Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis

Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury.These findings highlight the importance of integrating structural and functional connectivity in unde rstanding the occurrence and evolution of mild traumatic brain injury.Additionally,exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

Assessment of sediment connectivity using modelling and field-based approaches in the Slavíč River catchment(MoravskoslezskéBeskydy Mts,Czech Republic)

Mountain streams act as conveyors of sediments within the river continuum,where the physical transport of sediments between river reaches through the catchment or between individual parts(e.g.,between hillslopes and channels)of the catchment is assumed.This study focused on sediment connectivity analysis in the SlavíčRiver catchment in the MoravskoslezskéBeskydy Mts in the eastern part of the Czech Republic.The connectivity index and connectivity index target modelling were combined with an analysis of anthropogenic interventions.Additionally,field mapping,grain size of bed sediments and stream power analysis were used to obtain information about connectivity in the catchment.Based on the analysis and obtained results,terrain topography is the current main driving factor affecting the connectivity of sediment movement in the SlavíčRiver catchment.However,the modelling provided valuable information about high sediment connectivity despite different recent land use conditions(highly forested area of the catchment)than those in historical times from the 16th to 19th centuries when the SlavíčRiver catchment was highly deforested and sediment connectivity was probably higher.The analysis of anthropogenic interventions,field mapping,grain size of bed sediments and stream power analysis revealed more deceleration of sediment movement through the catchment,decreased sediment connectivity with bed erosion,and gradual river channel process transformation in some reaches.Field mapping has identified various natural formations and human-induced changes impacting the longitudinal and lateral connectivity in the SlavíčRiver.For instance,embankments along 48%of the river's length,both on the right and left banks,significantly hinder lateral sediment supply to the channel.Stream power index analysis indicates increased energy levels in the flowing water in the river's upper reaches(up to 404.8 W m^(-2)).This high energy is also observed in certain downstream sections(up to 337.6 W m^(-2)),where it is influenced by human activities.These conditions lead to intensified erosion processes,playing a crucial role in sediment connectivity.Similar observations were described in recent studies that pointed out the long-term human interventions on many streams draining European mountains,where a decrease in sediment connectivity in these streams is linked with sediment deficits and the transformation of processes forming channels.

A divergent pattern in functional connectivity: a transdiagnostic perspective

Functional magnetic resonance imaging(fMRI)is a popular tool used to investigate not only how the brain responds to specific stimuli during sensorimotor or cognitive tasks,but also brain activity at rest.The physics beyond this approach is based on the analysis of the blood oxygenation level-dependent signal.

A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

With the continuous advancement in topology optimization and additive manufacturing(AM)technology,the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown significantly.However,a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures,potentially resulting in diminished efficiency or macroscopic failure.A Hybrid Level Set Method(HLSM)is proposed,specifically designed to enhance connectivity among non-uniform microstructures,contributing to the design of functionally graded cellular structures.The HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure interfaces.Initially,an interpolation algorithm is presented to construct transition microstructures seamlessly connected on both sides.Subsequently,the algorithm enables the morphing of non-uniform unit cells to seamlessly adapt to interconnected adjacent microstructures.The method,seamlessly integrated into a multi-scale topology optimization framework using the level set method,exhibits its efficacy through numerical examples,showcasing its prowess in optimizing 2D and 3D functionally graded materials(FGM)and multi-scale topology optimization.In essence,the pressing issue of interface connections in complex structure design is not only addressed but also a robust methodology is introduced,substantiated by numerical evidence,advancing optimization capabilities in the realm of functionally graded materials and cellular structures.

Brain mechanism of acupuncture for children with anisometropic amblyopia: a resting functional magnetic resonance imaging study based on voxel-mirrored homotopic connectivity

