Organization Of Structural Brain Networks Research Articles

Disrupted Structural Brain Networks and Structural-Functional Decoupling in First-Episode Drug-Naïve Adolescent Major Depressive Disorder

PurposeMajor depressive disorder (MDD) tends to emerge during adolescence, but the neurobiology of adolescent MDD is still poorly understood. This study aimed to explore the topological organization of white matter structural networks and the relationship between structural and functional connectivity in adolescent MDD. MethodsStructural and functional magnetic resonance imaging data were acquired from 94 first-episode drug-naïve adolescent MDD patients and 78 healthy adolescents. Whole brain structural and functional brain networks were constructed for each subject. Then, the topological organization of structural brain networks and the coupling strength between structural and functional connectivity were analyzed. ResultsCompared with controls, adolescent MDD patients showed disrupted small-world, rich-club, and modular organizations. Nodal centralities in the medial part of bilateral superior frontal gyrus, bilateral hippocampus, right superior occipital gyrus, right angular gyrus, bilateral precuneus, left caudate nucleus, bilateral putamen, right superior temporal gyrus, and right temporal pole part of superior temporal gyrus were significantly lower in adolescent MDD patients compared with controls. The coupling strength between structural and functional connectivity was significantly lower in adolescent MDD patients compared with controls. DiscussionOur findings suggest widespread disruption of structural brain networks and structural-functional decoupling in adolescent MDD, potentially leading to reduced network communication capacity.

Early adversity changes the economic conditions of mouse structural brain network organization.

Early adversity can change educational, cognitive, and mental health outcomes. However, the neural processes through which early adversity exerts these effects remain largely unknown. We used generative network modeling of the mouse connectome to test whether unpredictable postnatal stress shifts the constraints that govern the organization of the structural connectome. A model that trades off the wiring cost of long-distance connections with topological homophily (i.e., links between regions with shared neighbors) generated simulations that successfully replicate the rodent connectome. The imposition of early life adversity shifted the best-performing parameter combinations toward zero, heightening the stochastic nature of the generative process. Put simply, unpredictable postnatal stress changes the economic constraints that reproduce rodent connectome organization, introducing greater randomness into the development of the simulations. While this change may constrain the development of cognitive abilities, it could also reflect an adaptive mechanism that facilitates effective responses to future challenges.

Microstructural deficits of the thalamus in major depressive disorder.

Macroscopic structural abnormalities in the thalamus and thalamic circuits have been implicated in the neuropathology of major depressive disorder. However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. Here, we examined systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative MRI was used to examine structural-related alternations in 56 patients with depression compared with 35 age- and sex-matched controls. The seed-based probabilistic tractography showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in patients with depression. These subcortical regions included the putamen, thalamus and caudate, which are predominantly involved in the limbic-cortical-striatal-pallidal-thalamic network. Structural connectivity was disrupted within and between large-scale networks, including the subcortical network, default-mode network and salience network. Consistently, morphometric measurements, including cortical thickness and voxel-based morphometry, showed widespread volume reductions of these key regions in patients with depression. A conjunction analysis identified common structural alternations of the left orbitofrontal cortex, left putamen, bilateral thalamus and right amygdala across macro-modalities. Importantly, the microstructural properties, longitudinal relaxation time of the left thalamus was increased and inversely correlated with its grey matter volume in patients with depression. Together, this work to date provides the first macro–micro neuroimaging evidence for the structural abnormalities of the thalamus in patients with depression, shedding light on the neuropathological disruptions of the limbic-cortical-striatal-pallidal-thalamic circuit in major depressive disorder. These findings have implications in understanding the abnormal changes of brain structures across the development of depression.

The maturation and cognitive relevance of structural brain network organization from early infancy to childhood

The interactions of brain regions with other regions at the network level likely provide the infrastructure necessary for cognitive processes to develop. Specifically, it has been theorized that in infancy brain networks become more modular, or segregated, to support early cognitive specialization, before integration across networks increases to support the emergence of higher-order cognition. The present study examined the maturation of structural covariance networks (SCNs) derived from longitudinal cortical thickness data collected between infancy and childhood (0–6 years). We assessed modularity as a measure of network segregation and global efficiency as a measure of network integration. At the group level, we observed trajectories of increasing modularity and decreasing global efficiency between early infancy and six years. We further examined subject-based maturational coupling networks (sbMCNs) in a subset of this cohort with cognitive outcome data at 8–10 years, which allowed us to relate the network organization of longitudinal cortical thickness maturation to cognitive outcomes in middle childhood. We found that lower global efficiency of sbMCNs throughout early development (across the first year) related to greater motor learning at 8–10 years. Together, these results provide novel evidence characterizing the maturation of brain network segregation and integration across the first six years of life, and suggest that specific trajectories of brain network maturation contribute to later cognitive outcomes.

