Structural Connectivity Research Articles

Multiscale detrended cross-correlation coefficient: estimating coupling in non-stationary neurophysiological signals

The brain consists of a vastly interconnected network of regions, the connectome. By estimating the statistical interdependence of neurophysiological time series, we can measure the functional connectivity (FC) of this connectome. Pearson’s correlation (rP) is a common metric of coupling in FC studies. Yet rP does not account properly for the non-stationarity of the signals recorded in neuroimaging. In this study, we introduced a novel estimator of coupled dynamics termed multiscale detrended cross-correlation coefficient (MDC3). Firstly, we showed that MDC3 had higher accuracy compared to rP and lagged covariance using simulated time series with known coupling, as well as simulated functional magnetic resonance imaging (fMRI) signals with known underlying structural connectivity. Next, we computed functional brain networks based on empirical magnetoencephalography (MEG) and fMRI. We found that by using MDC3 we could construct networks of healthy populations with significantly different properties compared to rP networks. Based on our results, we believe that MDC3 is a valid alternative to rP that should be incorporated in future FC studies.

Abstract 4121198: Structural Network Alterations After Cardiopulmonary Bypass In a Juvenile Porcine Model

Background: Cardiopulmonary bypass (CPB) can trigger inflammatory and oxidative stresses in the developing brain. Clinical studies showed altered brain network structure in children after infant cardiac surgery. However, the impact of CPB on structural connectivity remains poorly understood. This study aims to determine the effects of CPB on structural connectivity and underlying cellular events using a juvenile porcine model. Methods: CPB (150 min total) was performed on 2-week-old Yorkshire piglets. High-resolution diffusion tensor imaging (DTI) and neurite orientation dispersion and density (NODDI) imaging were performed 4 weeks post-CPB in a total of 12 animals (Control; n=7, CPB; n=5). Structural connectivity assay together with histological analysis was conducted to assess the brain network organization. Results: Our network analysis (Image 1) revealed a CPB-induced reduction of structural connections in particular nodes, such as in the anterior prefrontal cortex (APC), primary somatosensory cortex, substantia nigra (SN), and globus pallidus (GP). In contrast, there was an increase in the premotor cortex (PreMC), primary motor cortex (PriMC), dorsal posterior cingulate cortex (DPCC), and somatosensory cortex (SAC). Three-dimensional images were generated based on these altered nodes, and tractography was generated to indicate changed fiber tracking (Image 2). We found reduced network connections between the basal ganglia and frontal cortex, and increased connections between the motor and posterior region. DTI and NODDI indicated that microstructures of the superior corona radiata (SCR), internal capsule (PLIC), and anterior prefrontal (AP-WM), motor (PreM-/PriM-WM), and somatosensory white matter (SA-WM) were significantly altered after CPB (Image 3). While Iba1+ microglia was activated across all brain regions after CPB (P<.05), CPB-induced oligodendrocyte immatureness was identified in the WMs involved in APC-SN and APC-GP pathways (P<.05). Notably, CPB increased the number of mature oligodendrocytes in motor and SA-WMs (P<.05) where structural connections were increased after CPB. In addition, we found SN dopaminergic neuron injury after CPB (P<.05). Conclusion: CPB altered structural network organization in the developing brain. Spatial differences in oligodendrocyte responses and susceptibility of specific subpopulations of neurons may contribute to the unique connectivity alterations observed after CPB.

Diffusion MRI with machine learning

Abstract Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of disease and injury, and for neuroscience research. Analyzing the dMRI data to extract useful information for medical and scientific purposes can be challenging. The dMRI measurements may suffer from strong noise and artifacts, and may exhibit high intersession and interscanner variability in the data, as well as intersubject heterogeneity in brain structure. Moreover, the relationship between measurements and the phenomena of interest can be highly complex. Recent years have witnessed increasing use of machine learning methods for dMRI analysis. This manuscript aims to assess these efforts, with a focus on methods that have addressed data preprocessing and harmonization, microstructure mapping, tractography, and white matter tract analysis. We study the main findings, strengths, and weaknesses of the existing methods and suggest topics for future research. We find that machine learning may be exceptionally suited to tackle some of the difficult tasks in dMRI analysis. However, for this to happen, several shortcomings of existing methods and critical unresolved issues need to be addressed. There is a pressing need to improve evaluation practices, to increase the availability of rich training datasets and validation benchmarks, as well as model generalizability, reliability, and explainability concerns.