AIM:To explore the brain mechanism of acupuncture for children with anisometropic amblyopia using the voxelmirror homotopic connectivity(VMHC)analysis method of resting functional magnetic resonance imaging(rs-fMRI)technology based on clinical effectiveness.METHODS:Eighty children with anisometropic monocular amblyopia were randomly divided into two groups:control(40 cases,1 case of shedding)and acupuncture(40 cases,1 case of shedding)groups.The control group was treated with glasses,red flash,grating,and visual stimulations,with each procedure conducted for 5min per time.Based on routine treatment,the acupuncture group underwent acupuncture of“regulating qi and unblocking meridians to bright eyes”,Jingming(BL1),Cuanzhu(BL2),Guangming(GB37),Fengchi(GB20)acupoints were taken on both sides,with the needle kept for 30min each time.Both groups were treated once every other day,three times per week,for a total of 4wk.After the treatment,the overall curative effect of the two groups and the latency and amplitude changes of P100 wave of pattern visual-evoked potential were counted.At the same time,nine children with left eye amblyopia were randomly selected from the two groups and were scanned with rsfMRI before and after treatment.The differences in the brain regions between the two groups were compared and analyzed with VMHC.RESULTS:Chi-square test showed a notable difference in the total efficiency rate between the acupuncture(94.87%)and control groups(79.49%).Regarding the P100 wave latency and amplitude,the acupuncture group had significantly shorter latency and higher amplitude of P100 wave than the control group.Moreover,the VMHC values of the bilateral temporal lobe,superior temporal gyrus,and middle temporal gyrus were notably increased in the acupuncture group after treatment.CONCLUSION:Acupuncture combined with conventional treatment can significantly improve the corrected visual acuity and optic nerve conduction in children with anisometropic amblyopia.Compared with the conventional treatment,the regulation of acupuncture on the functional activities of the relevant brain areas in the anterior cerebellum may be an effective acupuncture mechanism for anisometropic amblyopia.

The g-Good-Neighbor Connectivity of Some Cartesian Product Graphs

The g-good-neighbor connectivity of G is a generalization of the concept of connectivity, which is just for, and an important parameter in measuring the fault tolerance and reliability of interconnection network. Many well-known networks can be constructed by the Cartesian products of some simple graphs. In this paper, we determine the g-good-neighbor connectivity of some Cartesian product graphs. We give the exact value of g-good-neighbor connectivity of the Cartesian product of two complete graphs and for , mesh for , cylindrical grid and torus for .

Probing the influence of secondary fracture connectivity on fracturing fluid flowback efficiency

A deep understanding of the geometric impacts of fracture on fracturing fluid flowback efficiency is essential for unconventional oil development. Using nuclear magnetic resonance and 2.5-dimensional matrix-fracture visualization microfluidic models, qualitative and quantitative descriptions of the influences of connectivity between primary fracture and secondary fracture on flowback were given from core scale to pore network scale. The flow patterns of oil-gel breaking fluid two-phase flow during flowback under different fracture connectivity were analyzed. We found some counterintuitive results that non-connected secondary fracture (NCSF, not connect with artificial primary fracture and embedded in the matrix) is detrimental to flowbackefficiency. The NCSF accelerates the formation of oil channeling during flowback, resulting in a large amount of fracturing fluid trapped in the matrix, which is not beneficial for flowback. Whereas the connected secondary fracture (CSF, connected with the artificial primary fracture) is conducive to flowback. The walls of CSF become part of primary fracture, which expands the drainage area with low resistance, and delays the formation of the oil flow channel. Thus, CSF increases the high-speed flowback stage duration, thereby enhancing the flowback efficiency. The fracturing fluid flowback efficiency investigated here follows the sequence of the connected secondary fracture model (72%) > the matrix model (66%) > the non-connected secondary fracture model (38%). Our results contribute to hydraulic fracturing design and the prediction of flowback efficiency.

Pore Connectivity of Deep Lacustrine Shale and its Effect on Gas-bearing Characteristics in the Songliao Basin:Implications from Continental Scientific Drilling

