Connectivity Of Large-scale Networks Research Articles

Altered brain functional network connectivity and topology in type 2 diabetes mellitus

IntroductionType 2 diabetes mellitus (T2DM) accelerates brain aging and disrupts brain functional network connectivity, though the specific mechanisms remain unclear. This study aimed to investigate T2DM-driven alterations in brain functional network connectivity and topology.MethodsEighty-five T2DM patients and 67 healthy controls (HCs) were included. All participants underwent clinical, neuropsychological, and laboratory tests, followed by MRI examinations, including resting-state functional magnetic resonance imaging (rs-fMRI) and three-dimensional high-resolution T1-weighted imaging (3D-T1WI) on a 3.0 T MRI scanner. Post-image preprocessing, brain functional networks were constructed using the Dosenbach atlas and analyzed with the DPABI-NET toolkit through graph theory.ResultsIn T2DM patients, functional connectivity within and between the default mode network (DMN), frontal parietal network (FPN), subcortical network (SCN), ventral attention network (VAN), somatosensory network (SMN), and visual network (VN) was significantly reduced compared to HCs. Conversely, two functional connections within the VN and between the DMN and SMN were significantly increased. Global network topology analysis showed an increased shortest path length and decreased clustering coefficient, global efficiency, and local efficiency in the T2DM group. MoCA scores were negatively correlated with the shortest path length and positively correlated with global and local efficiency in the T2DM group. Node network topology analysis indicated reduced clustering coefficient, degree centrality, eigenvector centrality, and nodal efficiency in multiple nodes in the T2DM group. MoCA scores positively correlated with clustering coefficient and nodal efficiency in the bilateral precentral gyrus in the T2DM group.DiscussionThis study demonstrated significant abnormalities in connectivity and topology of large-scale brain functional networks in T2DM patients. These findings suggest that brain functional network connectivity and topology could serve as imaging biomarkers, providing insights into the underlying neuropathological processes associated with T2DM-related cognitive impairment.

Large-scale functional network connectivity alterations in adolescents with major depression and non-suicidal self-injury.

Non-suicidal self-injury (NSSI) is prevalent among adolescent populations worldwide, yet its neuropathological mechanisms remain unclear. This study aimed to investigate brain functional differences in NSSI patients by utilizing large-scale functional networks and examining their correlation with clinical outcomes. Cross-sectional clinical and functional magnetic resonance imaging (fMRI) data were collected from 42 patients and 47 healthy controls. Independent component analysis (ICA) was utilized to investigate changes in both intra-network and inter-network functional connectivity. We then investigated the potential association between functional network connectivity and clinical self-injurious behavior. The results revealed significant abnormalities in intra-network functional connectivity within the left middle cingulum gyrus, right angular gyrus, and middle frontal gyrus in patients with NSSI. Additionally, we found altered inter-network connectivity patterns, particularly between higher-order cognitive networks and primary sensory networks, suggesting potential disruptions in multisensory integration and emotional regulation in these patients. This study revealed significant alterations in large-scale functional network connectivity in adolescents with depression and NSSI, particularly in networks related to emotion regulation and cognitive control. These findings provide novel perspectives on the neurobiological mechanisms of NSSI and suggest possible avenues for early intervention and treatment.

Functional connectivity profiles in remitted depression and their relation to ruminative thinking

The triple network model suggests that dysfunction in three major brain networks – the default mode network (DMN), central executive network (CEN), and salience network (SN) – might contribute to cognitive impairments in various psychiatric disorders, including major depressive disorder (MDD). While hyperconnectivity in the DMN, hypoconnectivity in the CEN, and abnormal SN connectivity have been observed in acutely depressed patients, evidence for network alterations during remission is limited. Further, there are few studies examining connectivity in people in remission from MDD (rMDD) during emotional processing tasks, including during affective cognition (i.e., tasks that encompass affective processing in the context of cognitive processes, such as inhibition).To address these literature gaps, this study compared functional connectivity (FC) between resting and task conditions, specifically during the emotional Stroop (eStroop) task, as well as between rMDD and healthy volunteers (HVs), within and between nodes of the three networks. We also explored how FC relates to rumination in the rMDD group, given that rumination tends to persist in rMDD and involves affective and cognitive networks.We unexpectedly found greater FC during the task vs. rest condition within the DMN, and decreased FC during the task vs. rest conditions within the CEN and SN across the groups. Greater FC during the task vs. rest condition between DMN and SN nodes, as well as between CEN and SN nodes were also observed. These effects were more pronounced in the rMDD group as per our exploratory analyses. Additionally, the rMDD vs. HV group showed higher FC between DMN-CEN nodes, regardless of condition. Higher hopeless rumination scores were associated with decreased resting FC within the DMN, while higher active problem-solving scores were associated with increased task FC within the DMN in the rMDD group.These findings suggest that tasks engaging affective cognition processes influence FC within and among the three networks, with this effect more pronounced in the rMDD group. This might indicate potential protective and compensatory mechanisms in rMDD and expands our understanding of large-scale intrinsic network connectivity alterations during remission from depression. However, given the limited sample and the exploratory nature of some of our analyses, replication is necessary.

