Differences In Connectivity Patterns Research Articles

Comparative Functional Connectivity of Core Brain Regions between Implicit and Explicit Memory Tasks Underlying Negative Emotion in General Anxiety Disorder.

ObjectiveTo investigate not only differential patterns of functional connectivity of core brain regions between implicit and explicit verbal memory tasks underlying negatively evoked emotional condition, but also correlations of functional connectivity (FC) strength with clinical symptom severity in patients with generalized anxiety disorder (GAD).MethodsThirteen patients with GAD and 13 healthy controls underwent functional magnetic resonance imaging for memory tasks with negative emotion words.ResultsClinical symptom and its severities of GAD were potentially associated with abnormalities of task-based FC with core brain regions and distinct FC patterns between implicit vs. explicit memory processing in GAD were potentially well discriminated. Outstanding FC in implicit memory task includes positive connections of precentral gyus (PrG) to inferior frontal gyrus and inferior parietal gyrus (IPG), respectively, in encoding period; a positive connection of amygdala (Amg) to globus pallidus as well as a negative connection of Amg to cerebellum in retrieval period. Meanwhile, distinct FC in explicit memory included a positive connection of PrG to inferior temporal gyrus (ITG) in encoding period; a positive connection of the anterior cingulate gyrus to superior frontal gyrus in retrieval period. Especially, there were positive correlation between GAD-7 scores and FC of PrG-IPG (r2 = 0.324, p = 0.042) in implicit memory encoding, and FC of PrG-ITG (r2 = 0.378, p = 0.025) in explicit memory encoding.ConclusionThis study clarified differential patterns of brain activation and relevant FC between implicit and explicit verbal memory tasks underlying negative emotional feelings in GAD. These findings will be helpful for an understanding of distinct brain functional mechanisms associated with clinical symptom severities in GAD.

Differential alterations in brain structural network organization during addiction between adolescents and adults.

The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

Adolescents with a concussion have altered brain network functional connectivity one month following injury when compared to adolescents with orthopedic injuries

Concussion is a mild traumatic brain injury (mTBI) with increasing prevalence among children and adolescents. Functional connectivity (FC) within and between the default mode network (DMN), central executive network (CEN) and salience network (SN) has been shown to be altered post-concussion. Few studies have investigated connectivity within and between these 3 networks following a pediatric concussion. The present study explored whether within and between-network FC differs between a pediatric concussion and orthopedic injury (OI) group aged 10–18. Participants underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan at 4 weeks post-injury. One-way ANCOVA analyses were conducted between groups with the seed-based FC of the 3 networks. A total of 55 concussion and 27 OI participants were included in the analyses. Increased within-network FC of the CEN and decreased between-network FC of the DMN-CEN was found in the concussion group when compared to the OI group. Secondary analyses using spherical SN regions of interest revealed increased within-network FC of the SN and increased between-network FC of the DMN-SN and CEN-SN in the concussion group when compared to the OI group. This study identified differential connectivity patterns following a pediatric concussion as compared to an OI 4 weeks post-injury. These differences indicate potential adaptive brain mechanisms that may provide insight into recovery trajectories and appropriate timing of treatment within the first month following a concussion.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic.

BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.MethodsRNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19’s main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Differential patterns of connectivity in Western Pacific hydrothermal vent metapopulations: A comparison of biophysical and genetic models.

Hydrothermal ecosystems face threats from planned deep-seabed mining activities, despite the fact that patterns of realized connectivity among vent-associated populations and communities are still poorly understood. Since populations of vent endemic species depend on larval dispersal to maintain connectivity and resilience to habitat changes, effective conservation strategies for hydrothermal ecosystems should include assessments of metapopulation dynamics. In this study, we combined population genetic methods with biophysical models to assess strength and direction of gene flow within four species of the genus Alviniconcha (A.boucheti, A.kojimai, A.strummeri and A.hessleri) that are ecologically dominant taxa at Western Pacific hydrothermal vents. In contrast to predictions from dispersal models, among-basin migration in A.boucheti occurred predominantly in an eastward direction, while populations within the North Fiji Basin were clearly structured despite the absence of oceanographic barriers. Dispersal models and genetic data were largely in agreement for the other Alviniconcha species, suggesting limited between-basin migration for A.kojimai, lack of genetic structure in A.strummeri within the Lau Basin and restricted gene flow between northern and southern A.hessleri populations in the Mariana back-arc as a result of oceanic current conditions. Our findings show that gene flow patterns in ecologically similar congeneric species can be remarkably different and surprisingly limited depending on environmental and evolutionary contexts. These results are relevant to regional conservation planning and to considerations of similar integrated analyses for any vent metapopulations under threat from seabed mining.

