Global Structural Connectivity Research Articles

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.

Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia

BackgroundOffspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated. MethodsA total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity. ResultsOffspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder. ConclusionsThe findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.

Symmetry differences of structural connectivity in multiple sclerosis and healthy state

Focal and diffuse cerebral damages occur in Multiple Sclerosis (MS) that promotes profound shifts in local and global structural connectivity parameters, mainly derived from diffusion tensor imaging. Most of the reconstruction analyses have applied conventional tracking algorithms largely based on the controversial streamline count. For a more credible explanation of the diffusion MRI signal, we used convex optimization modeling for the microstructure-informed tractography2 (COMMIT2) framework. All multi-shell diffusion data from 40 healthy controls (HCs) and 40 relapsing-remitting MS (RRMS) patients were transformed into COMMIT2-weighted matrices based on the Schefer-200 parcels atlas (7 networks) and 14 bilateral subcortical regions. The success of the classification process between MS and healthy state was efficiently predicted by the left DMN-related structures and visual network-associated pathways. Additionally, the lesion volume and age of onset were remarkably correlated with the components of the left DMN. Using complementary approaches such as global metrics revealed differences in WM microstructural integrity between MS and HCs (efficiency, strength). Our findings demonstrated that the cutting-edge diffusion MRI biomarkers could hold the potential for interpreting brain abnormalities in a more distinctive way.

Prediction of Post-stroke Motor Recovery Benefits from Measures of Sub-acute Widespread Network Damages (P12-8.002)

<h3>Objective:</h3> Developing a more accurate post-stroke motor recovery prediction model leveraging brain network connectivity measurements. <h3>Background:</h3> Following an acute ischemic stroke, some patients recover almost completely, while others barely recover. It is known that lesion volume, initial motor impairment, and cortico-spinal tract asymmetry (benchmark features) significantly impact motor changes over time. However, accurate prediction models of patients’ recovery are still missing. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Here, we built on this hypothesis to develop a more accurate post-stroke motor recovery prediction model. <h3>Design/Methods:</h3> We evaluated a dataset of 37 patients (17 women) with upper extremity motor strokes. Their impairment was assessed at 2 weeks (baseline) and 3 months after the stroke using the Fugl-Meyer-Assessment. 18 graph measures of global structural connectivity were obtained using the patients’ T2 lesion mask to virtually reproduce the lesions in 60 healthy streamline tractography connectomes. We added these indirect measures to the benchmark features, and we used a ridge regression regularization in a leave-one-out cross-validation framework to predict motor recovery at 3 months post-injury. <h3>Results:</h3> Prediction accuracy significantly increased when using brain connectivity measures (R²=0.68, 95% CI: 0.64–0.74) as compared to benchmark features alone (R²=0.38, 95% CI: 0.31–0.51). <h3>Conclusions:</h3> We report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients compared to focal and clinical measures used until now. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging (MRI) and would, therefore, have a more substantial clinical impact. <b>Disclosure:</b> An immediate family member of Dr. Pirondini has stock in Reach Neuro. The institution of Dr. Pirondini has received research support from NIH. The institution of an immediate family member of Dr. Pirondini has received research support from NIH. Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. An immediate family member of Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. Maria Giulia Preti has nothing to disclose. Dimitri Van De Ville has nothing to disclose. Prof. Guggisberg has nothing to disclose. Dr. Rivier has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Pyxis Partners.

Abstract 7: Prediction Of Post-stroke Motor Recovery Benefits From Measures Of Sub-acute Widespread Network Damages

Background: Following an acute ischemic stroke, some patients recover almost completely, while others barely recover. It is known that lesion volume, initial motor impairment, and cortico-spinal tract asymmetry (benchmark features) significantly impact motor changes over time. However, accurate prediction models of patients’ recovery are still missing. Recent work suggested that disabilities arise not only from focal structural changes, but also from widespread alterations in inter-regional connectivity. Here, we built on this hypothesis to develop a more accurate post-stroke motor recovery prediction model. Methods: We evaluated a dataset of 37 patients (17 women) with upper extremity motor strokes. Their impairment was assessed at 2 weeks (baseline) and 3 months after the stroke using the Fugl-Meyer-Assessment. 18 graph measures of global structural connectivity were obtained using the patients’ T2 lesion mask to virtually reproduce the lesions in 60 healthy streamline tractography connectomes. We added these indirect measures to the benchmark features, and we used a ridge regression regularization in a leave-one-out cross-validation framework to predict motor recovery at 3 months post-injury. Results: Accuracy in prediction significantly increased when using brain connectivity measures (R 2 =0.68, 95% CI: 0.64-0.74) as compared to benchmark features alone (R 2 =0.38, 95% CI: 0.31-0.51). Conclusion: We reported that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients compared to focal and clinical measures used until now. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging (MRI) and would, therefore, have a more substantial clinical impact.

