Strength Of Connections Research Articles

Low arousal threshold is associated with altered functional connectivity of the ascending reticular activating system in patients with obstructive sleep apnea

A low arousal threshold (LAT) is a pathophysiological trait of obstructive sleep apnea (OSA) that may be associated with brainstem ascending reticular activating system-cortical functional connectivity changes. We evaluated resting-state connectivity between the brainstem nuclei and 105 cortical/subcortical regions in OSA patients with or without a LAT and healthy controls. Twenty-five patients with moderate to severe OSA with an apnea–hypopnea index between 20 and 40/hr (15 with and 10 without a LAT) and 15 age- and sex-matched controls were evaluated. Participants underwent functional magnetic resonance imaging after overnight polysomnography. Three brainstem nuclei—the locus coeruleus (LC), laterodorsal tegmental nucleus (LDTg), and ventral tegmental area (VTA)—associated with OSA in our previous study were used as seeds. Functional connectivity values of the two brainstem nuclei (LC and LDTg) significantly differed among the three groups. The connectivity of the LC with the precuneus was stronger in OSA patients than in controls regardless of the concomitant LAT. The connectivity between the LDTg and the posterior cingulate cortex was also stronger in OSA patients regardless of the LAT. Moreover, OSA patients without a LAT showed stronger LDTg-posterior cingulate cortex connectivity than those with a LAT (post hoc p = 0.013), and this connectivity strength was negatively correlated with the minimum oxygen saturation in OSA patients (r = − 0.463, p = 0.023). The LAT in OSA patients was associated with altered LDTg-posterior cingulate cortex connectivity. This result may suggested that cholinergic activity may play a role in the LAT in OSA patients.

Individual patterns of functional connectivity in neonates as revealed by surface-based Bayesian modeling.

Resting-state functional connectivity is a widely used approach to study the functional brain network organization during early brain development. However, the estimation of functional connectivity networks in individual infants has been rather elusive due to the unique challenges involved with functional magnetic resonance imaging (fMRI) data from young populations. Here, we use fMRI data from the developing Human Connectome Project (dHCP) database to characterize individual variability in a large cohort of term-born infants (N = 289) using a novel data-driven Bayesian framework. To enhance alignment across individuals, the analysis was conducted exclusively on the cortical surface, employing surface-based registration guided by age-matched neonatal atlases. Using 10 minutes of resting-state fMRI data, we successfully estimated subject-level maps for fourteen brain networks/subnetworks along with individual functional parcellation maps that revealed differences between subjects. We also found a significant relationship between age and mean connectivity strength in all brain regions, including previously unreported findings in higher-order networks. These results illustrate the advantages of surface-based methods and Bayesian statistical approaches in uncovering individual variability within very young populations.

Socioeconomic status moderates associations between hippocampal development and cognition in preterms.

The hippocampus plays a critical role in cognitive networks. The anterior hippocampus is vulnerable to early-life stress and socioeconomic status (SES) with alterations persisting beyond childhood. How SES modifies the relationship between early hippocampal development and cognition remains poorly understood. This study examined associations between SES, structural and functional development of neonatal hippocampus, and 18-month cognition in very preterm neonates. In total, 179 preterm neonates were followed prospectively. Structural and resting-state functional MRI were obtained early-in-life and at term-equivalent age (median 32.9 and 41.1 weeks post-menstrual age) to calculate anterior and posterior hippocampal volumes and hippocampal functional connectivity strength. Eighteen-month cognition was assessed via Bayley-III. Longitudinal statistical analysis using generalized estimating equations, accounting for birth gestational age, post-menstrual age at scan, sex, and motion, was performed. SES, measured as maternal education level, modified associations between anterior but not posterior hippocampal volumes and 18-month cognition (interaction term p = 0.005), and between hippocampal connectivity and cognition (interaction term p = 0.05). Greater anterior hippocampal volumes and hippocampal connectivity were associated with higher cognitive scores only in the lowest SES group. Maternal education alone did not predict neonatal hippocampal volume from early-in-life and term. SES modified the relationship between neonatal hippocampal development and 18-month cognition in very preterm neonates. The lack of direct association between maternal education and neonatal hippocampal volumes indicates that socio-environmental factors beyond the neonatal period contribute to modifying the relationship between hippocampal development and cognition. These findings point toward opportunities to more equitably promote optimal neurodevelopmental outcomes in very preterm infants.