Electrophysiological differences between older women and men in the absence of disease: A step closer to personalized medicine

AbstractBackgroundMultiple electrophysiological footprints have been identified to be associated with silent and clinical neuropathological processes predicting mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Nevertheless, it is important to bear in mind that women show greater risk of developing both MCI and AD. Therefore, it is crucial to understand in first place how sex differences might modulate these electrophysiological mechanisms in healthy older adults.Method240 healthy cognitively normal older adults (age = 60 ‐ 85) participated in this study. They were divided into two groups: women (n = 140) and men (n = 120), matched in age and educational level. Each individual underwent four minutes of closed eyes resting state MEG recording. The aim was to detect any clusters where power was significantly associated with sex and also any networks where functional connectivity was associated with sex (total intracranial volume and age where used as covariates p‐value < 0.01) in either frequency band (gamma, beta, alpha, theta and delta).ResultWomen showed greater power in the beta band in a posterior cluster composed of occipital and temporal brain regions. Additionally women also showed greater functional connectivity across all frequency bands, always in frontal brain networks.ConclusionEven in the absence of an undergoing neuropathological process, men and women present differential patterns of brain connectivity and power. The role that these differences play in the pathogenesis of Alzheimer’s disease remains to be fully understood. However, these differential baseline characteristics should be accounted for in studies aiming to establish electrophysiological markers of AD.

Increased amygdala and decreased frontolimbic r esting- s tate functional connectivity in children with aggressive behavior.

Childhood maladaptive aggression is associated with disrupted functional connectivity within amygdala-prefrontal circuitry. In this study, neural correlates of childhood aggression were probed using the intrinsic connectivity distribution, a voxel-wise metric of global resting-state brain connectivity. This sample included 38 children with aggressive behavior (26 boys, 12 girls) ages 8–16 years and 21 healthy controls (14 boys, 6 girls) matched for age and IQ. Functional MRI data were acquired during resting state, and differential patterns of intrinsic functional connectivity were tested in a priori regions of interest implicated in the pathophysiology of aggressive behavior. Next, correlational analyses tested for associations between functional connectivity and severity of aggression measured by the Reactive-Proactive Aggression Questionnaire in children with aggression. Children with aggressive behavior showed increased global connectivity in the bilateral amygdala relative to controls. Greater severity of aggressive behavior was associated with decreasing global connectivity in the dorsal anterior cingulate and ventromedial prefrontal cortex. Follow-up seed analysis revealed that aggression was also positively correlated with left amygdala connectivity with the dorsal anterior cingulate, ventromedial and dorsolateral prefrontal cortical regions. These results highlight the potential role of connectivity of the amygdala and medial prefrontal and anterior cingulate cortices in modulating the severity of aggressive behavior in treatment-seeking children.

Discriminating mild traumatic brain injury using sparse dictionary learning of functional network dynamics.

Mild traumatic brain injury (mTBI) is usually caused by a bump, blow, or jolt to the head or penetrating head injury, and carries the risk of inducing cognitive disorders. However, identifying the biomarkers for the diagnosis of mTBI is challenging as evident abnormalities in brain anatomy are rarely found in patients with mTBI. In this study, we tested whether the alteration of functional network dynamics could be used as potential biomarkers to better diagnose mTBI. We propose a sparse dictionary learning framework to delineate spontaneous fluctuation of functional connectivity into the subject‐specific time‐varying evolution of a set of overlapping group‐level sparse connectivity components (SCCs) based on the resting‐state functional magnetic resonance imaging (fMRI) data from 31 mTBI patients in the early acute phase (<3 days postinjury) and 31 healthy controls (HCs). The identified SCCs were consistently distributed in the cohort of subjects without significant inter‐group differences in connectivity patterns. Nevertheless, subject‐specific temporal expression of these SCCs could be used to discriminate patients with mTBI from HCs with a classification accuracy of 74.2% (specificity 64.5% and sensitivity 83.9%) using leave‐one‐out cross‐validation. Taken together, our findings indicate neuroimaging biomarkers for mTBI individual diagnosis based on the temporal expression of SCCs underlying time‐resolved functional connectivity.