Aberrant individual large-scale functional network connectivity and topology in chronic insomnia disorder with and without depression

Insomnia is increasingly prevalent with significant associations with depression. Delineating specific neural circuits for chronic insomnia disorder (CID) with and without depressive symptoms is fundamental to develop precision diagnosis and treatment. In this study, we examine static, dynamic and network topology changes of individual large-scale functional network for CID with (CID-D) and without depression to reveal their specific neural underpinnings. Seventeen individual-specific functional brain networks are obtained using a regularized nonnegative matrix factorization technique. Disorders-shared and -specific differences in static and dynamic large-scale functional network connectivities within or between the cognitive control network, dorsal attention network, visual network, limbic network, and default mode network are found for CID and CID-D. Additionally, CID and CID-D groups showed compromised network topological architecture including reduced small-world properties, clustering coefficients and modularity indicating decreased network efficiency and impaired functional segregation. Moreover, the altered neuroimaging indices show significant associations with clinical manifestations and could serve as effective neuromarkers to distinguish among healthy controls, CID and CID-D. Taken together, these findings provide novel insights into the neural basis of CID and CID-D, which may facilitate developing new diagnostic and therapeutic approaches.

Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor.

Introduction: Essential tremor (ET) comprises motor and non-motor-related features, whereas the current neuro-pathogenetic basis is still insufficient to explain the etiologies of ET. Although cerebellum-associated circuits have been discovered, the large-scale cerebral network connectivity in ET remains unclear. This study aimed to characterize the ET in terms of functional connectivity as well as network. We hypothesized that the resting-state network (RSN) within cerebrum could be altered in patients with ET. Methods: Resting-state functional magnetic resonance imaging (fMRI) was used to evaluate the inter- and intra-network connectivity as well as the functional activity in ET and normal control. Correlation analysis was performed to explore the relationship between RSN metrics and tremor features. Results: Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group (p < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs (p < 0.05). The ET group generally has higher degree centrality over normal control. Correlation analysis has revealed that tremor features are associated with inter-network connectivity (|r| = 0.135-0.506), ALFF (|r| = 0.313-0.766), and degree centrality (|r| = 0.523-0.710). Conclusion: Alterations in the cerebral network of ET were detected by using resting-state fMRI, demonstrating a potentially useful approach to explore the cerebral alterations in ET.

Shared and unique alterations of large-scale network connectivity in drug-free adolescent-onset and adult-onset major depressive disorder

Differences in clinical manifestations and biological underpinnings between Major Depressive Disorder (MDD) onset during adolescence and adulthood have been posited in previous studies, implying an influential role of age of onset (AOO) in the clinical subtyping and therapeutic approaches to MDD. However, direct comparisons between the two cohorts and their age-matched controls have been lacking in extant investigations. In this investigation, 156 volunteers participated, comprising 46 adolescents with MDD (adolescent-onset group), 35 adults with MDD (adult-onset group), 19 healthy adolescents, and 56 healthy adults. Resting-state functional MRI scans were undergone by all participants. Large-scale network analyses were applied. Subsequently, a 2 × 2 ANOVA was employed to analyze the main effects of diagnosis, age, and their interaction effect on functional connectivity (FC). Furthermore, regression analysis was employed to scrutinize the association between anomalous FC and HAMD sub-scores. Increased FC in visual network (VN), limbic network (LN), VN-dorsal attention network (DAN), VN-LN, and LN-Default Mode (DMN) was found in both adolescent-onset and adult-onset MDD; however, the increased FC in DAN and LN were only found in adult-onset MDD and the decreased FC in DAN was only found in adolescent-onset MDD. Additionally, the relationship between HAMD factor 1 anxiety somatization and altered FC of DAN, VN, and VN-DAN was moderated by AOO. In conclusion, shared and distinctive large-scale network alterations in adolescent-onset and adult-onset MDD patients were suggested by our findings, providing valuable contributions towards refining clinical subtyping and treatment approaches for MDD.