The lacustrine shale of deep Shahezi Formation in the Songliao basin has great gas potential,but its pore evolution,heterogeneity,and connectivity characteristics remain unclear.In this work,total organic carbon analysis,rock pyrolysis,X-ray diffraction field emission scanning electron microscopy,the particle and crack analysis system software,low-temperature nitrogen adsorption experiment,fractal theory,high-pressure mercury injection experiment and nuclear magnetic resonance experiment were used to study the Shahezi shale from Well SK-2.The result indicated that the organic pores in Shahezi shale are not developed,and the intergranular and intragranular pores are mainly formed by illitedominated clay.As the burial depth increases,the pore size and slit-shaped pores formed by clay decrease,and dissolved pores in the feldspar and carbonate minerals and dissolved fractures in the quartz increase.The pore evolution is affected by clay,compaction,and high-temperature corrosion.Based on the pore structure characteristics reflected by the pore size distribution and pore structure parameters obtained by multiple experimental methods,the pore development and evolution are divided into three stages.During stageⅠandⅡ,the pore heterogeneity of the shale reservoirs increases with the depth,the physical properties and pore connectivity deteriorate,but the gas-bearing property is good.In stageⅢ,the pore heterogeneity is the highest,its gas generation and storage capacity are low,but the increase of micro-fractures makes pore connectivity and gas-bearing better.

Regional differences in gully network connectivity based on graph theory:a case study on the Loess Plateau,China

Material exchange frequently occurs in gullies,and thus the relationship between a gullynetwork structure and sediment transport potential has attracted considerable interest.However,previous researches ignored the difficulty of material transport from sources to sinks,and did not quantify the connectivity of a network structure.In this study,we used a graph model structure to model gully networks of six typical sample areas in the Loess Plateau of China and quantified gully network connectivity using four indexes:average node strength,accessibility from sources to sinks,potential flow,and network structural connectivity index.Results show that:(1)Reflected by different quantitative indexes,the trends of gully network connectivity in different regions are similar.From north to south,the connectivity of a sample area first increases and then decreases.(2)The more mature gullies have stronger network connectivity.Small resistance is conducive to material transport in the gullies.(3)The node connectivity index of the gully network shows a significant aggregation distribution in space,and node connectivity on the main channel is often stronger than that on the branch trench.These results not only deepen the understanding of the process and mechanism of loess gully geomorphic development and evolution but also provide a reference for geomorphic studies.

Quantitative characterization of shale pore connectivity and controlling factors using spontaneous imbibition combined with nuclear magnetic resonance T_(2)and T_(1)-T_(2)

Shale oil can be extracted from shale by using interconnected pore networks.The migration of hydrocarbon molecules within the shale is controlled by pore connectivity.However,assessing the pore connectivity of shale oil reservoirs is uncommon.To characterize pore connectivity and clarify its controlling factors,this study used spontaneous imbibition(SI)combined with nuclear magnetic resonance(NMR)T_(2)and T_(1)-T_(2)technologies on shale oil reservoirs selected from the Shahejie Formation in the Dongying Sag,Bohai Bay Basin.According to the findings,the SI processes of shales include fast-rising,slow-rising,and stable stages.The fast-rising stage denotes pore connectivity.The shales studied have poor connectivity,with lower imbibition slopes and connected porosity ratios,but large effective tortuosity.During the SI process,micropores have the highest imbibition saturation,followed by mesopores and macropores.Furthermore,n-dodecane ingested into micropores appears primarily as adsorbed,whereas n-dodecane appears primarily as free states in mesopores and macropores during the SI process.The pore connectivity of the shales under study is primarily controlled by inorganic minerals.Quartz and feldspar develop large and regular pores,resulting in better pore connectivity,whereas clay minerals and calcite with plenty of complex intragranular pores do not.Organic matter negatively influences pore connectivity because the dissolution of calcite by organic acid produced during hydrocarbon generation leads to a more complex and heterogeneous pore structure.This study sheds light on the pore connectivity and controlling factors of the shale oil reservoir and aids in the understanding of shale oil mobility.

Morphodynamics and sediment connectivity index in an unmanaged,debris-flow prone catchment:a through time perspective