Neural Changes in Reward Processing Following Approach Avoidance Training for Depression.

Altered approach motivation is hypothesized to be critical for the maintenance of depression. Computer-administered approach-avoidance training programs to increase approach action tendencies toward positive stimuli produce beneficial outcomes. However, there have been few studies examining neural changes following approach-avoidance training. Participants with Major Depressive Disorder were randomized to an Approach Avoidance Training (AAT) manipulation intended to increase approach tendencies for positive social cues (n=13) or a control procedure (n=15). We examined changes in neural activation (primary outcome) and connectivity patterns using Group Iterative Multiple Model Estimation during a social reward anticipation task (exploratory). A laboratory-based social affiliation task was also administered following the manipulation to measure affect during anticipation of real-world social activity. Individuals in the AAT group demonstrated increased activation in reward processing regions during social reward anticipation relative to the control group from pre to post-training. Following training, connectivity patterns across reward regions were observed in the full sample and connectivity between the medial PFC and caudate was associated with anticipatory positive affect before the social interaction; preliminary evidence of differential connectivity patterns between the two groups also emerged. Results support models whereby modifying approach-oriented behavioral tendencies with computerized training leads to alterations in reward circuitry. (NCT02330744).

A-31 Distinguishing Neuro-Markers of Math Learning Disability Using EEG Coherence

Abstract Objective The current study evaluated brain connectivity in math learning disability (MLD) by examining intra- and interhemispheric electroencephalography (EEG) coherence in three groups of children with differing math profiles. Differential patterns of connectivity were evaluated during “at-rest” conditions and statistically evaluated across three groups. Method Testing occurred in a university laboratory setting. Participants were recruited through media and local agencies serving children with disabilities. The Woodcock Johnson cognitive and achievement tests were used to determine general intelligence and skills across all math achievement subtests. Additionally, 3-minute eye-closed EEG resting data was collected. Groups used in the current study were: neurotypical controls (NC) (n = 30), math learning disability (MLD) (n = 15), and lower achievement (LA) (n = 15). Participants’ mean age was 9.58 (SD = 1.38) with 53.3% being male. Results Intrahemispheric comparisons suggest MLD children demonstrated reduced left hemispheric coherence to NC’s (p = 0.006), not seen in LA children. Additionally, NC’s had greater beta coherence (p = 0.002). Interhemispheric analyses revealed the MLD group had reduced alpha occipital coherence compared to the LA group (p = 0.031). Conclusion The current study provides supporting evidence for implicating brain connectivity as an underlying cause of MLD. Specifically, left hemispheric differences in delta coherence were found in children with MLD not observed in children with LA profiles. Weaknesses in areas of visuo-spatial integration in the MLD group were also observed. Results suggest atypical patterns of brain connectivity in the default-mode network (DMN) in delta wavelengths may serve as a useful biomarker of MLD.

Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion

Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.

Mapping grip force to motor networks

AimThere is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force. MethodsUsing magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content. ResultsThe SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections. ConclusionWe interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.

Conceptual Analysis: A Social Neuroscience Approach to Interpersonal Interaction in the Context of Disruption and Disorganization of Attachment (NAMDA).