Reversibility of Cognitive Deficits and Functional Connectivity With Transfusion in Children With Sickle Cell Disease.

People with sickle cell disease (SCD) are at risk of cognitive dysfunction independent of stroke. Diminished functional connectivity in select large-scale networks and white matter integrity reflect the neurologic consequences of SCD. Because chronic transfusion therapy is neuroprotective in preventing stroke and strengthening executive function abilities in people with SCD, we hypothesized that red blood cell (RBC) transfusion facilitates the acute reversal of disruptions in functional connectivity while white matter integrity remains unaffected. Children with SCD receiving chronic transfusion therapy underwent a brain MRI measuring white matter integrity with diffusion tensor imaging and resting-state functional connectivity within 3 days before and after transfusion of RBCs. Cognitive assessments with the NIH Toolbox were acquired after transfusion and then immediately before the following transfusion cycle. Sixteen children with a median age of 12.5 years were included. Global assessments of functional connectivity using homotopy (p = 0.234) or modularity (p = 0.796) did not differ with transfusion. Functional connectivity within the frontoparietal network significantly strengthened after transfusion (median intranetwork Z-score 0.21 [0.17-0.30] before transfusion, 0.29 [0.20-0.36] after transfusion, p < 0.001), while there was not a significant change seen within the sensory motor, visual, auditory, default mode, dorsal attention, or cingulo-opercular networks. Corresponding to the change within the frontoparietal network, there was a significant improvement in executive function abilities after transfusion (median executive function composite score 87.7 [81.3-90.7] before transfusion, 90.3 [84.3-93.7] after transfusion, p = 0.021). Participants with stronger connectivity in the frontoparietal network before transfusion had a significantly greater improvement in the executive function composite score with transfusion (r = 0.565, 95% CI 0.020-0.851, p = 0.044). While functional connectivity and executive abilities strengthened with transfusion, there was not a significant change in white matter integrity as assessed by fractional anisotropy and mean diffusivity within 16 white matter tracts or globally with tract-based spatial statistics. Strengthening of functional connectivity with concomitant improvement in executive function abilities with transfusion suggests that functional connectivity MRI could be used as a biomarker for acutely reversible neurocognitive injury as novel therapeutics are developed for people with SCD.

Resting-state functional connectivity and structural differences between smokers and healthy non-smokers

Previous studies have shown an association between cigarette use and altered resting-state functional connectivity (rsFC) in many large-scale networks, sometimes complemented by measures of cortical atrophy. In this study, we aimed to further explore the neural differences between smokers and healthy non-smokers through the integration of functional and structural analyses. Imaging data of fifty-two smokers and forty-five non-smokers were analyzed through an independent component analysis for group differences in rsFC. Smokers showed lower rsFC within the dorsal attention network (DAN) in the left superior and middle frontal gyrus and left superior division of the lateral occipital cortex compared to non-smokers; moreover, cigarette use was found to be associated with reduced grey matter volume in the left superior and middle frontal gyrus and right orbitofrontal cortex, partly overlapping with functional findings. Within smokers, daily cigarette consumption was positively associated with increased rsFC within the cerebellar network and the default mode network and decreased rsFC within the visual network and the salience network, while carbon monoxide level showed a positive association with increased rsFC within the sensorimotor network. Our results suggest that smoking negatively impacts rsFC within the DAN and that changes within this network might serve as a circuit-based biomarker for structural deficits.

Salience Network Functional Connectivity Mediates Association Between Social Engagement and Cognition in Non-Demented Older Adults: Exploratory Investigation.

Social engagement has beneficial effects during cognitive aging. Large-scale cognitive brain network functions are implicated in both social behaviors and cognition. We evaluated associations between functional connectivity (FC) of large-scale brain cognitive networks and social engagement, characterized by self-reported social network size and contact frequency. We subsequently tested large-scale brain network FC as a potential mediator of the beneficial relationship between social engagement and cognitive performance. 112 older adults (70.7±7.3 years, range 54.6-89.7; 84 women) completed the Lubben Social Network Scale 6 (LSNS-6), National Alzheimer's Coordinating Center (NACC) Uniform Data Set 3 (UDS-3) cognitive battery, and resting state fMRI. We completed seed-based correlational analysis in the default mode and salience networks. Significant associations between social engagement scores and cognitive performance, as well as between social engagement and FC of brain networks, informed the construction of mediation models. Social engagement was significantly associated with executive function and global cognition, with greater social engagement associated with better cognitive performance. Social engagement was significantly associated with salience network FC, with greater social engagement associated with higher connectivity. Salience network FC partially mediated associations between social engagement and both executive function and global cognition. Our results suggest that the salience network is a key mediator of the beneficial relationship between social engagement and cognition in older adults.