Septum of the penis – dissection, anatomical description and functional relevance

Abstract Background The septum of the penis or the pectiniform septum (from Latina pecten) is a connective structure that separates the two corpora cavernosa of the penis. It is formed through the joining of the circular fibers of the tunica albuginea, which envelops the corpora cavernosa. The septum neither completely separates, nor entirely joins the two corpora cavernosa. Results We dissected the penile septum in 10 formalized bodies. The dissections were carried out using magnifying lenses, emphasizing the connective structures. We studied the structure of the septum using transverse and sagittal dissection planes. We identified the penile septum as a structure consisting of clusters of tendinous cords incompletely separating the two cavernous structures. The septum completely separates the two corpora cavernosa in its posterior segment. As we progress forward, the septum starts resembling the tendinous cords that attach to the papillary muscles of the heart. These cords are differentiated from the internal layer of the albuginea of each corpus cavernosum. We evaluated the opportunity of considering the anterior and posterior intercavernous ligaments as septal structures. Conclusion In this type of construction, the septum maintains both the hemodynamic and mechanical coherence of the cavernous structures and allows penile movement more efficiently than a continuous septal structure. The septum enables the lengthening of the penis and simultaneous filling with blood of both its corpora cavernosa through the transseptal vascular anastomosis. This allows for penile deformation during erection to be avoided. Our study also provides a description of the way the corpora cavernosa attach to the bulbus of corpus spongiosum.

INNV-28. CONNECTOMICS-GUIDED GLIOMA RESECTION: HOW CHANGES IN STRUCTURAL CONNECTIVITY CORRELATE WITH LANGUAGE FUNCTION

Abstract Postoperative aphasia is a risk inherent to resections of brain masses in language eloquent areas. Neurosurgical strategies to minimize damage of functional language structures include awake craniotomies combined with stimulation mapping and intra-operative speech and language pathology (SLP) testing. Until now, consideration of white matter tracts involved in language processing as measured by diffusion tensor imaging (DTI) has been minimally incorporated into resection planning. In addition, there is limited understanding as to the association between specific tracts and aphasia risk. Quicktome™ by Omniscient Neurotechnology is clinically-oriented connectomics software that uses DTI sequences from MRIs to model connectivity between geographically distinct brain regions. This model can then be integrated with intraoperative navigation to avoid language connections during resection. Here, we investigate how language tract changes affect clinical aphasia. Patients with language-eloquent gliomas with available pre- and post-operative DTI and SLP evaluations were included in this retrospective study. Structural networks were quantified using Quicktome™ and compared using Spearman correlation. Changes in language function were evaluated using the Boston Naming Test and the Western Aphasia Battery. Patients with postoperative auditory verbal deficits showed a moderate correlation in connectivity changes (ρ=0.42), whereas patients with postoperative naming deficits showed a weak correlation (ρ=0.19). The inferior frontal junction, anterior portion (IFJa), and the superior temporal sulcus, ventral posterior portion (STSvp), in the right hemisphere demonstrated the most associated structural connectivity changes. To our knowledge, this is the first study which uses Quicktome™ to directly associate postoperative connectivity with aphasia outcomes. Understanding the interplay between structural connectivity and neurological symptoms can elucidate neural pathways underlying cortical function with the potential to reduce neurosurgical postoperative morbidity.

NCOG-15. CONNECTOME-BASED APPROACHES FOR PRESERVING COGNITIVE FUNCTION AND MINIMIZING DELIRIUM DURING GLIOMA RESECTION: A PILOT STUDY