Humans are strongly dependent upon social resources for allostasis and emotion regulation. This applies especially to early childhood because humans—as an altricial species—have a prolonged period of dependency on support and input from caregivers who typically act as sources of co-regulation. Accordingly, attachment theory proposes that the history and quality of early interactions with primary caregivers shape children's internal working models of attachment. In turn, these attachment models guide behavior, initially with the set goal of maintaining proximity to caregivers but eventually paving the way to more generalized mental representations of self and others. Mounting evidence in non-clinical populations suggests that these mental representations coincide with differential patterns of neural structure, function, and connectivity in a range of brain regions previously associated with emotional and cognitive capacities. What is currently lacking, however, is an evidence-based account of how early adverse attachment-related experiences and/or the emergence of attachment disorganization impact the developing brain. While work on early childhood adversities offers important insights, we propose that how these events become biologically embedded crucially hinges on the context of the child–caregiver attachment relationships in which the events take place. Our selective review distinguishes between direct social neuroscience research on disorganized attachment and indirect maltreatment-related research, converging on aberrant functioning in neurobiological systems subserving aversion, approach, emotion regulation, and mental state processing in the wake of severe attachment disruption. To account for heterogeneity of findings, we propose two distinct neurobiological phenotypes characterized by hyper- and hypo-arousal primarily deriving from the caregiver serving either as a threatening or as an insufficient source of co-regulation, respectively.

Creative Connections: Computational Semantic Distance Captures Individual Creativity and Resting-State Functional Connectivity.

Recent studies of creative cognition have revealed interactions between functional brain networks involved in the generation of novel ideas; however, the neural basis of creativity is highly complex and presents a great challenge in the field of cognitive neuroscience, partly because of ambiguity around how to assess creativity. We applied a novel computational method of verbal creativity assessment-semantic distance-and performed weighted degree functional connectivity analyses to explore how individual differences in assembly of resting-state networks are associated with this objective creativity assessment. To measure creative performance, a sample of healthy adults (n = 175) completed a battery of divergent thinking (DT) tasks, in which they were asked to think of unusual uses for everyday objects. Computational semantic models were applied to calculate the semantic distance between objects and responses to obtain an objective measure of DT performance. All participants underwent resting-state imaging, from which we computed voxel-wise connectivity matrices between all gray matter voxels. A linear regression analysis was applied between DT and weighted degree of the connectivity matrices. Our analysis revealed a significant connectivity decrease in the visual-temporal and parietal regions, in relation to increased levels of DT. Link-level analyses showed higher local connectivity within visual regions was associated with lower DT, whereas projections from the precuneus to the right inferior occipital and temporal cortex were positively associated with DT. Our results demonstrate differential patterns of resting-state connectivity associated with individual creative thinking ability, extending past work using a new application to automatically assess creativity via semantic distance.

Differential spatial patterns of structural connectivity of amygdala nuclei with orbitofrontal cortex.

The orbitofrontal cortex (OFC)‐amygdala circuit is critical to goal‐directed behavior, learning, and valuation. However, our understanding of the OFC‐amygdala connections that support these emergent processes is hampered by our reliance on the primate literature and insufficient knowledge regarding the connectivity patterns between regions of OFC and amygdala nuclei, each of which is differentially involved in these processes in humans. Thus, we examined structural connectivity between different OFC regions and four amygdala nuclei in healthy adults (n = 1,053) using diffusion‐based anatomical networks and probabilistic tractography in four conceptually distinct ways. First, we identified the OFC regions that connect with each nucleus. Second, we identified the OFC regions that were more likely to connect with a given nucleus than the others. Finally, we developed probabilistic and rank‐order maps of OFC (one for each nucleus) based upon the likelihood of each OFC voxel exhibiting preferential connectivity with each nucleus and the relative density of connectivity between each OFC voxel and each nucleus, respectively. The first analyses revealed that the connections of each nucleus spanned all of OFC, reflecting widespread overall amygdala linkage with OFC. Analysis of preferential connectivity and probabilistic and rank‐order maps of OFC converged to reveal differential patterns of connectivity between OFC and each nucleus. Present findings illustrate the importance of accounting for spatial specificity when examining links between OFC and amygdala. This fine‐grained examination of OFC‐amygdala connectivity can be applied to understand how such connectivity patterns support a range of emergent functions including affective and motivational processes.