Towards understanding neurocognitive mechanisms of parenting: Maternal behaviors and structural brain network organization in late childhood.

A substantial body of knowledge suggests that exposure to adverse family environments – including violence and neglect – influences many aspects of brain development. Relatively less attention has been directed toward the influence of “normative” differences in parenting behaviors. Given the rapid brain reorganization during late childhood, parenting behaviors are particularly likely to impact the structure of the brain during this time. This study investigated associations between maternal parenting behaviors and the organization of structural brain networks in late childhood, as measured by structural covariance. One hundred and forty‐five typically developing 8‐year‐olds and their mothers completed questionnaire measures and two observed interaction tasks; magnetic resonance imaging (MRI) scans were obtained from the children. Measures of maternal negative, positive, and communicative behavior were derived from the interaction tasks. Structural covariance networks based on partial correlations between cortical thickness estimates were constructed and estimates of modularity were obtained using graph theoretical analysis. High levels of negative maternal behavior were associated with low modularity. Minimal support was found for an association between positive maternal behaviors and modularity and between maternal communicative behaviors and modularity. Our findings suggest that variation in negative maternal behavior is associated with the structural organization of brain networks in children.

Disrupted Structural Brain Network Organization Behind Depressive Symptoms in Major Depressive Disorder.

Major depressive disorder (MDD) is a severe and devastating condition. However, the anatomical basis behind the affective symptoms, cognitive symptoms, and somatic-vegetative symptoms of MDD is still unknown. To explore the mechanism behind the depressive symptoms in MDD, we used diffusion tensor imaging (DTI)–based structural brain connectivity analysis to investigate the network difference between MDD patients and healthy controls (CN), and to explore the association between network metrics and patients’ clinical symptoms. Twenty-six patients with MDD and 25 CN were included. A baseline 24-item Hamilton rating scale for depression (HAMD-24) score ≥ 21 and seven factors (anxiety/somatization, weight loss, cognitive disturbance, diurnal variation, retardation, sleep disturbance, hopelessness) scores were assessed. When compared with healthy subjects, significantly higher characteristic path length and clustering coefficient as well as significantly lower network efficiencies were observed in patients with MDD. Furthermore, MDD patients demonstrated significantly lower nodal degree and nodal efficiency in multiple brain regions including superior frontal gyrus (SFG), supplementary motor area (SMA), calcarine fissure, middle temporal gyrus (MTG), and inferior temporal gyrus (ITG). We also found that the characteristic path length of MDD patients was associated with weight loss. Moreover, significantly lower global efficiency of MDD patients was correlated with higher total HAMD score, anxiety somatization, and cognitive disturbance. The nodal degree in SFG was also found to be negatively associated with disease duration. In conclusion, our results demonstrated that MDD patients had impaired structural network features compared to CN, and disruption of optimal network architecture might be the mechanism behind the depressive symptoms and emotion disturbance in MDD patients.

Reduced segregation and integration of structural brain network associated with sympathetic and dorsal penile nerve activity in anejaculation patients: a graph-based connectome study.

Recent neuroimaging studies have indicated that some brain areas are involved in the sexual behavior process. Pre-mature ejaculation patients exhibit altered brain activation and abnormal cortical structures. However, there has been no research evaluating the topological organization of structural brain network in anejaculation (AE). We employed diffusion tensor imaging data and graph theory to examine the whole-brain structural networks among 16 AE patients and 23 healthy controls. In addition, the results of sexual function assessment were also obtained from each patient for symptom assessment. Moreover, the relationships between these clinical features and the altered topological characteristics of AE patients were also explored. Decreased clustering coefficient was found in the right amygdala, inferior temporal gyrus, and left pallidum of AE. AE also showed increased path length in the right post-central gyrus, supramarginal gyrus, putamen, pallidum and left heschl gyrus, temporal pole (superior temporal gyrus); however, these altered brain regions showed no significant differences after false discovery rate correction. Moreover, the path length between subcortical and frontal regions was increased in AE. In addition, negative correlations were found between the altered nodal parameters and the amplitudes of somatosensory evoked potentials of dorsal nerve, sympathetic skin response located in the penis. Together, our results suggest that AE was associated with disruptions in the topological organization of structural brain networks. The decreased clustering coefficient in temporal and subcortical regions and the increased path length between subcortical and frontal regions may contribute to AE. These findings provide new insights into the pathophysiological mechanisms of AE.

