, corrosion products, microscopic structure characteristics, and mesoscopic mechanical mechanisms of splitting failure of such HPC under 10-year corrosion from salt lake brine. The relationship between mechanical properties and corrosion damage, as well as the characteristics of internal crack propagation paths and failure mechanisms of HPC under splitting load, are explored. The findings reveal that as the alkali content within HPC rises, corrosion damage intensifies, resulting in a reduction in splitting tensile strength. Moreover, a linear association between mechanical properties and corrosion damage is observed. Microscopic structural analysis and numerical simulation of the splitting failure process of HPC elucidate that while the substantial presence of mineral admixtures effectively suppresses the ASR risk associated with alkali-reactive aggregates in concrete, uneven ASR gel products persist. These discontinuous micro-fine interface cracks induced by the gel products and the cracks induced by the gel products around the selective alkali-active aggregate particles distributed in the local area are the initiation sources of mortar cracks in HPC splitting failure. In terms of the overall failure state observed during the concrete splitting process, mortar cracks manifest two distinct extension paths: along the coarse aggregate interface and directly through the aggregates themselves. Notably, a greater proportion of coarse aggregates are directly penetrated by mortar cracks, as opposed to the number of interface failures bypassing coarse aggregates. More importantly, the above work establishes a theoretical reference in three dimensions: macroscopic, mesoscopic, and microscopic, for studying concrete corrosion damage in complex environments such as salt lake brine corrosion and ASR inhibition.

Highly sensitive photoacoustic gas sensor based on near-concentric cavity.

The precise detection of trace gases in the atmosphere is vital for both environmental preservation and human health. Addressing the inherent challenges in enhancing the sensitivity of photoacoustic spectroscopy, a highly sensitive photoacoustic gas detection method utilizing a near-concentric cavity was proposed. By constructing a near-concentric optical cavity, laser reflections within the photoacoustic cell were substantially amplified, resulting in enhanced sensitivity of photoacoustic signal detection. Additionally, to align with the optical path characteristics of the near-concentric cavity, a miniaturized dumbbell-like photoacoustic cell was designed. Characterized by its high-frequency resonance, this design effectively mitigated background noise while maintaining a high sound pressure level. Experimental results demonstrated a remarkable enhancement in both signal intensity and signal-to-noise ratio by factors of 22.06 and 21.26, respectively, compared to traditional excitation methods. According to the 1σ standard, with a laser power of 21 mW, the setup achieved a detection limit of 10.15 ppb for NO2. The corresponding normalized noise equivalent absorption was calculated to be 2.84 × 10-9 cm-1WHz-1/2, with a gas consumption rate of merely 15.19 mL.

Alterations of brain structural and functional connectivity networks topology and decoupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease

ObjectiveTo investigate the alteration in structural and functional connectivity networks (SCN and FCN) as well as their coupling in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and determine if these properties could serve as potential biomarkers for the disease. Materials and methodsIn total of 32 children with MOGAD and 30 age- and sex-matched healthy controls (HC) were employed to construct the SCN and FCN, respectively. The graph-theoretical analyses of the global properties, node properties of the 90 brain nodes, and the structural-functional connectivity (SC-FC) coupling of the two networks were performed. The graph-theoretical properties that exhibited significant differences were analyzed using partial correlation analysis in conjunction with the clinical scales, including the expanded disability status scale (EDSS), modified Rankin scale (mRS), and pediatric cerebral performance category (PCPC) of the MOGAD group. Subsequently, a machine learning model was developed to discriminate between MOGAD and the HC group, aiming to explore the potential of these properties as biomarkers. ResultsThe SCN of the MOGAD group exhibited aberrant global properties, including an increased characteristic path length (Lp) and a decreased global efficiency (Eg), along with reduced nodal properties such as degree centrality (Dc), nodal efficiency (Ne), and local efficiency in multiple nodes. The FCN of the MOGAD group only exhibited decreased Dc, Ne, and betweenness centrality in two nodes of nodal properties. Besides, MOGAD showed a significant decrease in SC-FC coupling compared to the HC group. The analysis of partial correlation revealed significant correlations between several properties and the scales of EDSS and mRS in the MOGAD group. The machine learning method was used to extract six features and establish the model, achieving a classification accuracy of 82.3% for MOGAD. ConclusionsPediatric MOGAD showed a more pronounced impairment in the SCN along with decoupling of SC-FC. Both partial correlation analysis and discriminant modeling suggest that alterations in brain network properties have the potential as biomarkers for assessing brain damage in MOGAD.

An EEG Study on [Formula: see text] Phase-Amplitude Coupling-Based Functional Brain Network in Epilepsy Patients.