Torrential processes are among the main actors responsible for sediment production and mobility in mountain catchments.For this reason,the understanding of preferential pathways for sediment routing has become a priority in hazard assessment and mitigation.In this context,the sediment Connectivity Index(IC)enables to analyse the existing linkage between sediment sources and the selected target(channel network or catchment outlet).The IC is a grid-based index that allows fast computation of sediment connectivity based on landscape information derived from a single Digital Terrain Model(DTM).The index computation is based on the log-ratio between an upslope and a downslope component,including information about drainage area,slope,terrain roughness,and distance to the analysis target(e.g.outlet).The output is a map that highlights the degree of structural connectivity of sediment pathways over analysed catchments.Until now,these maps are however rarely used to help defining debris-flow hazard maps,notably due to a lack of guidelines to interpret the IC spatial distribution.This paper proposes an exploitation procedure along profiles to extract more information from the analysis of mapped IC values.The methodology relies on the analysis of the IC and its component variables along the main channel profile,integrated with information about sediment budgeting derived from Difference of DEMs(DoD).The study of connectivity was applied in the unmanaged sub-catchment(without torrent control works)of the Rio Soial(Autonomous Province of Trento–NE Italy)to understanding the geomorphic evolution of the area after five debris flows(in ten years)and the related changes of sediment connectivity.Using a recent DTM as validation,we demonstrated how an IC analysis over the older DTM can help predicting geomorphic changes and associated hazards.The results show an IC aptitude to capture geomorphic trajectories,anticipate debris flow deposits in a specific channel location,and depict preferential routing pathways.

Corrigendum:Altered intra-and inter-network brain functional connectivity in upper-limb amputees revealed through independent component analysis

Corrigendum:Altered intra-and inter-network brain functional connectivity in upper-limb amputees revealed through independent component analysis https://doi.org/10.4103/1673-5374.373719 There is an error in the registration number of the published paper“Altered intra-and inter-network brain functional connectivity in upper-limb amputees revealed through independent component analysis”(doi:10.4103/1673-5374.339496)(Bao et al.,2022).The correct registration number should be ChiCTR-IOR-17011413.

Functional hyperconnectivity related to brain disease:maladaptive process or element of resilience?

Neuroimaging techniques such as magnetic resonance imaging(MRI)and positron emission tomography provide unique in vivo data to analyze structural and functional connectivity of the whole brain.Recent advances in small animal neuroimaging have opened new opportunities for the study of structure-function interactions in healthy and diseased brain networks,which are essential to develop therapies targeting network reorganization associated with functional improvement.

Next generation drug connectivity mapping for acquiring therapeutic agents to differentially regulate myelination

The need for new therapeutic approaches:Conventional drug discovery is a lengthy and expensive process,taking decades and billions of dollars to get a drug from bench to bedside.Much of the costs incurred are at the pre-clinical stages,between drug design and synthesis to delineating the cellular“Mechanisms of Action”(MoA).Notably,there is a very high risk of failure,and only a very small proportion of therapeutic agents reach later-phase clinical trials.Accordingly,drug repositioning has become a valuable strategy aimed at fast-tracking treatments into clinical use and improving the chances of therapeutic success.A novel addition to this approach is connectivity mapping,which defines cell-specific transcriptional responses to small molecules in disease-dependent contexts.This commentary outlines how some of the latest innovations in connectivity mapping can be exploited for drug repurposing.

Joint User Association and Fair Scheduling for Dual Connectivity Heterogeneous Networks

Heterogeneous small cell network is one of the most effective solutions to overcome spectrum scarcity for the next generation of mobile networks.Dual connectivity(DC)can improve the throughput for each individual user by allowing concurrent access to two heterogeneous radio networks.In this paper,we propose a joint user association and fair scheduling algorithm(JUAFS)to deal with the resource allocation and load balancing issues for DC heterogeneous small cell networks.Considering different coverage sizes,numbers of users,and quality of experience characteristics of heterogeneous cells,we present a proportional fair scheduling for user association among cells and utilize interference graph to minimize the transmission conflict probability.Simulation results show the performance improvement of the proposed algorithm in spectrum efficiency and fairness comparing to the existing schemes.

Learning-Based Dynamic Connectivity Maintenance for UAV-Assisted D2D Multicast Communication

Unmanned aerial vehicles(UAVs) enable flexible networking functions in emergency scenarios.However,due to the movement characteristic of ground users(GUs),it is challenging to capture the interactions among GUs.Thus,we propose a learningbased dynamic connectivity maintenance architecture to reduce the delay for the UAV-assisted device-todevice(D2D) multicast communication.In this paper,each UAV transmits information to a selected GU,and then other GUs receive the information in a multi-hop manner.To minimize the total delay while ensuring that all GUs receive the information,we decouple it into three subproblems according to the time division on the topology:For the cluster-head selection,we adopt the Whale Optimization Algorithm(WOA) to imitate the hunting behavior of whales by abstracting the UAVs and cluster-heads into whales and preys,respectively;For the D2D multi-hop link establishment,we make the best of social relationships between GUs,and propose a node mapping algorithm based on the balanced spanning tree(BST) with reconfiguration to minimize the number of hops;For the dynamic connectivity maintenance,Restricted Q-learning(RQL) is utilized to learn the optimal multicast timeslot.Finally,the simulation results show that our proposed algorithms perfor better than other benchmark algorithms in the dynamic scenario.