Childhood poverty and the organization of structural brain connectome

Socioeconomic disadvantage is associated with atypical development in specific brain regions, yet the relation between poverty and whole brain network organization (i.e., the connectome, a set of brain regions connected with neuronal pathways) has not been characterized. Developmental studies indicate that the connectome undergoes rapid change during childhood and is consequently likely to be highly sensitive to both salutary and detrimental influences. We investigated associations between the socioeconomic disparities measured by the income-to-needs ratio (INR) in childhood and structural brain network organization with 144 healthy children between 6 and 11 years of age (mean age = 8 years). INR of girls was positively and logarithmically associated with the extent to which brain networks were efficiently organized, suggesting that girls in more impoverished environments had less efficient brain network organization. Lower INR was associated with network inefficiency in multiple cortical regions including prefrontal cortex, cingulate, and insula, and in subcortical regions including the hippocampus and amygdala. These findings suggest that childhood poverty may result in wide-spread disruptions of the brain connectome among girls, particularly at the lowest INR levels, and are differentially expressed in females and males.

Disrupted topological organization of structural brain networks in childhood absence epilepsy

Childhood absence epilepsy (CAE) is the most common paediatric epilepsy syndrome and is characterized by frequent and transient impairment of consciousness. In this study, we explored structural brain network alterations in CAE and their association with clinical characteristics. A whole-brain structural network was constructed for each participant based on diffusion-weighted MRI and probabilistic tractography. The topological metrics were then evaluated. For the first time, we uncovered modular topology in CAE patients that was similar to healthy controls. However, the strength, efficiency and small-world properties of the structural network in CAE were seriously damaged. At the whole brain level, decreased strength, global efficiency, local efficiency, clustering coefficient, normalized clustering coefficient and small-worldness values of the network were detected in CAE, while the values of characteristic path length and normalized characteristic path length were abnormally increased. At the regional level, especially the prominent regions of the bilateral precuneus showed reduced nodal efficiency, and the reduction of efficiency was significantly correlated with disease duration. The current results demonstrate significant alterations of structural networks in CAE patients, and the impairments tend to grow worse over time. Our findings may provide a new way to understand the pathophysiological mechanism of CAE.

Positron Emission Tomography Reveals Abnormal Topological Organization in Functional Brain Network in Diabetic Patients.

Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM). However, the DM-related changes in the topological properties in functional brain networks are unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET) data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs), followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized characteristic path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing functional evidence for the abnormalities of brain networks in DM.

Aberrant Topological Patterns of Structural Cortical Networks in Psychogenic Erectile Dysfunction.

Male sexual arousal (SA) has been known as a multidimensional experience involving closely interrelated and coordinated neurobehavioral components that rely on widespread brain regions. Recent functional neuroimaging studies have shown relation between abnormal/altered dynamics in these circuits and male sexual dysfunction. However, alterations in the topological1 organization of structural brain networks in male sexual dysfunction are still unclear. Here, we used graph theory2 to investigate the topological properties of large-scale structural brain networks, which were constructed using inter-regional correlations of cortical thickness between 78 cortical regions in 40 patients with psychogenic erectile dysfunction (pED) and 39 normal controls. Compared with normal controls, pED patients exhibited a less optimal global topological organization with reduced global and increased local efficiencies. Our results suggest disrupted neural integration among distant brain regions in pED patients, consistent with previous reports of impaired white matter structure and abnormal functional integrity in pED. Additionally, disrupted global network topology in pED was observed to be primarily relevant to altered subnetwork and nodal properties within the networks mediating the cognitive, motivational and inhibitory processes of male SA, possibly indicating disrupted integration of these networks in the whole brain networks and might account for pED patients' abnormal cognitive, motivational and inhibitory processes for male SA. In total, our findings provide evidence for disrupted integrity in large-scale brain networks underlying the neurobehavioral processes of male SA in pED and provide new insights into the understanding of the pathophysiological mechanisms of pED.

Whole-brain structural topology in adult attention-deficit/hyperactivity disorder: Preserved global - disturbed local network organization.

Prior studies demonstrate altered organization of functional brain networks in attention-deficit/hyperactivity disorder (ADHD). However, the structural underpinnings of these functional disturbances are poorly understood. In the current study, we applied a graph-theoretic approach to whole-brain diffusion magnetic resonance imaging data to investigate the organization of structural brain networks in adults with ADHD and unaffected controls using deterministic fiber tractography. Groups did not differ in terms of global network metrics — small-worldness, global efficiency and clustering coefficient. However, there were widespread ADHD-related effects at the nodal level in relation to local efficiency and clustering. The affected nodes included superior occipital, supramarginal, superior temporal, inferior parietal, angular and inferior frontal gyri, as well as putamen, thalamus and posterior cerebellum. Lower local efficiency of left superior temporal and supramarginal gyri was associated with higher ADHD symptom scores. Also greater local clustering of right putamen and lower local clustering of left supramarginal gyrus correlated with ADHD symptom severity. Overall, the findings indicate preserved global but altered local network organization in adult ADHD implicating regions underpinning putative ADHD-related neuropsychological deficits.