Abstract AIM The surgical treatment of gliomas poses significant challenges due to the involvement of complex neural networks critical for cognitive functions. This study reviews the application of connectome-based approaches to minimize cognitive impairments and delirium during glioma resection, focusing on networks related to cognitive functions: the Default Mode Network (DMN), Dorsal Attention Network (DAN), Salience Network (SN), and Central Executive Network (CEN). METHODS Ten patients underwent surgery utilizing cloud-based connectomics software (Quicktome®), which maps the brain’s structural and functional connectivity. Preoperative MRIs with structural and functional connectome were performed for preoperative planning and intraoperative navigation. Preoperative neuropsychological assessments were conducted for elective cases. Only one patient was able to undergo awake craniotomy due to various medical, neurological and psychological limitations. Intraoperatively, with connectome-navigation guidance, a connectomics-based approach was conducted to preserve the networks. A semiquantitative analysis was performed as described (https://pubmed.ncbi.nlm.nih.gov/36719613). Pre- and postoperative (inpatient and 2 week follow up) RASS and NuDESC delirium screenings were performed, with long-term cognitive evaluations and repeat connectomics imaging planned. RESULTS Three out of ten patients presented with rapid functional deterioration and needed urgent surgical decompression had postoperative delirium. Connectome analysis showed involvement of cognition-related networks in these patients. Two out of 3 patients showed improvement in delirium scores at a two-week follow-up after tumor resection. CONCLUSION This pilot study suggests that factors such as acute presentation, emergency surgery, and tumor location involving and disrupting the DMN, SN, DAN, and CEN networks may contribute to early postoperative delirium. The study may pave the way for the efficacy of connectomics in preserving cognitive functions post-operatively, particularly when awake craniotomy is not possible. This approach holds promise for improving surgical outcomes, survival, and the quality of life for patients with gliomas by mitigating the cognitive impacts of tumor resection and postoperative complications.

CNSC-66. STRUCTURAL AND ELECTROPHYSIOLOGICAL CONNECTIVITY IN GLIOBLASTOMA IS MEDIATED BY TUMOR AND IMMUNE DERIVED CYTOKINES

Abstract BACKGROUND In glioblastomas (GBM), the pleiotropic cytokine interleukin-6 (IL-6) upregulates PD-L1 expression. This results in local immunosuppression favorable to tumor progression, and may account for the limited efficacy of immune checkpoint inhibition. Additionally, IL-6 increases synaptogenesis during development, and contributes to neuronal network remodeling following focal brain or spinal cord injury. Therefore, the aim was to determine whether IL-6 contributes to GBM-induced circuit remodeling from a structural and electrophysiological perspective. METHODS In magnetoencephalography (MEG)-based intratumoral regions of High- (HFC) and Low-Functional Connectivity (LFC) from GBM patients, the expression of IL-6 and GAP43 was compared using bulk and single-cell RNA sequencing and immunofluorescence staining in biological replicates (n=44). In mouse postnatal cortical neurons and primary patient-derived GBM cell cocultures, the expression of Ki67, GAP43, tumor connectivity and neuronal activity were monitored after exogenous application of recombinant human IL-6 (rIL-6) or microglial depletion using PLX5622. Results. IL-6 and GAP43 were overexpressed in HFC compared to LFC regions. In neuron-GBM cocultures, the tumour proliferation index was significantly increased by rIL-6 and decreased by PLX5622. Morphologically, the number of microtubes per tumor cell was significantly increased by rIL-6 and decreased by PLX5622. The expression of GAP43 was inconstantly increased by rIL-6, suggesting the regulation of other pathways involved in tumour microtube formation. Multielectrode array recordings showed a significant increase or decrease in the neuronal activity, following the addition of rIL-6 or microglial depletion, respectively. CONCLUSIONS IL-6-signaling increases proliferation, structural and electrophysiological connectivity in gliomas and may contribute to neuronal network hyper-excitability and synchrony. Microglial depletion provided opposite effects. Additional experiments are mandatory to determine whether the effects of IL-6 on GBM cells depend on the presence of microglial cells or not. These data will be critical to design new therapeutic options, likely to improve the oncological and functional outcomes of patients treated for GBM.

Assessing the causal role of the structural connectome in temporomandibular disorders: A Mendelian randomization study

ABSTRACT Objective We examined the relationships between the structural connectome and temporomandibular disorders (TMDs). Methods Bidirectional Mendelian randomization analyses were conducted using Genome-wide association studies data on the structural connectome and TMDs. Results Positive associations with TMD risk were found for white matter structural connectivity from the left hemisphere limbic network to putamen, left hemisphere salience_ventral attention network to caudate, right hemisphere visual network to thalamus, and right hemisphere salience_ventral attention network to right hemisphere control network, while negative associations were observed for connectivity from the left hemisphere control and somatomotor networks to pallidum, left hemisphere somatomotor network to right hemisphere dorsal attention network, and right hemisphere somatomotor network to hippocampus (p< 0.05). In TMD patients, connectivity from the Left-hemisphere visual network to putamen was reduced, whereas connectivity from the Left-hemisphere limbic network to left-hemisphere control network was increased (p< 0.05). Conclusion Our findings provide insights into the TMD pathogenesis.