Epilepsy, a chronic neuropsychiatric brain disorder characterized with recurrent seizures, is closely associated with abnormal neural communications within the brain. Despite that the phase-amplitude coupling (PAC) has been suggested to offer a new way to observe neural interactions during epilepsy, however, few studies pay attention to alterations of the epileptic functional brain network based on PAC, especially on the [Formula: see text] PAC. Therefore, we use scalp electroencephalography (EEG) data of epileptic patients and the [Formula: see text] PAC modulation index (MI) to construct functional brain networks to examine variations of neural interactions during different epileptic phases. Statistically, the findings show that between-channel MI values in the post-ictal period significantly increase compared to that in the pre-ictal period, and the between-channel MI value has a close association with the information of phase and amplitude provided by the channels. Importantly, in both the phase-amplitude and amplitude-phase functional brain networks, the average node degree is remarkably higher in the post-ictal period than that in the pre-ictal period, whereas the characteristic path length in the ictal and post-ictal periods is significantly lower than that in the pre-ictal period. Besides, the average betweenness centrality in the post-ictal period is remarkably higher than that in the ictal period. Interestingly, the positive correlations between within-channel MI values and between-channel MI values can be observed during the pre-ictal, ictal and post-ictal periods. These findings suggest that the [Formula: see text] PAC-based functional brain network may provide a novel perspective to understanding alterations of neural interactions during the epileptic evolution, and may contribute to effectively controlling the spread of epileptic seizures.

Distortions in China's agricultural virtual water trade: A perspective on value chain decomposition

Due to the exacerbation of climate change, agricultural water security has risen to a prominent position on the global agenda. However, virtual water trade isn't always beneficial for enhancing water resource sustainability; instead, it often leads to serious trade distortion problems due to unreasonable industrial and trade structures. This study employs pathway decomposition method to highlight the path characteristics of such distortions, revealing how virtual water trade distortions occur, why there are regional differences, and what insights can be gained for policy formulation. The study focuses on the agricultural sectors of seven key provinces in China. Findings indicate that virtual water in these provinces' agricultural sectors is predominantly exported through inter-regional and inter-sectoral intermediate goods trade. Furthermore, in regions where virtual water trade distortion is more severe, this characteristic becomes more apparent, leading to significant exports of virtual water. However, the trade chains for importing virtual water are usually short and direct, resulting in a relatively low volume of virtual water imports. These characteristics are closely related to the value chain participation mode. The policy implication is: while "value chain upgrading" has become a trendy term, merely improving trade conditions without enhancing the processing of agricultural products for export, or simply increasing imports of low-end intermediate inputs without upgrading the agricultural input structure for imports, offers no assistance in alleviating virtual water trade distortions. Based on these findings, we propose several differentiated strategies to mitigate virtual water trade distortions.

Spatiotemporal structure of foraging and path integration errors by fiddler crabs, Leptuca pugilator

Path integration is the navigational process by which animals construct a memory of a previous location by continuously measuring and summing their movements to form a single home vector pointing to the starting location. It is intrinsically error prone, subject to random errors and, potentially, to systematic errors in either measurement or the summing algorithm. Both types of errors lead to an incorrect vector memory and thus to an error in homing. Because the errors are incurred when animals move, they are theoretically predictable from the movements. We analyzed the behavior of fiddler crabs (Leptuca pugilator) as they performed foraging excursions followed by homing with varying degrees of error. From video recordings we measured body orientations and locations and computed these spatiotemporal path characteristics: duration, distance, turns, bearing and arc sector. These were analyzed for their effect on, separately, the magnitude, and the direction, of crabs’ homing error. The magnitude of the homing error was predicted by arc sector, Δbearing and path length, and several interactions. The direction of the homing error was predicted by interactions including arc sector x Δbearing, arc sector x turns, and Δbearing x turns. Covariance among these factors results in a path that traces a large arc while maintaining body orientation toward the burrow direction and leads to an error with the same clockwise/counterclockwise sign as the arc and the body turns. These results place L. pugilator’s path integration mechanism among others with known systematic errors.

Geometrical multiscale tortuosity of desert ant walking trajectories.

Desert ants stand out as some of the most intriguing insect navigators, having captured the attention of scientists for decades. This includes the structure of walking trajectories during goal approach and search behaviour for the nest and familiar feeding sites. In the present study, we analysed such trajectories with regard to changes in walking direction. The directional change of the ants was quantified, i.e. an angle θ between trajectory increments of a given arclength λ was computed. This was done for different length scales λ, according to our goal of analysing desert ant path characteristics with respect to length scale. First, varying λ through more than two orders of magnitude demonstrated Brownian motion characteristics typical of the random walk component of search behaviour. Unexpectedly, this random walk component was also present in - supposedly rather linear - approach trajectories. Second, there were small but notable deviations from a uniform angle distribution that is characteristic of random walks. This was true for specific search situations, mostly close to the (virtual) goal position. And third, experience with a feeder position resulted in straighter approaches and more focused searches, which was also true for nest searches, albeit to a lesser extent. Taken together, these results both verify and extend previous studies on desert ant path characteristics. Of particular interest are the ubiquitous Brownian motion signatures and specific deviations thereof close to the goal position, indicative of unexpectedly structured search behaviour.