Sex-specific social aging in wild African lions

There is a growing interest in social behavior change with age,1,2,3,4,5 and the impacts of sociality on longevity,6,7,8 but current knowledge is broadly limited to primates, societies structured by dominance hierarchies, or single-sex studies. It is less clear how social aging patterns emerge in carnivores. The African lion (Panthera leo), a species that lives in egalitarian fission-fusion societies, presents an exceptional opportunity to examine social aging. Across felids, lions are unique in their dependence on conspecifics for many essential processes,9,10,11 and there is vast knowledge of lion behavioral ecology,10,11,12,13,14 including documented reproductive senescence in both sexes.14,15 Applying spatial-social network analyses across 30 years of data on the wild Serengeti lion population, we show that sex strongly modulates patterns of social aging and longevity. Group size increased with age for both sexes, but only males experienced significant changes in associate numbers (degree), specifically to females, which peaked in mid-life before declining. While aging females experienced declines in intra-sex connectivity (strength) and bond strength (mean strength), they peaked in both to males during mid-life. Male inter-sex strength also peaked in mid-life, while conversely their intra-sex strength and mean strength significantly dipped in mid-life. Although social associations were important for survival in both sexes, the investment diverged significantly: females' overall network connectivity was key for longevity, while the number of associates was important for males. These findings illustrate important potential effects of social aging in a wild carnivore and demonstrate how these diverge strongly between the sexes.

Continuum percolation of two-dimensional adaptive dynamics systems.

The percolation phase transition of a continuum adaptive neuron system with homeostasis is investigated. In order to maintain their average activity at a particular level, each neuron (represented by a disk) varies its connection radius until the sum of overlapping areas with neighboring neurons (representing the overall connection strength in the network) has reached a fixed target area for each neuron. Tuning the two key parameters in the model, i.e., the density defined as the number of neurons (disks) per unit area and the sum of the overlapping area of each disk with its adjacent disks, can drive the system into the critical percolating state. These two parameters are inversely proportional to each other at the critical state, and the critical filling factors are fixed about 0.7157, which is much less than the case of the continuum percolation with uniform disks. It is also confirmed that the critical exponents in this model are the same as the two-dimensional standard lattice percolation. Although the critical state is relatively more sensitive and exhibits long-range spatial correlation, local fluctuations do not propagate in a long-range manner through the system by the adaptive dynamics, which renders the system overall robust against perturbations.

Comparison of Negative Symptom Network Structures Between Patients With Early and Chronic Schizophrenia: A Network and Exploratory Graph Analysis.

Despite the clinical relevance of negative symptoms in schizophrenia, our understanding of negative symptoms remains limited. Although various courses and stages of schizophrenia have been identified, variations in the negative symptom networks between distinct stages of schizophrenia remain unexplored. We examined 405 patients with early schizophrenia (ES) and 330 patients with chronic schizophrenia (CS) using the Scale for the Assessment of Negative Symptoms. Network analysis and exploratory graph analysis were used to identify and compare the network structures and community memberships of negative symptoms between the two groups. Further, associations between communities and social functioning were evaluated. The potential influences of other symptom domains and confounding factors were also examined. Multidimensional differences were found in the networks of negative symptoms between ES and CS. The global connectivity strength was higher in the network of ES than in the network of CS. In ES, central symptoms were mainly related to expressive deficits, whereas in CS they were distributed across negative symptom domains. A three-community structure was suggested across stages but with different memberships and associations with social functioning. Potential confounding factors and symptom domains, including mood, positive, disorganization, and excitement symptoms, did not affect the network structures. Our findings revealed the presence of stage-specific network structures of negative symptoms in schizophrenia, with negative symptom communities having differential significance for social functioning. These findings provide implications for the future development of tailored interventions to alleviate negative symptoms and improve functionality across stages.

Influence of Bolt Threads on the Net Section Tensile Rupture Strength of Single-Bolt Connections in Pultruded Structures

Influence of Bolt Threads on the Net Section Tensile Rupture Strength of Single-Bolt Connections in Pultruded Structures

Exploration of resting-state brain functional connectivity as preclinical markers for arousal prediction in prolonged disorders of consciousness: A pilot study based on functional near-infrared spectroscopy.

There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near-infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. Five minutes resting-state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting-state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut-off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)-based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR-based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut-off value of resting-state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. Resting-state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut-off values of resting-state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.

Progressive remodeling of structural networks following surgery for operculo-insular epilepsy.

Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients. Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling. We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1). To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.

Linking the neural signature of response time variability to Alzheimer's disease pathology and cognitive functioning.