Longitudinal changes in global structural brain connectivity and cognitive performance in former hospitalized COVID-19 survivors: an exploratory study

BackgroundLong-term sequelae of COVID-19 can result in reduced functionality of the central nervous system and substandard quality of life. Gaining insight into the recovery trajectory of admitted COVID-19 patients on their cognitive performance and global structural brain connectivity may allow a better understanding of the diseases' relevance.ObjectivesTo assess whole-brain structural connectivity in former non-intensive-care unit (ICU)- and ICU-admitted COVID-19 survivors over 2 months following hospital discharge and correlate structural connectivity measures to cognitive performance.MethodsParticipants underwent Magnetic Resonance Imaging brain scans and a cognitive test battery after hospital discharge to evaluate structural connectivity and cognitive performance. Multilevel models were constructed for each graph measure and cognitive test, assessing the groups' influence, time since discharge, and interactions. Linear regression models estimated whether the graph measurements affected cognitive measures and whether they differed between ICU and non-ICU patients.ResultsSix former ICU and six non-ICU patients completed the study. Across the various graph measures, the characteristic path length decreased over time (β = 0.97, p = 0.006). We detected no group-level effects (β = 1.07, p = 0.442) nor interaction effects (β = 1.02, p = 0.220). Cognitive performance improved for both non-ICU and ICU COVID-19 survivors on four out of seven cognitive tests 2 months later (p < 0.05).ConclusionAdverse effects of COVID-19 on brain functioning and structure abate over time. These results should be supported by future research including larger sample sizes, matched control groups of healthy non-infected individuals, and more extended follow-up periods.

Predicting Sumatriptan Responsiveness Based on Structural Connectivity in Patients Newly Diagnosed With Migraine.

We aimed to determine whether structural brain connectivity is significantly associated with the response to sumatriptan in patients with migraine. We retrospectively enrolled patients with newly diagnosed migraine who underwent brain diffusion-tensor imaging (DTI) at the time of diagnosis, with regular follow-up for at least 6 months after the initial diagnosis. Patients were classified into good- and poor-responder groups according to their response to sumatriptan. We analyzed the structural connectivity using DTI by applying graph theory using DSI Studio software. We enrolled 59 patients (35 good responders and 24 poor responders) and 30 healthy controls. Global structural connectivity differed significantly between patients with migraine and healthy controls, while local structural connectivity differed significantly between good and poor responders. The betweenness centrality was lower in good responders than in poor responders in the left lateral geniculate thalamic nucleus (26.078 vs. 41.371, p=0.039) and right medial mediodorsal magnocellular thalamic nucleus (60.856 vs. 90.378, p=0.021), whereas was higher in good responders in the left lateral pulvinar thalamic nucleus (98.365 vs. 50.347, p=0.003) and right medial pulvinar thalamic nucleus (216.047 vs. 156.651, p=0.036). We found that structural connectivity in patients with migraine differed from that in healthy controls. Moreover, the local structural connectivity varied with the response to sumatriptan, which suggests that structural connectivity is a useful factor for predicting how a patient will respond to sumatriptan.

Topological Structural Brain Connectivity Alterations in Aspartylglucosaminuria: A Case-Control Study.

We investigated global and local properties of the structural brain connectivity networks in aspartylglucosaminuria, an autosomal recessive and progressive neurodegenerative lysosomal storage disease. Brain connectivity in aspartylglucosaminuria has not been investigated before, but previous structural MR imaging studies have shown brain atrophy, delayed myelination, and decreased thalamic and increased periventricular WM T2 signal intensity. We acquired diffusion MR imaging and T1-weighted data from 12 patients with aspartylglucosaminuria (mean age, 23 [SD, 8] years; 5 men), and 30 healthy controls (mean age, 25 [SD, 10] years; 13 men). We performed whole-brain constrained spherical deconvolution tractography, which enables the reconstruction of neural tracts through regions with complex fiber configurations, and used graph-theoretical analysis to investigate the structural brain connectivity networks. The integration of the networks was decreased, as demonstrated by a decreased normalized global efficiency and an increased normalized characteristic path length. In addition, the average strength of the networks was decreased. In the local analyses, we found decreased strength in 11 nodes, including, for example, the right thalamus, right putamen, and, bilaterally, several occipital and temporal regions. We found global and local structural connectivity alterations in aspartylglucosaminuria. Biomarkers related to the treatment efficacy are needed, and brain network properties may provide the means for long term follow-up.