Functional connectivity with the anterior and posterior hippocampus during spatial memory

Evidence of differential connectivity and activity patterns across the long-axis of the hippocampus has led to many hypotheses about functional specialization of the anterior and posterior hippocampus, including a hypothesis linking the anterior hippocampus to memory encoding and the posterior hippocampus to memory retrieval. The hippocampal encoding/retrieval and network (HERNET) model of memory predicts that encoding should engage the anterior hippocampus and the attention network, whereas retrieval should engage the posterior hippocampus and the default network. In a previous fMRI study that employed multivoxel pattern analysis, we found that the patterns of activity in the anterior hippocampus predicted the quadrant of spatial memory encoding. In the current fMRI study, we investigated whether the spatial memory encoding activity in the anterior hippocampus and retrieval activity in the posterior hippocampus had a higher degree of connectivity to the attention network or the default network. During the study phase, abstract shapes were presented in each quadrant of the visual field and participants were instructed to remember each shape's location while maintaining central fixation. During the test phase, the same shapes were presented in the center of the screen and participants identified the previous location of each shape. Generalized psychophysiological interaction analyses were conducted between the anatomically defined anterior and posterior hippocampus and the rest of the brain. This revealed preferential connectivity between the anterior hippocampus and regions of the attention network during encoding and between the posterior hippocampus and regions of the default network during retrieval. In addition, there were location-specific patterns of connectivity with the anterior hippocampus and posterior hippocampus during encoding and retrieval of right visual field items. These results suggest that the anterior and posterior hippocampus interact with regions of the attention network and default network during spatial memory encoding and retrieval, respectively, and support the HERNET model of memory.

The intrinsic neonatal hippocampal network: rsfMRI findings.

Many adults cannot voluntarily recall memories before the ages of 3-5, a phenomenon referred to as "infantile amnesia." The development of the hippocampal network likely plays a significant part in the emergence of the ability to form long-lasting memories. In adults, the hippocampus has specialized and privileged connections with certain cortical networks, which presumably facilitate its involvement in memory encoding, consolidation, and retrieval. Is the hippocampus already specialized in these cortical connections at birth? And are the topographical principles of connectivity (e.g., long-axis specialization) present at birth? We analyzed resting-state hippocampal connectivity in neonates scanned within 1 wk of birth (Developmental Human Connectome Project) and compared it with that of adults (Human Connectome Project). We explored the connections of the whole hippocampus and its long-axis specialization to seven canonical cortical networks. We found that the neonatal hippocampal networks show clear immaturity at birth: adults showed hippocampal connectivity that was unique for each cortical network, whereas neonates showed no differentiation in hippocampal connectivity across these networks. Furthermore, neonates lacked long-axis specialization (i.e., along the anterior-posterior axis) of the hippocampus in its differential connectivity patterns to the cortical networks. This immaturity in connectivity may contribute to immaturity in memory formation in the first years of life.NEW & NOTEWORTHY Although both animal data and human data suggest that the hippocampus is immature at birth, to date, there are no direct assessments of human hippocampal functional connectivity (FC) very early in life. Our study explores the FC of the hippocampus to the cortex at birth, allowing insight into the development of human memory systems. In particular, we find that adults and neonates exhibit vastly different hippocampal connectivity profiles-a finding that likely has large developmental implications.

Disrupted rich-club network organization and individualized identification of patients with major depressive disorder

BackgroundAltered structural and functional brain networks have been extensively studied in major depressive disorder (MDD) patients. However, whether the differential connectivity patterns in the rich-club organization, assessed from structural brain network analyses, and the associated connections of these regions are particularly susceptible to depression remain unclear. MethodsWe acquired resting-state functional magnetic resonance imaging (R-fMRI) and diffusion tensor imaging (DTI) from 31 unmedicated MDD patients and 32 cognitively normal (CN) subjects and completed a series of neuropsychological tests. Rich-club organization, network properties, and coupling between structural and functional connectivity (SC-FC) were explored. Furthermore, whether these indices could potentially deliver effective clinical predictive value for MDD patients were examined. ResultsThe MDD patients showed disrupted structural rich-club organization and modularity, as well as a distinct correlation pattern between global efficiency and rich-club organization. Importantly, reduced SC-FC coupling, reflecting a decreased agreement in the integrity of the networks, was significantly associated with the strength of structural rich-club connections in the MDD patients. Furthermore, the disrupted structural rich-club organization, which was primarily located in the default mode network (DMN) and executive control network (ECN), emerged as a valuable indicator to distinguish between MDD and CN. ConclusionsFindings of this study identified that the disrupted rich-club structural organization significantly influenced brain structural network modularity and integrity and could serve as a promising biological marker for the identification of MDD patients.