Personalized functional network mapping for autism spectrum disorder and attention-deficit/hyperactivity disorder

Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are two typical neurodevelopmental disorders that have a long-term impact on physical and mental health. ASD is usually comorbid with ADHD and thus shares highly overlapping clinical symptoms. Delineating the shared and distinct neurophysiological profiles is important to uncover the neurobiological mechanisms to guide better therapy. In this study, we aimed to establish the behaviors, functional connectome, and network properties differences between ASD, ADHD-Combined, and ADHD-Inattentive using resting-state functional magnetic resonance imaging. We used the non-negative matrix fraction method to define personalized large-scale functional networks for each participant. The individual large-scale functional network connectivity (FNC) and graph-theory-based complex network analyses were executed and identified shared and disorder-specific differences in FNCs and network attributes. In addition, edge-wise functional connectivity analysis revealed abnormal edge co-fluctuation amplitude and number of transitions among different groups. Taken together, our study revealed disorder-specific and -shared regional and edge-wise functional connectivity and network differences for ASD and ADHD using an individual-level functional network mapping approach, which provides new evidence for the brain functional abnormalities in ASD and ADHD and facilitates understanding the neurobiological basis for both disorders.

Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease.

Neuromelanin hypopigmentation within substantia nigra pars compacta (SNc) reflects the loss of pigmented neurons, which in turn contributes to the dysfunction of the nigrostriatal and striato-cortical pathways in Parkinson's disease (PD). Our study aims to investigate the relationships between SN degeneration manifested by neuromelanin reduction, functional connectivity (FC) among large-scale brain networks, and motor impairment in PD. This study included 68 idiopathic PD patients and 32 age-, sex- and education level-matched healthy controls who underwent neuromelanin-sensitive magnetic resonance imaging (MRI), functional MRI, and motor assessments. SN integrity was measured using the subregional contrast-to-noise ratio calculated from neuromelanin-sensitive MRI. Resting-state FC maps were obtained based on the independent component analysis. Subsequently, we performed partial correlation and mediation analyses in SN degeneration, network disruption, and motor impairment for PD patients. We found significantly decreased neuromelanin within SN and widely altered inter-network FCs, mainly involved in the basal ganglia (BG), sensorimotor and frontoparietal networks in PD. In addition, decreased neuromelanin content was negatively correlated with the dorsal sensorimotor network (dSMN)-medial visual network connection (P = 0.012) and dSMN-BG connection (P = 0.004). Importantly, the effect of SN neuromelanin hypopigmentation on motor symptom severity in PD is partially mediated by the increased connectivity strength between BG and dSMN (indirect effect = - 1.358, 95% CI: - 2.997, - 0.147). Our results advanced our understanding of the interactions between neuromelanin hypopigmentation in SN and altered FCs of functional networks in PD and suggested the potential of multimodal metrics for early diagnosis and monitoring the response to therapies.

Resting state functional magnetic resonance imaging: an analysis of the connectivity of brain large-scale networks

Objective: To assess the possibilities of various methods for analyzing the functional integration of large-scale brain neural networks in healthy subjects according to functional MRI resting state.Material and methods. Functional MRI at rest was performed on 28 healthy male subjects aged 27.4 ± 5.1 years, without bad habits and craniocerebral injuries. A functional evaluation of large-scale neural networks included in the triple network model was carried out: default mode network, salience network, executive control network.Results. The analysis of independent components made it possible to fully identify the default mode network and the salience network, however, the executive control network were partially identified, and this mainly concerned structures with a bilateral location. Graph analysis has identified structures of greatest value for neurofunctional research. Almost all structures that have the highest graph indicators are related to the executive control network. The results of the Roi-analysis showed the interaction between all large-scale networks, which indicates their joint work in providing important brain functions. It was also determined that in healthy people, all structures within large-scale networks are functionally interconnected.Conclusion. Different methods of resting functional MRI data analysis reveal different aspects of connectivity in the brain, completely different principles are involved in the processing of each method, and the final quantification parameters also vary depending on the preferred method. Currently, there is no single method that in itself would be considered the standard of analysis. Applying multiple methods to the same dataset can produce more informative results.