Brain structural connectome in neonates with prenatal opioid exposure.

IntroductionInfants with prenatal opioid exposure (POE) are shown to be at risk for poor long-term neurobehavioral and cognitive outcomes. Early detection of brain developmental alterations on neuroimaging could help in understanding the effect of opioids on the developing brain. Recent studies have shown altered brain functional network connectivity through the application of graph theoretical modeling, in infants with POE. In this study, we assess global brain structural connectivity through diffusion tensor imaging (DTI) metrics and apply graph theoretical modeling to brain structural connectivity in infants with POE.MethodsIn this prospective observational study in infants with POE and control infants, brain MRI including DTI was performed before completion of 3 months corrected postmenstrual age. Tractography was performed on the whole brain using a deterministic fiber tracking algorithm. Pairwise connectivity and network measure were calculated based on fiber count and fractional anisotropy (FA) values. Graph theoretical metrics were also derived.ResultsThere were 11 POE and 18 unexposed infants included in the analysis. Pairwise connectivity based on fiber count showed alterations in 32 connections. Pairwise connectivity based on FA values showed alterations in 24 connections. Connections between the right superior frontal gyrus and right paracentral lobule and between the right superior occipital gyrus and right fusiform gyrus were significantly different after adjusting for multiple comparisons between POE infants and unexposed controls. Additionally, alterations in graph theoretical network metrics were identified with fiber count and FA value derived tracts.ConclusionComparisons show significant differences in fiber count in two structural connections. The long-term clinical outcomes related to these findings may be assessed in longitudinal follow-up studies.

Structural brain connectivity in patients with restless legs syndrome: a diffusion tensor imaging study.

To evaluate alterations of global and local structural brain connectivity in patients with restless legs syndrome (RLS). Patients with primary RLS and healthy controls were recruited at a sleep center where they underwent diffusion tensor imaging (DTI) of the brain. We calculated the network measures of global and local structural brain connectivity based on the DTI in both groups using DSI studio program and a graph theory. A total of 69 patients with primary RLS and 51 healthy controls were included in the study. We found a significant difference in the global structural connectivity between the groups. The transitivity in the patients with RLS was lower than that in healthy controls (0.031 vs. 0.033, p = 0.035). Additionally, there were significant differences in the local structural connectivity between the groups. The characteristic path length (r = 0.283, p = 0.018), radius of graph (r = 0.260, p = 0.030), and diameter of graph (r = 0.280, p = 0.019) were all positively correlated with RLS severity, whereas the mean clustering coefficient (r = -0.327, p = 0.006), global efficiency (r = -0.272, p = 0.023), small-worldness index (r = -0.325, p = 0.006), and transitivity (r = -0.351, p = 0.003) were negatively correlated with RLS severity. We identified changes in the global structural connectivity of patients with RLS using graph theory based on DTI, which showed decreased segregation in the brain network compared to healthy controls. These changes are well correlated with RLS severity. We also found changes in local structural connectivity, especially in regions involved in sensorimotor function, which suggests that these areas play a pivotal role in RLS. These findings contribute to a better understanding of the pathophysiology of RLS symptoms.

Cerebral and cerebellar white matter tract alterations in patients with Pantothenate Kinase-Associated Neurodegeneration (PKAN)

BackgroundTo examine structural connectivity of white matter tracts in patients with Pantothenate Kinase-Associated Neurodegeneration (PKAN) dystonia and identify those ones which correlate negatively to severity of symptoms. MethodsIn a group of 41 patients suffering from PKAN dystonia and an age- and gender-matched control group, white matter tractography was carried out, based on diffusion tensor imaging magnetic resonance data. Postprocessing included assessment of Quantitative Anisotropy (QA) using q-space diffeomorphic reconstruction in order to reduce influence of iron accumulation in globus pallidus of patients. ResultsWhole brain tractography presented significantly reduced QA values in patients (0.282 ± 0.056, as compared to controls (0.325 ± 0.046, p < 0.001). 9 fiber clusters of tracts correlated negatively to the dystonia score of patients: the middle cerebellar peduncle and the tracts of both cerebellar hemispheres as well as corpus callosum, forceps minor, the superior cortico-striate tracts and the superior thalamic radiations of both cerebral hemispheres (False Discovery Rate FDR = 0.041). ConclusionThe finding of a reduced global structural connectivity within the white matter and of negative correlation of motor system-related tracts, mainly those between the basal ganglia, cortical areas and the cerebellum, fits well to the concept of a general functional disturbance of the motor system in PKAN.

Glymphatic system function in patients with newly diagnosed focal epilepsy.