Structural connectome and connectivity lateralization of the multimodal vestibular cortical network

Unlike other sensory systems, the structural connectivity patterns of the human vestibular cortex remain a matter of debate. Based on their functional properties and hypothesized centrality within the vestibular network, the ‘core’ cortical regions of this network are thought to be areas in the posterior peri-sylvian cortex, in particular the retro-insula (previously named the posterior insular cortex-PIC), and the subregion OP2 of the parietal operculum.To study the vestibular network, structural connectivity matrices from n=974 healthy individuals drawn from the public Human Connectome Project (HCP) repository were estimated using multi-shell diffusion-weighted data followed by probabilistic tractography and spherical-deconvolution informed filtering of tractograms in combination with subject-specific grey-matter parcellations. Weighted graph-theoretical measures, modularity, and ‘hubness’ of the multimodal vestibular network were then estimated, and a structural lateralization index was defined in order to assess the difference in fiber density of homonym regions in the right and left hemisphere. Differences in connectivity patterns between OP2 and PIC were also estimated.We found that the bilateral intraparietal sulcus, PIC, and to a lesser degree OP2, are key ‘hub’ regions within the multimodal vestibular network. PIC and OP2 structural connectivity patterns were lateralized to the left hemisphere, while structural connectivity patterns of the posterior peri-sylvian supramarginal and superior temporal gyri were lateralized to the right hemisphere. These lateralization patterns were independent of handedness.We also found that the structural connectivity pattern of PIC is consistent with a key role of PIC in visuo-vestibular processing and that the structural connectivity pattern of OP2 is consistent with integration of mainly vestibular somato-sensory and motor information. These results suggest an analogy between PIC and the simian visual posterior sylvian (VPS) area and OP2 and the simian parieto-insular vestibular cortex (PIVC).Overall, these findings may provide novel insights to the current models of vestibular function, as well as to the understanding of the complexity and lateralized signs of vestibular syndromes.

Differential patterns of interhemispheric functional connectivity between AQP4-optic neuritis and MOG-optic neuritis: a resting-state functional MRI study.

Several neuroimaging studies demonstrated that optic neuritis (ON) leads to functional and anatomical architecture changes in the brain. The alterations of interhemispheric functional connectivity (IFC) in patients with AQP4-ON and myelin oligodendrocyte glycoprotein (MOG)-ON are not well understood. To investigate the differential patterns of VMHC in patients with AQP4-ON and MOG-ON. Twenty-one patients with AQP4-ON, 11 patients with MOG-ON, and 34 healthy controls underwent resting-state MRI scans. One-way ANOVA was used to identify regions in which the zVMHC differed among the three groups. Post hoc two-sample t-tests were then conducted to compare zVMHC values between pairs of groups. Pearson correlation analysis was conducted to reveal relationships between mean zVMHC values and clinical variables in the AQP4-ON and MOG-ON groups. The results revealed significant differences in zVMHC values in the PreCG among the three groups. Compared to the control group: the AQP4-ON group showed significantly lower VMHC values in the superior temporal gyrus, inferior frontal gyrus, and PreCG; and the MOG-ON group showed significantly higher zVMHC values in the PostCG. Compared to the AQP4-ON group, the MOG-ON group showed significantly lower zVMHC values in the PreCG/PostCG (voxel-level P<0.01, GRF correction, cluster-level P<0.05). Patients with AQP4-ON and those with MOG-ON showed abnormal VMHC in the motor cortices, sensorimotor cortices, and frontal lobe, possibly indicating impaired sensorimotor function in patients with ON. Moreover, differential patterns of VMHC in patients with AQP4-ON, compared to patients with MOG-ON, might serve as a clinical indicator for classification of ON.