Structural Connectivity Enhanced Anisotropic 3D Network for Brain Midline Delineation

Brain midline delineation can facilitate the clinical evaluation of brain midline shift,which has a pivotal role in the diagnosis and prognosis of various brain pathology.However,there are still challenges for brain midline delineation:1)the largely deformed midline is hard to localize if mixed with severe cerebral hemorrhage;2)the predicted midlines of recent methods are not smooth and continuous which violates the structural priority.To overcome these challenges,we propose an anisotropic three dimensional(3D)network with context-aware refinement(A3D-CAR)for brain midline modeling.The proposed network fuses 3D context from different two dimensional(2D)slices through asymmetric context fusion.To exploit the elongated structure of the midline,an anisotropic block is designed to balance the difference between the adjacent pixels in the horizontal and vertical directions.For maintaining the structural priority of a brain midline,we present a novel 3D connectivity regular loss(3D CRL)to penalize the disconnectivity between nearby coordinates.Extensive experiments on the CQ dataset and one in-house dataset show that the proposed method outperforms three state-of-the-art methods on four evaluation metrics without excessive computational burden.

The relationship between extra connectivity and t/k-diagnosability under the PMC model

It is well-known that connectivity is closely related to diagnosability.If the relationships be-tween them can be established,many kinds of diagnosability will be determined directly.So far,some notable relationships between connectivity and diagnosability had been revealed.This paper in-tends to find out the relationship between extra connectivity and t/k-diagnosability under the PMC(Preparata,Metze,and Chien)model.Then,applying this relationship,the t/k-diagnosability of bijective connection(BC)networks are determined conveniently.

Adaptation to Fluctuating Neuronal Signal Traffic for Brain Connectivity

Brain connectivity is commonly studied in terms of causal interaction or statistical dependency between brain regions. In this analysis paper, we draw attention to the constraining effect the dynamics of fiber tract connections may impose on neuronal signal traffic. We propose a model developed by Copelli and Kinouchi (l.c.) for a different purpose to safeguard signal transmission for brain connectivity by ensuring dynamic adaptation of signal reception to a wide frequency range of traffic flow over connecting fiber tracts. Gap junction connectivity would confer to neuronal groups the capacity of acting as collectives for dynamical adaptability to impinging neural traffic thereby forestalling traffic congestion and overload. It is suggested that applying this model to signal reception in brain connectivity would deliver the required functionality as a collective achievement of the interrelations between neurons and gap junctions, the latter regulated by glia.

Cost-effective distributed FTFC for uncertain nonholonomic mobile robot fleet with collision avoidance and connectivity preservation

In this paper,the fault-tolerant formation control(FTFC)problem is investigated for a group of uncertain nonholonomic mobile robots with limited communication ranges and unpredicted actuator faults,where the communication between the robots is in a directed one-to-one way.In order to guarantee the connectivity preservation and collision avoidance among the robots,some properly chosen performance functions are incorporated into the controller to per-assign the asymmetrical bounds for relative distance and bearing angle between each pair of adjacent mobile robots.Particularly,the resultant control scheme remains at a costeffective level because its design does not use any velocity information from neighbors,any prior knowledge of system nonlinearities or any nonlinear approximator to account for them despite the presence of modeling uncertainties,unknown external disturbances,and unexpected actuator faults.Meanwhile,each follower is derived to track the leader with the tracking errors regarding relative distance and bearing angle subject to prescribed transient and steady-state performance guarantees,respectively.Moreover,all the closed-loop signals are ensured to be ultimately uniformly bounded.Finally,a numerical example is simulated to verify the effectiveness of this methodology.