The brain’s first “traffic map” through Unified Structural and Functional Connectivity (USFC) modeling

The brain’s white matter connections are thought to provide the structural basis for its functional connections between distant brain regions but how our brain selects the best structural routes for functional communications remains poorly understood. In this study, we propose a Unified Structural and Functional Connectivity (USFC) model and use an “economical assumption” to create the brain’s first “traffic map” reflecting how frequently each segment of the brain structural connection is used to achieve the global functional communication system. The resulting USFC map highlights regions in the subcortical, default-mode, and salience networks as the most heavily traversed nodes and a midline frontal-caudate-thalamus-posterior cingulate-visual cortex corridor as the backbone of the whole brain connectivity system. Our results further revealed a striking negative association between structural and functional connectivity strengths in routes supporting negative functional connections, as well as significantly higher efficiency metrics and better predictive performance for cognition in the USFC connectome when compared to structural and functional ones alone. Overall, the proposed USFC model opens up a new window for integrated brain connectome modeling and provides a major leap forward in brain mapping efforts for a better understanding of the brain’s fundamental communication mechanisms.

Processing demands modulate the activities and functional connectivity patterns of the posterior (VWFA-1) and anterior (VWFA-2) VWFA

Previous studies have shown that the visual word form area (VWFA) has structural and intrinsic functional connectivity with both language and attention networks. Nevertheless, it is still unclear how the functional connectivity pattern of the VWFA is regulated by processing demands induced by experimental tasks, and whether processing demands differentially regulate the posterior (VWFA-1) and anterior (VWFA-2) subregions of the VWFA. To address these questions, the present study adopted two tasks varying in processing demands (i.e., verbal and non-verbal tasks), and used generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses to explore the task-dependent functional connectivity patterns of the two subregions of the VWFA. Activation analysis revealed that the VWFA-2 showed higher activation for the verbal task than the non-verbal task, while there were no activation differences in the VWFA-1 after controlling for the stimulus driven effects. Functional and effective connectivity analyses revealed that, for both VWFA-1 and VWFA-2, the verbal task enhanced connections from VWFAs to the ventral language regions (e.g., the left orbital frontal cortex), while the non-verbal task enhanced connections from VWFAs to the dorsal visuospatial regions (e.g., the left intraparietal sulcus). Results of the present study indicate that processing demands induced by tasks modulate both the local activity and functional connectivity patterns of the VWFA, providing new insights for understanding its domain-general function.

Mother-Child Closeness and Adolescent Structural Neural Networks: A Prospective Longitudinal Study of Low-Income Families.

Mother-child closeness, a mutually trusting and affectionate bond, is an important factor in shaping positive youth development. However, little is known about the neural pathways through which mother-child closeness are related to brain organization. Utilizing a longitudinal sample primarily from low-income families (N=181; 76% African American youth and 54% female), this study investigated the associations between mother-child closeness at ages 9 and 15 and structural connectivity organization (network integration, robustness, and segregation) at age 15. The assessment of mother-child closeness included perspectives from both mother and child. The results revealed that greater mother-child closeness is linked with increased global efficiency and transitivity, but not modularity. Specifically, both the mother's and child's report of closeness at age 15 predicted network metrics but report at age 9 did not. Our findings suggest that mother-child closeness is associated with neural white matter organization, as adolescents who experienced greater mother-child closeness displayed topological properties indicative of more integrated and robust structural networks.