Promising evidence has suggested potential links between mind-wandering and Alzheimer's disease (AD). Yet, older adults with diagnosable neurocognitive disorders show reduced meta-awareness, thus questioning the validity of probe-assessed mind-wandering in older adults. In prior work, we employed response time variability as an objective, albeit indirect, marker of mind-wandering to identify patterns of functional connectivity that predicted mind-wandering. In the current study, we evaluated the association of this connectome-based, mind-wandering model with cerebral spinal fluid (CSF) p-tau/Aβ 42 ratio in 289 older adults from the Alzheimer's Disease NeuroImaging Initiative (ADNI). Moreover, we examined if this model was similarly associated with individual differences in composite measures of global cognition, episodic memory, and executive functioning. Edges from the high response time variability model were significantly associated with CSF p-tau/Aβ ratio. Furthermore, connectivity strength within edges associated with high response time variability was negatively associated with global cognition and episodic memory functioning. This study provides the first empirical support for a link between an objective neuromarker of mind-wandering and AD pathophysiology. Given the observed association between mind-wandering and cognitive functioning in older adults, interventions targeted at reducing mind-wandering, particularly before the onset of AD pathogenesis, may make a significant contribution to the prevention of AD-related cognitive decline.

Tracking EEG network dynamics through transitions between eyes-closed, eyes-open, and task states

Our study aimed to verify the possibilities of effectively applying chronnectomics methods to reconstruct the dynamic processes of network transition between three types of brain states, namely, eyes-closed rest, eyes-open rest, and a task state. The study involved dense EEG recordings and reconstruction of the source-level time-courses of the signals. Functional connectivity was measured using the phase lag index, and dynamic analyses concerned coupling strength and variability in alpha and beta frequencies. The results showed significant and dynamically specific transitions regarding processes of eyes opening and closing and during the eyes-closed-to-task transition in the alpha band. These observations considered a global dimension, default mode network, and central executive network. The decrease of connectivity strength and variability that accompanied eye-opening was a faster process than the synchronization increase during eye-opening, suggesting that these two transitions exhibit different reorganization times. While referring the obtained results to network studies, it was indicated that the scope of potential similarities and differences between rest and task-related networks depends on whether the resting state was recorded in eyes closed or open condition.

Research on the Influence of Information Iterative Propagation on Complex Network Structure.

Dynamic propagation will affect the change of network structure. Different networks are affected by the iterative propagation of information to different degrees. The iterative propagation of information in the network changes the connection strength of the chain edge between nodes. Most studies on temporal networks build networks based on time characteristics, and the iterative propagation of information in the network can also reflect the time characteristics of network evolution. The change of network structure is a macromanifestation of time characteristics, whereas the dynamics in the network is a micromanifestation of time characteristics. How to concretely visualize the change of network structure influenced by the characteristics of propagation dynamics has become the focus of this article. The appearance of chain edge is the micro change of network structure, and the division of community is the macro change of network structure. Based on this, the node participation is proposed to quantify the influence of different users on the information propagation in the network, and it is simulated in different types of networks. By analyzing the iterative propagation of information, the weighted network of different networks based on the iterative propagation of information is constructed. Finally, the chain edge and community division in the network are analyzed to achieve the purpose of quantifying the influence of network propagation on complex network structure.

DTI Tractography

The DTI technology used to observe the Nerve fascicle - Nerve fascicle imaging was also discussed in detail. Two types of deterministic and probabilistic traction imaging were compared from effectiveness and computational efficiency perspectives. Then an experimental study was conducted using different software to compare the fiber bundles of the subjects brain and the normal brain and to evaluate the impact of different angle thresholds on the number of observable fiber bundles. Research has confirmed that the subjects whole brain fiber bundle imaging reconstruction was successful, and there was no significant difference compared to the normal brain fiber bundle. The study also found a specific quantitative relationship between the angle threshold and the number of fiber bundles. This experiment also explored the differences in connectivity strength between the brain regions of the left and right brains and their significance.

A new method of magnetic pulse welding of dissimilar metal plates using a uniform pressure electromagnetic actuator based on pre-deformation

The magnetic pulse welding method using a uniform pressure electromagnetic actuator can effectively weld dissimilar metal plates. However, the existing uniform pressure welding method leads to serious thinning of the plate at the chamfer, lack of welding at the center, and bulging of the welded sample, which seriously affects the quality of the welded joint. To solve these problems and improve the quality of welded joints, a new uniform pressure welding method of dissimilar metal plates based on pre-deformation was developed in this work. In this study, using the welding of an AA1060 aluminum plate and an SS304 steel plate with a thickness of 1 mm as an example, it was confirmed through numerical simulation and experimental research that the pre-deformation of the flyer plate controlled the impact angle of the central area of the plate, and it effectively suppressed central non-welding and serious bulge issues. Further, the welding method also reduced the height of the cushion blocks on both sides, thus mitigating aluminum plate thinning at the chamfer, ultimately improving the tensile strength of the joint. Additionally, a microscopic observation showed that the welding interface formed a wavy composite interface, and the connection strength was good. This welding method can also be extended to welding other dissimilar metal plates.