IntroductionThe aim of this study was to analyze the glymphatic system function and its relationship with clinical characteristics, global diffusion tensor imaging (DTI) parameters, and global structural connectivity in treatment‐naïve patients with newly diagnosed focal epilepsy.MethodsThis retrospective single‐center study investigated patients with focal epilepsy and healthy controls. All participants underwent routine brain magnetic resonance imaging and DTI. DTI analysis along the perivascular space (DTI‐ALPS) was used to evaluate glymphatic system function. We also calculated the measures of global DTI parameters, including whole‐brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and performed a graph theoretical network analysis to measure global structural connectivity.ResultsA total of 109 patients with focal epilepsy and 88 healthy controls were analyzed. There were no significant differences in the DTI‐ALPS index (1.67 vs. 1.68, p = 0.861) between the groups. However, statistically significant associations were found between the DTI‐ALPS index and age (r = ‐0.242, p = 0.01), FA (r = 0.257, p = 0.007), MD (r = −0.469, p < 0.001), AD (r = −0.303, p = 0.001), RD (r = −0.434, p < 0.001), and the assortative coefficient (r = 0.230, p = 0.016) in patients with focal epilepsy.ConclusionThe main finding of this study is that DTI‐ALPS index is significantly correlated with global DTI parameters and structural connectivity measures of the brain in patients with focal epilepsy. In addition, DTI‐ALPS index decreases with age in these patients. We conclude that the DTI‐ALPS index can be used to investigate glymphatic system function in patients with focal epilepsy.

Brain networks in migraine with and without aura: An exploratory arterial spin labeling MRI study.

The aim of this exploratory study was to investigate the underlying pathomechanisms of migraine with aura (MA) and migraine without aura (MO) in the interictal phase using a connectivity analysis. We prospectively enrolled patients who were newly diagnosed with migraine. All patients underwent brain MRI, including diffusion tensor imaging and arterial spin labeling perfusion MRI. We analyzed the differences between patients with MA and those with MO in structural connectivity based on diffusion tensor imaging and functional connectivity based on arterial spin labeling perfusion MRI using a graph theoretical analysis. We enrolled 58 patients with migraine (11 patients with MA and 47 patients with MO). There were no differences between patients with MA and those with MO in the network measures of global structural connectivity. However, differences in global functional connectivity were found between the two groups. The assortative coefficient was lower in patients with MA than in those with MO (-0.050 vs. -0.012, p=.017). There were no differences in local structural and functional connectivity between patients with MA and those with MO. We found differences in global functional connectivity between patients with MO and those with MA. The study of MA and MO using a connectivity analysis may shed light on migraine pathophysiology. We suggest it is worthwhile to investigate if changes in functional connectivity may serve as novel biomarkers in MA. In this regard, ASL MRI appears to be valuable in the context of network analysis, but further studies are needed to confirm our findings.

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case.

Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.

Early Life Adversities and Borderline Intellectual Functioning Negatively Impact Limbic System Connectivity in Childhood: A Connectomics-Based Study.

Early life adversity (ELA) in childhood is a major risk factor for borderline intellectual functioning (BIF). BIF affects both adaptive and intellectual abilities, commonly leading to school failure and to an increased risk to develop mental and social problems in the adulthood. This study aimed to investigate the neurobiological underpinnings of ELA associated with BIF in terms of global topological organization and structural connectivity and their relation with intellectual functioning. BIF (N=32) and age-matched typical development (TD, N=14) children were evaluated for intelligence quotient (IQ), behavioral competencies, and ELA. Children underwent an anatomical and diffusion-weighted MR imaging (DWI) protocol. Global brain topological organization was assessed measuring segregation and integration indexes. Moreover, structural matrices, measuring normalized number of fibers (NFn), were compared between the 2 groups using network-based statistics. Finally, a linear regression model was used to explore the relationship between network parameters and clinical measures. Results showed increased behavioral difficulties and ELA, together with decreased network integration in BIF children. Moreover, significantly lower NFn was observed in the BIF group (p=.039) in a sub-network comprising anterior and posterior cingulate, the pericallosal sulcus, the orbital frontal areas, amygdala, basal ganglia, the accumbens nucleus, and the hippocampus. Linear regression showed that NFn significantly predicted IQ (p<.0001). This study demonstrated that ELA in children with BIF is associated with a decreased information integration at the global level, and with an altered structural connectivity within the limbic system strictly related to the intellectual functioning.