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium.

Previous studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD). This study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups. Our findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group. These findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

5 Large-Scale Network Connectivity and Cognitive Function after Exercise Training in Older Adults

Objective:Despite growing evidence regarding the association between exercise training (ET) and functional brain connectivity, little is known about the effects of ET on within- and between-network functional connectivity (FC) of core brain networks. We investigated the effects of ET on within- and between-network functional connectivity of the default mode network (DMN), frontoparietal network (FPN), and salience network (SAL) in older adults with intact cognition (CN) and older adults diagnosed with mild cognitive impairment (MCI). We further examined whether the ET-induced changes in FC were associated with changes in cognitive performance.Participants and Methods:33 older adults (78.0±7.0 years; 16 MCI and 17 CN) participated in the present study. Before and after a 12-week walking ET intervention, participants underwent cardiorespiratory fitness tests, the Controlled Oral Word Association Test (COWAT), the Rey Auditory Verbal Learning test (RAVLT), a narrative memory test (logical memory; LM), and a resting-state fMRI scan. We examined the within- and between-network connectivity of the DMN, FPN, and SAL before and after ET. We also used linear regression to examine associations between ET-related changes in the within- and between-network connectivity and cognitive function.Results:There were significant improvements in VO2peak, COWAT, RAVLT, and LM after ET across participants. Significant increases in within-network connectivity of the DMN and SAL were observed in response to ET across participants. FC between the DMN-FPN, DMN-SAL, and FPN-SAL were also increased after ET. Moreover, greater SAL within connectivity and FPN-SAL between connectivity were associated with enhanced LM immediate recall performance after ET. There were no significant interactions between Time (before vs after ET) and Group (CN vs MCI) for network connectivity or cognitive function.Conclusions:Our findings suggest that increased within- and between-network connectivity following 12-weeks of walking exercise may subserve improvements in memory performance in older individuals with intact cognition and in those diagnosed with MCI.

Large-scale functional network connectivity mediates the associations between lipids metabolism and cognition in type 2 diabetes

Type 2 diabetes (T2D) is associated with dyslipidemia and mild cognitive impairment. This study investigated the relationships between serum lipids metabolism, cognition, and functional connectivity (FC) within and between brain networks in T2D patients. The study included 102 T2D patients and 45 healthy controls who underwent functional magnetic resonance imaging, lipid profile tests, and cognitive assessments. Thirteen functional networks were identified using independent component analysis. The statistical analyses included multivariate analysis of covariance, partial correlation, canonical correlation, and mediation analyses. We found widely reduced between-network FCs in T2D, especially between the ventral sensorimotor network (SMN) and dorsal attention network (DAN) (p = 0.001) and between the ventral SMN and lateral visual network (VN) (p < 0.001). Moreover, lower between-network FCs were correlated with worse serum lipids metabolism and poorer cognitive performance (all p < 0.05). Importantly, between-network FCs mediated the relationship between lipid metabolism and cognition (β = −0.3136, 95% CI: −0.7660, −0.0186). Within-network analyses revealed altered FCs within the anterior default mode network, DAN, and lateral VN, each positively correlated with global cognition (all p < 0.01). Our results suggest the potential of improving cognitive function by regulating serum lipids in individuals with T2D.

Intelligent Edge Caching and Computing for Scalable Information Systems

INTRODUCTION: In scalable information systems, edge computing can help to overcome the challenges of latency, bandwidth, and connectivity in large-scale networks by reducing the amount of data that needs to be transmitted over the network.OBJECTIVES: The edge devices, such as sensors, cameras, gateways, routers, switches, multiplexers, integrated access devices, etc., can perform initial data processing and filtering, reducing the data volume sent to the central system. METHODS: This special issue aims to provide the recent progress of intelligent edge caching and computing for scalable information systems.RESULTS: The guest editors received more than 30 submissions, and finally, ten papers were accepted.CONCLUSION: This special issue has contributed to advancing academic research and practice in intelligent edge caching and computing for scalable information systems.