Reproducible routes: reliably navigating the connectome to enrich personalized brain stimulation strategies

Non-invasive brain stimulation (NIBS) technologies, such as repetitive transcranial magnetic stimulation (rTMS), offer significant therapeutic potential for a growing number of neuropsychiatric conditions. Concurrent with the expansion of this field is the swift evolution of rTMS methodologies, including approaches to optimize stimulation site planning. Traditional targeting methods, foundational to early successes in the field and still widely employed today, include using scalp-based heuristics or integrating structural MRI co-registration to align the transcranial magnetic stimulation (TMS) coil with anatomical landmarks. Recent evidence, however, supports refining and personalizing stimulation sites based on the target's structural and/or functional connectivity profile. These connectomic approaches harness the network-wide neuromodulatory effects of rTMS to reach deeper brain structures while also enabling a greater degree of personalization by accounting for heterogenous network topology. In this study, we acquired baseline multimodal magnetic resonance (MRI) at two time points to evaluate the reliability and reproducibility of distinct connectome-based strategies for stimulation site planning. Specifically, we compared the intra-individual difference between the optimal stimulation sites generated at each time point for (1) functional connectivity (FC) guided targets derived from resting-state functional MRI and (2) structural connectivity (SC) guided targets derived from diffusion tensor imaging. Our findings suggest superior reproducibility of SC-guided targets. We emphasize the necessity for further research to validate these findings across diverse patient populations, thereby advancing the personalization of rTMS treatments.

Global changes in the pattern of connectivity in developmental prosopagnosia.

Developmental prosopagnosia is a neurodevelopmental condition characterized by difficulties in recognizing the identity of a person from their face. While current theories of the neural basis of developmental prosopagnosia focus on the face processing network, successful recognition of face identities requires broader integration of neural signals across the whole brain. Here, we asked whether disruptions in global functional and structural connectivity contribute to the face recognition difficulties observed in developmental prosopagnosia. We found that the left temporal pole was less functionally connected to the rest of the brain in developmental prosopagnosia. This was driven by weaker contralateral connections to the middle and inferior temporal gyri, as well as to the medial prefrontal cortex. The pattern of global connectivity in the left temporal pole was also disrupted in developmental prosopagnosia. Critically, these changes in global functional connectivity were only evident when participants viewed faces. Structural connectivity analysis revealed localized reductions in connectivity between the left temporal pole and a number of regions, including the fusiform gyrus, inferior temporal gyrus, and orbitofrontal cortex. Our findings underscore the importance of whole-brain integration in supporting typical face recognition and provide evidence that disruptions in connectivity involving the left temporal pole may underlie the characteristic difficulties of developmental prosopagnosia.

Study of microstructural evolution during operation of electrically connected components and analysis of failure mechanism

Abstract As a key current-carrying structure of high-voltage bushings, the reliability of electrical connection components is crucial to the safe and stable operation of power equipment. To obtain the microstructural evolution of electrical connection components with different deterioration states, CUD strap contactors were deteriorated in different ways, and electron backscatter diffraction (EBSD) technique was used to test the microstructure of strap contactors with different deterioration states. The results showed that compared to the unused contactors, the contact resistance of the contactors under the combined effect of friction and high temperature increased 203.12 times and was in a failed state. During the process from unused state to wear deterioration, high temperature deterioration, and then to eventual failure of the contactors, the average grain size gradually grows from 8.15 μm to 25 μm, the dislocation density gradually decreases from 2.38×1014 m-2 to 1.04×1014 m-2, and there are a significant proportion of the recrystallized organization. These changes are detrimental to the mechanical properties of the contactors. In addition, the distribution of grain boundaries in the contact area proves the occurrence of over-temperature phenomenon in this area, which will accelerate the deterioration of the contactors and eventually lead to the failure of the component. The relevant conclusions can provide a theoretical basis for the design of electrical connection structure of strap contacts as well as the study of deterioration mechanism.

Morphological similarity and white matter structural mapping of new daily persistent headache: a structural connectivity and tract-specific study