Impaired Experience-Dependent Theta Oscillation Synchronization and Inter-Areal Synaptic Connectivity in the Visual Cortex of Fmr1 KO Mice.

Fragile X syndrome (FX) is the most prevalent inheritable form of autism spectrum disorder (ASD), characterized by hypersensitivity, difficulty in habituating to new sensory stimuli, and intellectual disability. Individuals with FX often experience visual perception and learning deficits. Visual experience leads to the emergence of the familiarity-evoked theta band oscillations in the primary visual cortex (V1) and the lateromedial area (LM) of mice. These theta oscillations in V1 and LM are synchronized with each other, providing a mechanism of sensory multi-areal binding. However, how this multi-areal binding and the corresponding theta oscillations are altered in FX is not known. Using iDISCO whole brain clearing with light-sheet microscopy, we quantified immediate early gene Fos expression in V1 and LM, identifying deficits in experience-dependent neural activity in FX mice. We performed simultaneous in vivo recordings with silicon probes in V1 and LM of awake mice and channelrhodopsin-2-assisted circuit mapping (CRACM) in acute brain slices to examine the neural activity and strength of long-range synaptic connections between V1 and LM in both wildtype (WT) and Fmr1 knockout (KO) mice, the model of FX, before and after visual experience. Our findings reveal synchronized familiarity-evoked theta oscillations in V1 and LM, the increased strength of V1→LM functional and synaptic connections, which correlated with the corresponding changes of presynaptic short-term plasticity in WT mice. The LM oscillations were attenuated in FX mice and correlated with impaired functional and synaptic connectivity and short-term plasticity in the feedforward (FF) V1→LM and feedback (FB) LM→V1 pathways. Finally, using 4Pi single-molecule localization microscopy (SMLM) in thick brain tissue, we identified experience-dependent changes in the density and shape of dendritic spines in layer 5 pyramidal cells of WT mice, which correlated with the functional synaptic measurements. Interestingly, there was an increased dendritic spine density and length in naïve FX mice that failed to respond to experience. Our study provides the first comprehensive characterization of the role of visual experience in triggering inter-areal neural synchrony and shaping synaptic connectivity in WT and FX mice.

Network excitability of stimulation-induced spectral responses helps localize the seizure onset zone

ObjectiveWhile evoked potentials elicited by single pulse electrical stimulation (SPES) may assist seizure onset zone (SOZ) localization during intracranial EEG (iEEG) monitoring, induced high frequency activity has also shown promising utility. We aimed to predict SOZ sites using induced cortico-cortical spectral responses (CCSRs) as an index of excitability within epileptogenic networks. MethodsSPES was conducted in 27 epilepsy patients undergoing iEEG monitoring and CCSRs were quantified by significant early (10–200 ms) increases in power from 10 to 250 Hz. Using response power as CCSR network connection strengths, graph centrality measures (metrics quantifying each site’s influence within the network) were used to predict whether sites were within the SOZ. ResultsAcross patients with successful surgical outcomes, greater CCSR centrality predicted SOZ sites and SOZ sites targeted for surgical treatment with median AUCs of 0.85 and 0.91, respectively. We found that the alignment between predicted and targeted SOZ sites predicted surgical outcome with an AUC of 0.79. ConclusionsThese findings indicate that network analysis of CCSRs can be used to identify increased excitability of SOZ sites and discriminate important surgical targets within the SOZ. SignificanceCCSRs may supplement traditional passive iEEG monitoring in seizure localization, potentially reducing the need for recording numerous seizures.

Synaptic Plasticity in the Injured Brain Depends on the Temporal Pattern of Stimulation.