Abnormal resting-state effective connectivity in large-scale networks among obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a chronic mental illness characterized by abnormal functional connectivity among distributed brain regions. Previous studies have primarily focused on undirected functional connectivity and rarely reported from network perspective. To better understand between or within-network connectivities of OCD, effective connectivity (EC) of a large-scale network is assessed by spectral dynamic causal modeling with eight key regions of interests from default mode (DMN), salience (SN), frontoparietal (FPN) and cerebellum networks, based on large sample size including 100 OCD patients and 120 healthy controls (HCs). Parametric empirical Bayes (PEB) framework was used to identify the difference between the two groups. We further analyzed the relationship between connections and Yale-Brown Obsessive Compulsive Scale (Y-BOCS). OCD and HCs shared some similarities of inter- and intra-network patterns in the resting state. Relative to HCs, patients showed increased ECs from left anterior insula (LAI) to medial prefrontal cortex, right anterior insula (RAI) to left dorsolateral prefrontal cortex (L-DLPFC), right dorsolateral prefrontal cortex (R-DLPFC) to cerebellum anterior lobe (CA), CA to posterior cingulate cortex (PCC) and to anterior cingulate cortex (ACC). Moreover, weaker from LAI to L-DLPFC, RAI to ACC, and the self-connection of R-DLPFC. Connections from ACC to CA and from L-DLPFC to PCC were positively correlated with compulsion and obsession scores (r = 0.209, p = 0.037; r = 0.199, p = 0.047, uncorrected). Our study revealed dysregulation among DMN, SN, FPN, and cerebellum in OCD, emphasizing the role of these four networks in achieving top-down control for goal-directed behavior. There existed a top-down disruption among these networks, constituting the pathophysiological and clinical basis.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia.

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition. A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores. Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC). Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.

Altered dynamic functional network connectivity states in patients with acute basal ganglia ischemic stroke

BackgroundDynamic functional network connectivity (dFNC) patterns are successfully able to capture the time-varying features of intrinsic fluctuations throughout a scan. We explored dFNC alterations across the entire brain in patients with acute ischemic stroke (AIS) of the basal ganglia (BG). MethodResting-state functional magnetic resonance imaging data were acquired from 26 patients with first-ever AIS in the BG and 26 healthy controls (HCs). Independent component analysis, the sliding window method, and the K-means clustering method were used to obtain reoccurring dynamic network connectivity patterns. Moreover, temporal features across diverse dFNC states were compared between the two groups, and the local and global efficiencies across states were analyzed to explore the characteristics of the topological networks among states. ResultsFour dFNC states were characterized for comparison of dynamic brain network connectivity patterns. In contrast to the HC group, the AIS group spent a significantly higher fraction of time in State 1, which is characterized by a relatively weaker brain network connectome. Conversely, compared with HC, patients with AIS showed a lower mean dwell time in State 2, which was characterized by a relatively stronger brain network connectome. Additionally, functional networks exhibited variable efficiency of information transfer across 4 states. ConclusionsAIS not only altered the interaction between the different dynamic networks but also promoted characteristic alterations in the temporal and topological features of large-scale dynamic network connectivity.

Large-Scale Network Connectivity and Cognitive Function Changes After Exercise Training in Older Adults with Intact Cognition and Mild Cognitive Impairment.

Despite growing evidence regarding the association between exercise training (ET) and functional brain network connectivity, little is known about the effects of ET on large-scale within- and between-network functional connectivity (FC) of core brain networks. We investigated the effects of ET on within- and between-network functional connectivity of the default mode network (DMN), frontoparietal network (FPN), and salience network (SAL) in older adults with intact cognition (CN) and older adults diagnosed with mild cognitive impairment (MCI). The association between ET-induced changes in FC and cognitive performance was examined. 33 older adults (78.0±7.0 years; 16 MCI and 17 CN) participated in this study. Before and after a 12-week walking ET intervention, participants underwent a graded exercise test, Controlled Oral Word Association Test (COWAT), Rey Auditory Verbal Learning Test (RAVLT), a narrative memory test (logical memory; LM), and a resting-state fMRI scan. We examined the within (W) and between (B) network connectivity of the DMN, FPN, and SAL. We used linear regression to examine associations between ET-related changes in network connectivity and cognitive function. There were significant improvements in cardiorespiratory fitness, COWAT, RAVLT, and LM after ET across participants. Significant increases in DMNW and SALW, and DMN-FPNB, DMN-SALB, and FPN-SALB were observed after ET. Greater SALW and FPN-SALB were associated with enhanced LM immediate recall performance after ET in both groups. Increased within- and between-network connectivity following ET may subserve improvements in memory performance in older individuals with intact cognition and with MCI due to Alzheimer's disease.