BackgroundNew daily persistent headache (NDPH) is a rare primary headache disorder characterized by daily and persistent sudden onset headaches. Specific abnormalities in gray matter and white matter structure are associated with pain, but have not been well studied in NDPH. The objective of this work is to explore the fiber tracts and structural connectivity, which can help reveal unique gray and white matter structural abnormalities in NDPH.MethodsThe regional radiomics similarity networks were calculated from T1 weighted (T1w) MRI to depict the gray matter structure. The fiber connectivity matrices weighted by diffusion metrics like fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) were built, meanwhile the fiber tracts were segmented by anatomically-guided superficial fiber segmentation (Anat-SFSeg) method to explore the white matter structure from diffusion MRI. The considerable different neuroimaging features between NDPH and healthy controls (HC) were extracted from the connectivity and tract-based analyses. Finally, decision tree regression was used to predict the clinical scores (i.e. pain intensity) from the above neuroimaging features.ResultsT1w and diffusion MRI data were available in 51 participants after quality control: 22 patients with NDPH and 29 HCs. Significantly decreased morphological similarity was found between the right superior frontal gyrus and right hippocampus. The superficial white matter (SWM) showed significantly decreased FA in fiber tracts including the right superficial-frontal, left superficial-occipital, bilateral superficial-occipital-temporal (Sup-OT) and right superficial-temporal, meanwhile significant increased RD was found in the left Sup-OT. For the fiber connectivity, NDPH showed significantly decreased FA in the bilateral basal ganglion and temporal lobe, increased MD in the right frontal lobe, and increased RD in the right frontal lobe and left temporal-occipital lobe. Clinical scores could be predicted dominantly by the above significantly different neuroimaging features through decision tree regression.ConclusionsOur research indicates the structural abnormalities of SWM and the neural pathways projected between regions like right hippocampus and left caudate nucleus, along with morphological similarity changes between the right superior frontal gyrus and right hippocampus, constitute the pathological features of NDPH. The decision tree regression demonstrates correlations between these structural changes and clinical scores.

Structure connectivity of a class of Cayley graph

As a generalization of connectivity, structure connectivity was proposed. For connected graphs G and T, the T-structure connectivity κ ( G ; T ) (resp. T-substructure connectivity κ s ( G ; T ) ) of G is the minimum cardinality of a set of subgraphs F of G that each is isomorphic to T (resp. a connected subgraph of T) such that G − F is disconnected or the singleton. n-dimensional graph Q n + is a class of Cayley graph, which obtained by adding edges to n-dimensional hypercubes. In this paper, we study star, path and cycle structure connectivity and substructure connectivity of graph Q n + for n ≥ 5 . For star ( K 1 , m ) structure, K 1 , m -structure (substructure) connectivity of Q n + is ⌈ n + 1 2 ⌉ for 2 ≤ m ≤ n − 1 . For path ( P k ) and cycle ( C k ) structures, we show that if 3 ≤ k ≤ 2 n , then P k -structure (substructure) connectivity is ⌈ 2 ( n + 1 ) k + 1 ⌉ and ⌈ 2 ( n + 1 ) k ⌉ for odd k and even k, respectively. We also obtain that P k -structure connectivity is equal to C k -substructure connectivity. Further, we calculate κ ( Q n + ; C 2 k ) = ⌈ n + 1 k ⌉ for 3 ≤ k ≤ n .

Structural brain connectivity does not associate with childhood trauma in individuals with schizophrenia

BackgroundSchizophrenia is a brain dysconnectivity disorder. However, it is not well understood whether the experience of childhood trauma (CT) affects dysconnectivity in individuals with schizophrenia (SZ). Using a network-based approach, we examined whether self-reported CT would explain additional variance compared to whole-brain topology and structural connectivity changes in SZ versus healthy controls (HC). Material and methodsCT was assessed in 51 SZ (mean age ± standard deviation 44 ± 11 years) and 140 HC (34.0 ± 12 years). Structural brain networks were constructed from T1-weighted MR and diffusion-MRI scans using non-tensor based tractography. Group differences in whole-brain topology and permutation-based statistics were examined and corrected for age and sex. ResultsSZ showed reductions in efficiency, strength, clustering and density (p <0.01) as well as increases in path length (F(range) = 4.71-18.1, p <0.03) when compared to HC. We also observed hypoconnectivity in a subnetwork of frontotemporal, frontoparietal and occipital regions in SZ relative to HC (T > 4.0, p <0.001). However, we did not find that high CT levels were related to structural network differences or structural connectivity changes in SZ. ConclusionsCT did not impact on topology or subnetwork connectivity changes in SZ. High CT levels were also not associated with any differences in network organisation irrespective of diagnosis. However, our findings confirm that SZ showed both network-level reductions and increases in a subnetwork. These findings suggest that the patterns of neuroanatomical dysconnectivity in established schizophrenia may not be influenced by CT. Future studies are needed to investigate the association between CT and structural dysconnectivity in schizophrenia.