Structural organization of the praxis network predicts gesture production: Evidence from healthy subjects and patients with schizophrenia

Hand gestures are an integral part of social interactions and communication. Several imaging studies in healthy subjects and lesion studies in patients with apraxia suggest the praxis network for gesture production, involving mainly left inferior frontal, posterior parietal and temporal regions. However, little is known about the structural connectivity underlying gesture production. We recruited 41 healthy participants and 39 patients with schizophrenia. All participants performed a gesture production test, the Test of Upper Limb Apraxia, and underwent diffusion tensor imaging. We hypothesized that gesture production is associated with structural network connectivity as well as with tract integrity. We defined the praxis network as an undirected graph comprised of 13 bilateral regions of interest and derived measures of local and global structural connectivity and tract integrity from Finsler geometry. We found an association of gesture deficit with reduced global and local efficiency of the praxis network. Furthermore, reduced tract integrity, for example in the superior longitudinal fascicle, arcuate fascicle or corpus callosum were related to gesture deficits. Our findings contribute to the understanding of structural correlates of gesture production as they first present diffusion tensor imaging data in a combined sample of healthy subjects and a patient cohort with gestural deficits.

Differences of connectivity between ESRD patients with PD and HD.

ObjectivesThe aim of this study was to investigate alterations in structural and functional brain connectivity between patients with end‐stage renal disease (ESRD) who were undergoing peritoneal dialysis (PD) and hemodialysis (HD).MethodsWe enrolled 40 patients with ESRD who were undergoing PD (20 patients) and HD (20 patients). We also enrolled healthy participants as a control group. All of the subjects underwent diffusion tensor imaging (DTI) and resting‐state functional magnetic resonance imaging (rs‐fMRI). Using data from the structural and functional connectivity matrix based on DTI and rs‐fMRI, we calculated several network measures using graph theoretical analysis.ResultsThe measures of global structural connectivity were significantly different between the patients with ESRD who were undergoing PD and healthy subjects. The global efficiency and local efficiency in the patients with PD were significantly decreased compared with those in healthy participants. However, all of the measures of global structural connectivity in the patients with HD were not different from those in healthy participants. Conversely, in the global functional connectivity, the characteristic path length was significantly increased and the small‐worldness index was decreased in patients with HD. However, the measures of the global functional connectivity in the patients with PD were not different from those in healthy subjects.ConclusionThis study revealed that alterations in structural and functional connectivity in patients who were undergoing PD and HD were different than those in healthy controls. These findings suggest that brain networks may be affected by different types of renal replacement therapy.

P0730ALTERATION OF BRAIN CONNECTIVITY IN NEUROLOGICALLY ASYMPTOMATIC PATIENTS WITH CHRONIC KIDNEY DISEASE

Abstract Background and Aims Our previous study demonstrated that patients in End stage renal disease had decreased structural and functional brain connectivity, and there was significant association between brain connectivity and cognitive function. The aim of this study was to evaluate the alterations of structural and functional connectivity using graph theoretical analysis in the neurologically asymptomatic patients with relatively early stage chronic kidney disease (CKD). Method We prospectively enrolled neurologically asymptomatic 20 patients with CKD stage 3 and 20 healthy controls, and all of the subjects underwent diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI). Using data from the structural and functional connectivity matrix based on DTI and rs-fMRI, we calculated network measures, including global efficiency, local efficiency, mean clustering coefficient, characteristic path length, and small-worldness index, and investigated the differences between the patients with CKD and healthy controls. Results The patients with CKD had altered global structural connectivity and preserved functional connectivity compared to healthy controls. The all of the measures of global structural connectivity were significantly different between the patients with CKD and healthy controls. However, all of the measures of global functional connectivity in the CKD patients were not different from those in healthy participants. In the CKD patients, the functional betweenness centrality of the right insular cortex, right occipital pole, and right thalamus was significantly different from that in healthy subjects. The structural betweenness centrality of the left calcarine, right posterior cingulum was significantly different from that in healthy subjects. Conclusion There were significant alterations of global structural connectivity between patients with CKD and control. However, functional connectivity of brain network was preserved in contrast to ESRD patients.

The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium.

Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants. The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition. Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44). This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients.

Computational studies of the influence of different network parameters on the dynamic and topological network effects of brain stimulation can enhance our understanding of different outcomes between individuals. In this study, a brain stimulation session along with the subsequent post-stimulation brain activity is simulated for a period of one day using a network of modified Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine how differences in the inter-region connectivity and the excitability of stimulated regions at the time of stimulation can affect post-stimulation behaviours. Our findings indicate that the initial inter-region connectivity can heavily affect the changes that stimulation induces in the connectivity of the network. Moreover, differences in the excitability of the stimulated regions seem to lead to different post-stimulation connectivity changes across the model network, including on the internal connectivity of non-stimulated regions.