Neurostimulation protocols are increasingly used as therapeutic interventions, including for brain injury. In addition to the direct activation of neurons, these stimulation protocols are also likely to have downstream effects on those neurons' synaptic outputs. It is well known that alterations in the strength of synaptic connections (long-term potentiation, LTP; long-term depression, LTD) are sensitive to the frequency of stimulation used for induction; however, little is known about the contribution of the temporal pattern of stimulation to the downstream synaptic plasticity that may be induced by neurostimulation in the injured brain. We explored interactions of the temporal pattern and frequency of neurostimulation in the normal cerebral cortex and after mild traumatic brain injury (mTBI), to inform therapies to strengthen or weaken neural circuits in injured brains, as well as to better understand the role of these factors in normal brain plasticity. Whole-cell (WC) patch-clamp recordings of evoked postsynaptic potentials in individual neurons, as well as field potential (FP) recordings, were made from layer 2/3 of visual cortex in response to stimulation of layer 4, in acute slices from control (naive), sham operated, and mTBI rats. We compared synaptic plasticity induced by different stimulation protocols, each consisting of a specific frequency (1 Hz, 10 Hz, or 100 Hz), continuity (continuous or discontinuous), and temporal pattern (perfectly regular, slightly irregular, or highly irregular). At the individual neuron level, dramatic differences in plasticity outcome occurred when the highly irregular stimulation protocol was used at 1 Hz or 10 Hz, producing an overall LTD in controls and shams, but a robust overall LTP after mTBI. Consistent with the individual neuron results, the plasticity outcomes for simultaneous FP recordings were similar, indicative of our results generalizing to a larger scale synaptic network than can be sampled by individual WC recordings alone. In addition to the differences in plasticity outcome between control (naive or sham) and injured brains, the dynamics of the changes in synaptic responses that developed during stimulation were predictive of the final plasticity outcome. Our results demonstrate that the temporal pattern of stimulation plays a role in the polarity and magnitude of synaptic plasticity induced in the cerebral cortex while highlighting differences between normal and injured brain responses. Moreover, these results may be useful for optimization of neurostimulation therapies to treat mTBI and other brain disorders, in addition to providing new insights into downstream plasticity signaling mechanisms in the normal brain.

Exploring the neurocognitive correlates of suicidal ideation in major depressive disorder: The role of frontoparietal and default mode networks

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI.URL: https://www.chictr.org.cn/bin/project/edit?pid=131537.Registration number: ChiCTR2100049646.

An experimental study of cold-formed steel connections with screwed clip angle under tension and shear loads

This paper aims to investigate the performance of typical cold-formed steel (CFS) beam-to-beam connections between floor bearers and floor joists through a series of full-scale experiments. The investigated connections consisted of a lipped channel (floor joist), an unlipped channel (floor bearer), a thin-walled clip angle (connector), and a self-drilling screw (fastener). In this study, customised T-shaped and H-shaped CFS connection specimens were tested to examine the performance under tension and shear loads, respectively. Two sizes of self-drilling screws, 10 G and 14 G, were used with the selected load bearing clip angle. The fabricated connection specimens were subjected to displacement-controlled tension and shear loads. The experiments uncovered the ultimate connection strengths, load-displacement relationships, and failure mechanisms of the designed CFS connections under the applied loads. Moreover, the experimental tensile and shear strengths of the connections were compared with the strengths predicted by the standard design equations. It was found that the screw pullout on the anchored leg of the clip angle was the main mode of failure under the tensile load. On the other hand, two different failure modes—fracturing of 10 G screws or shear buckling of the cantilevered leg of the clip angle with 14 G screws—were observed in the H-shaped specimen under the applied shear load. Among the designed connection specimens, the maximum tensile load capacity was 30.86 kN and the maximum shear load capacity 88.15 kN. The standard design calculations predicted screw pullout failure under tension, while the shear bucking failure mode of the clip angle under shear load was overlooked.

Epilepsy lesion localization method based on brain function network.

In the past, the localization of seizure onset zone (SOZ) primarily relied on traditional EEG signal analysis methods. However, due to their limited spatial and temporal resolution, accurately pinpointing neural activity was challenging, thereby restricting their clinical applicability. Compared with traditional EEG signals, SEEG signals have superior spatial and temporal resolution, and can more accurately record neural activity near epileptic foci, making them better suited for studying SOZ. In addition, the traditional EEG signal analysis methods still have limitations, mainly focusing on the analysis of local signal features, while ignoring the complexity and interconnection of the overall brain network. How to more accurately locate SOZ is still not well resolved. The purpose of this study is to develop an effective positioning method for more accurate positioning. To overcome these limitations, this study proposed a model integrating brain functional network analysis with nonlinear dynamics. We utilized weighted phase lag index (WPLI) to construct brain functional network, epilepic network connectivity strength (ENCS) as the feature, and introduced persistence entropy (PE) for feature fusion, subsequently employing support vector machine (SVM) classification. The proposed method was verified on the HUP-iEEG dataset, our solution identified the SOZ with 0.9440 accuracy, 0.9848 precision, 0.8974 recall rate, 0.9340 F1 score and 0.9697 area under the ROC curve across patients, which outperforms the existing approaches. It exhibits a 2.30 percentage point enhancement in localisation accuracy along with a 2.97 percentage points in AUC compared to others. Our method consider the interactions between nodes in brain network connections, as well as the inherent nonlinear and non-stationary properties of neural signals, to be more robust.