Effect of the connection structure of zirconia dental implants on biomechanical properties

The connection structure of zirconia dental implants significantly influences their biomechanical behavior and plays a crucial role in the overall service performance of the implant system. This study aims to compare the stress distribution of zirconia implants featuring various internal connection structures under different working conditions. Four distinct types of connection structures were designed for zirconia dental implants: triangular, quadrilateral, hexagonal, and hexalobular plus connections. Additionally, the finite element method was employed to analyze these structures under three working conditions: a static load test model, a bone level model, and a torsion model. Results indicated that in the static load test model, the hexagonal structure experienced the highest stress value at 1284.9 MPa due to its thin neck wall, whereas the hexalobular plus connected implant exhibited the lowest stress value at 1252.9 MPa. In the bone level model, the triangular connection structure demonstrated poor stress distribution for cortical bone and cancellous bone at 69.606 MPa and 7.8191 MPa, respectively. Conversely, the hexalobular plus connection yielded superior stress results for cortical bone and cancellous bone, with values of 69.606 MPa and 7.8191 MPa, respectively. In the torsion model, the hexalobular plus-connected implant exhibits the highest stress value at 210.37 MPa, while maintaining the smallest force transmission angle. Therefore, given that the abutment necessitates a greater range of installation angles and improved torque transmission, the hexalobular plus connection structure may represent the optimal choice.

Working memory related functional connectivity in adult ADHD and its amenability to training: A randomized controlled trial

BackgroundWorking memory (WM) deficits are among the most prominent cognitive impairments in attention deficit hyperactivity disorder (ADHD). While functional connectivity is a prevailing approach in brain imaging of ADHD, alterations in WM-related functional brain networks and their malleability by cognitive training are not well known. We examined whole-brain functional connectivity differences between adults with and without ADHD during n-back WM tasks and rest at pretest, as well as the effects of WM training on functional and structural brain connectivity in the ADHD group. MethodsForty-two adults with ADHD and 36 neurotypical controls performed visuospatial and verbal n-back tasks during functional magnetic resonance imaging (fMRI). In addition, seven-minute resting state fMRI data and diffusion-weighted MR images were collected from all participants. The adults with ADHD continued into a 5-week randomized controlled WM training trial (experimental group training on a dual n-back task, n = 21; active control group training on Bejeweled II video game, n = 21), followed by a posttraining MRI. Brain connectivity was examined with Network-Based Statistic. ResultsAt the pretest, adults with ADHD had decreased functional connectivity compared with the neurotypical controls during both n-back tasks in networks encompassing fronto-parietal, temporal, occipital, cerebellar, and subcortical brain regions. Furthermore, WM-related connectivity in widespread networks was associated with performance accuracy in a continuous performance test. Regarding resting state connectivity, no group differences or associations with task performance were observed. WM training did not modulate functional or structural connectivity compared with the active controls. ConclusionOur results indicate large-scale abnormalities in functional brain networks underlying deficits in verbal and visuospatial WM commonly faced in ADHD. Training-induced plasticity in these networks may be limited

A combined DTI-fMRI approach for optimizing the delineation of posteromedial versus anterolateral entorhinal cortex.

In the entorhinal cortex (EC), attempts have been made to identify the human homologue regions of the medial (MEC) and lateral (LEC) subregions using either functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI). However, there are still discrepancies between entorhinal subdivisions depending on the choice of connectivity seed regions and the imaging modality used. While DTI can be used to follow the white matter tracts of the brain, fMRI can identify functionally connected brain regions. In this study, we used both DTI and resting-state fMRI in 103 healthy adults to investigate both structural and functional connectivity between the EC and associated cortical brain regions. Differential connectivity with these regions was then used to predict the locations of the human homologues of MEC and LEC. Our results from combining DTI and fMRI support a subdivision into posteromedial (pmEC) and anterolateral (alEC) EC and reveal a confined border between the pmEC and alEC. Furthermore, the EC subregions obtained by either imaging modality showed similar distinct whole-brain connectivity profiles. Optimizing the delineation of the human homologues of MEC and LEC with a combined, cross-validated DTI-fMRI approach allows to define a likely border between the two subdivisions and has implications for both cognitive and translational neuroscience research.