Structural network disruption of corticothalamic pathways in cerebral small vessel disease.

Generalized fractional anisotropy (GFA) can eliminate the crossing fiber effect, which may be more reflective of brain tissue changes in patients with cerebral small vessel disease (CSVD). This study aimed to explore the alterations of structural networks based on GFA and its relationship with cognitive performance in CSVD patients. We recruited 50 CSVD patients which were divided into two groups: cognitive impairment (CSVD-CI) and normal cognition (CSVD-NC), and 22 healthy controls (HCs). All participants underwent the Montreal Cognitive Assessment (MoCA) and MRI examinations. The structural topological properties were compared among the three groups. The correlation between these structural alterations and MoCA was analyzed. Compared with HCs, significantly decreased nodal efficiency and connectivity were detected in the corticothalamic pathways in both patient groups, of which some were significantly decreased in CSVD-CIs compared with CSVD-NCs. Moreover, both patient groups exhibited global network disruption including decreased global efficiency and increased characteristic path length compared with HCs. Furthermore, the nodal efficiency in the right pallidum positively correlated with MoCA in CSVD-NCs controlling for nuisance variables (r = 0.471, p = 0.031). The alterations in corticothalamic pathways indicated that the brain structural network underwent extensive disruption, providing evidence for the consideration of CSVD as a global brain disease.

Functional brain network analysis using electroencephalography in late-onset Lennox–Gastaut syndrome

ObjectiveWe aimed to explore the clinical characteristics and functional network properties of patients with late-onset Lennox–Gastaut syndrome (LGS). MethodsLate-onset LGS was defined by the appearance of LGS features after 8 years of age. We reviewed the medical charts of 9 patients with late-onset LGS, and performed electroencephalography connectivity analysis using graph theory. We assessed the clustering coefficient (CC) and characteristic path length (CPL), which are common basic measures of functional networks that represent local segregation and global integration. The characteristics and brain parameters of late-onset LGS were compared with a typical age-onset LGS group. ResultsLate onset LGS subjects were older than typical age onset LGS at the time of testing, but otherwise there were no significant differences in clinical characteristics. The late-onset group showed higher median CC values in the alpha (p = 0.045) and beta (p < 0.001) bands over brain regions implicated in cognitive processing. There were no significant differences in CPL between the LGS groups. ConclusionsHigher clustering coefficient values, in alpha/beta bands over brain regions implicated in cognitive processing, are consistent with increased cognitive network segregation in late onset LGS compared to typical age-onset LGS. Given network segregation is a normal aspect of brain maturation, these results imply that this process is less disturbed when the LGS process begins later in childhood.

Contact resistance effects on current path and thermal characteristics of Ag-nanowire network

In this study, we measured the temperature distribution of Joule-heated Ag-NW network using thermoreflectance imaging (TRI). Numerical computation was conducted for the electric current flow and heat transfer of the Ag-NW network. The contact electric resistance was obtained by solving the optimization problem to minimize the difference between the temperature distributions of the measurement and computation. The results showed that the contact electric resistance varies over the Ag-NW network at certain magnitude. This variation significantly affected the temperature distribution by defining the current path and producing a non-uniform current distribution.

Refill Drinking Water Depot Risk Assessment for Chemical Hazard Contaminant in 25 Cities of East Java Province, Indonesia

Introduction: Water was a part of the environment that was very susceptible to contamination by various hazardous substances, both physical, chemical, and microbiological. Serious health problems might occur when humans consume contaminated drinking water and can cause infectious and non-infectious diseases. This study aimed to analyze the risk quotient of chemical hazard exposure in drinking water by depot refilling drinking water from 25 cities and regencies in East Java Province. Methods: This study was analytically observational with a cross-sectional research design. The sampling method used was porposive sampling, which took 25 from 38 cities and regencies in East Java province. There were three steps to analyze drinking water health risks: dose-response analysis, exposure path, and risk characteristics analyzed. Results and Discussion: The highest concentrations of each parameter parameter F (1.4132 mg/L), NO_3 (56.2780 mg/L), NO_2 (22,225 mg/L), Fe (0.3845 mg/L), Mg (4.54 mg/L), and Zn (0.4272 mg/L). Analysis of risk quotient &gt; 1 for parameters NO_3 (1.2265), NO_2 (7,748), and Mg (1.1308) Indicates that drinking water in the area is not safe for consumption by people weighing 55kg as much as 2L/day for 350 days. Conclusion: Based on the results of studies conducted on those substances (F, NO_3, NO_2, Fe, Mg, and Zn) there are three substances in the water that have RQ value &gt; 1, NO_3 (1.2265), NO_2 (7,748), and Mg (1.1308) this means that those substances are risking human health and needed to be addressed controlled.

Structural connectivity as a predictive factor for perampanel response in patients with epilepsy

ObjectivesThis study aimed to identify clinical characteristics that could predict the response to perampanel (PER) and determine whether structural connectivity is a predictive factor. MethodsWe enrolled patients with epilepsy who received PER and were followed-up for a minimum of 12 months. Good PER responders, who were seizure-free or presented with more than 50 % seizure reduction, were classified separately from poor PER responders who had seizure reduction of less than 50 % or non-responders. A graph theoretical analysis was conducted based on diffusion tensor imaging to calculate network measures of structural connectivity among patients with epilepsy. Results106 patients with epilepsy were enrolled, including 26 good PER responders and 80 poor PER responders. Good PER responders used fewer anti-seizure medications before PER administration compared to those by poor PER responders (3 vs. 4; p = 0.042). Early PER treatment was more common in good PER responders than poor PER responders (46.2 vs. 21.3 %, p = 0.014). Regarding cortical structural connectivity, the global efficiency was higher and characteristic path length was lower in good PER responders than in poor PER responders (0.647 vs. 0.635, p = 0.006; 1.726 vs. 1,759, p = 0.008, respectively). For subcortical structural connectivity, the mean clustering coefficient and small-worldness index were higher in good PER responders than in poor PER responders (0.821 vs. 0.791, p = 0.009; 0.597 vs. 0.560, p = 0.009, respectively). ConclusionThis study demonstrated that early PER administration can predict a good PER response in patients with epilepsy, and structural connectivity could potentially offer clinical utility in predicting PER response.

Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome

Deep brain stimulation (DBS) is an effective therapy for Meige syndrome (MS). However, the DBS efficacy varies across MS patients and the factors contributing to the variable responses remain enigmatic. We aim to explain the difference in DBS efficacy from a network perspective. We collected preoperative T1-weighted MRI images of 76 MS patients who received DBS in our center. According to the symptomatic improvement rates, all MS patients were divided into two groups: the high improvement group (HIG) and the low improvement group (LIG). We constructed group-level structural covariance networks in each group and compared the graph-based topological properties and interregional connections between groups. Subsequent functional annotation and correlation analyses were also conducted. The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. Different nodal betweennesses and degrees between groups were mainly identified in the precuneus, sensorimotor cortex, and subcortical nuclei, among which the gray matter volume of the left precentral gyrus and left thalamus were positively correlated with the symptomatic improvement rates. Moreover, HIG had enhanced interregional connections within the somatomotor network and between the somatomotor network and default-mode network relative to LIG. We concluded that the high and low DBS responders have notable differences in large-scale network architectures. Our study sheds light on the structural network underpinnings of varying DBS responses in MS patients.

Altered cortical thickness and structural covariance networks in chronic low back pain

BackgroundDespite regional brain structural changes having been reported in patients with chronic low back pain (CLBP), the topological properties of structural covariance networks (SCNs), which refer to the organization of the SCNs, remain unclear. This study applied graph theoretical analysis to explore the alterations of the topological properties of SCNs, aiming to comprehend the integration and separation of SCNs in patients with CLBP. MethodsA total of 38 patients with CLBP and 38 healthy controls (HCs), balanced for age and sex, were scanned using three-dimensional T1-weighted magnetic resonance imaging. The cortical thickness was extracted from 68 brain regions, according to the Desikan–Killiany atlas, and used to reconstruct the SCNs. Subsequently, graph theoretical analysis was employed to evaluate the alterations of the topological properties in the SCNs of patients with CLBP. ResultsIn comparison to HCs, patients with CLBP had less cortical thickness in the left superior frontal cortex. Additionally, the cortical thickness of the left superior frontal cortex was negatively correlated with the Visual Analogue Scale scores of patients with CLBP. Furthermore, patients with CLBP, relative to HCs, exhibited lower global efficiency and small-worldness, as well as a longer characteristic path length. This indicates a decline in the brain's capacity to transmit and process information, potentially impacting the processing of pain signals in patients with CLBP and contributing to the development of CLBP. In contrast, there were no significant differences in the clustering coefficient, local efficiency, nodal efficiency, nodal betweenness centrality, or nodal degree between the two groups. ConclusionsFrom the regional cortical thickness to the complex brain network level, our study demonstrated changes in the cortical thickness and topological properties of the SCNs in patients with CLBP, thus aiding in a better understanding of the pathophysiological mechanisms of CLBP.