Disrupted structural connectivity network in treatment-naive depression

Neuroimaging studies suggest that treatment-naive depression (TD) is characterized by abnormal functional connectivity between specific brain regions. However, the question surrounding the structural basis of functional aberrations in TD patients still remains. In the present study, diffusion tensor imaging tractography was employed to construct structural connectivity networks in 22 early adult-onset, first-episode TD patients and 19 healthy controls (HC). Graph theory and network-based statistic (NBS) were then employed to investigate systematically the alteration of whole brain structural topological organization and structural connectivity in TD patients. Graph theoretical analysis revealed that, compared with HC, TD patients exhibited altered structural topological measures, including decreased shortest path length, normalized clustering coefficient, normalized shortest path length, and small-worldness, as well as increased global and local efficiency. NBS results further revealed that TD patients showed two altered structural sub-networks. One sub-network mainly involved connections between the right orbitofrontal cortex (OFC) and the right insula, putamen, caudate, hippocampus, fusiform gyrus, inferior temporal gyrus and lingual gyrus. The other sub-network mainly included connections between the left OFC and the left gyrus rectus, insula, putamen, caudate, thalamus, pallidum and middle occipital gyrus. The findings suggest that TD patients exhibit a disruption in the topological organization of structural brain networks. The altered orbitofrontal connectivity may particularly contribute to the manifestation of symptoms in TD patients. The abnormalities may facilitate understanding of the functional disturbances of mood and cognition in the disease.

DWI and complex brain network analysis predicts vascular cognitive impairment in spontaneous hypertensive rats undergoing executive function tests.

The identification of biomarkers of vascular cognitive impairment is urgent for its early diagnosis. The aim of this study was to detect and monitor changes in brain structure and connectivity, and to correlate them with the decline in executive function. We examined the feasibility of early diagnostic magnetic resonance imaging (MRI) to predict cognitive impairment before onset in an animal model of chronic hypertension: Spontaneously Hypertensive Rats. Cognitive performance was tested in an operant conditioning paradigm that evaluated learning, memory, and behavioral flexibility skills. Behavioral tests were coupled with longitudinal diffusion weighted imaging acquired with 126 diffusion gradient directions and 0.3 mm3 isometric resolution at 10, 14, 18, 22, 26, and 40 weeks after birth. Diffusion weighted imaging was analyzed in two different ways, by regional characterization of diffusion tensor imaging (DTI) indices, and by assessing changes in structural brain network organization based on Q-Ball tractography. Already at the first evaluated times, DTI scalar maps revealed significant differences in many regions, suggesting loss of integrity in white and gray matter of spontaneously hypertensive rats when compared to normotensive control rats. In addition, graph theory analysis of the structural brain network demonstrated a significant decrease of hierarchical modularity, global and local efficacy, with predictive value as shown by regional three-fold cross validation study. Moreover, these decreases were significantly correlated with the behavioral performance deficits observed at subsequent time points, suggesting that the diffusion weighted imaging and connectivity studies can unravel neuroimaging alterations even overt signs of cognitive impairment become apparent.

A longitudinal study of structural brain network changes with normal aging

The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of change in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of change in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old) and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain.

Altered functional and structural brain network organization in autism

Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular network exhibiting small-world properties, network level organization has not been carefully examined in ASD. Here we used resting-state functional MRI (n = 42 ASD, n = 37 typically developing; TD) to show that children and adolescents with ASD display reduced short and long-range connectivity within functional systems (i.e., reduced functional integration) and stronger connectivity between functional systems (i.e., reduced functional segregation), particularly in default and higher-order visual regions. Using graph theoretical methods, we show that pairwise group differences in functional connectivity are reflected in network level reductions in modularity and clustering (local efficiency), but shorter characteristic path lengths (higher global efficiency). Structural networks, generated from diffusion tensor MRI derived fiber tracts (n = 51 ASD, n = 43 TD), displayed lower levels of white matter integrity yet higher numbers of fibers. TD and ASD individuals exhibited similar levels of correlation between raw measures of structural and functional connectivity (n = 35 ASD, n = 35 TD). However, a principal component analysis combining structural and functional network properties revealed that the balance of local and global efficiency between structural and functional networks was reduced in ASD, positively correlated with age, and inversely correlated with ASD symptom severity. Overall, our findings suggest that modeling the brain as a complex network will be highly informative in unraveling the biological basis of ASD and other neuropsychiatric disorders.

Abnormal topological organization of structural brain networks in schizophrenia

Schizophrenia is a debilitating mental disorder characterized by disturbances of thought and emotion as well as neurocognitive deficits. It is hypothesized that the core symptoms of schizophrenia arise from the inability to integrate neural processes segregated across distributed brain regions. Graph theory allows us to verify this hypothesis at large-scale structural network level. In this study, a sample of 101 schizophrenic patients and 101 healthy controls was included. We sought to investigate the abnormality of network topological organization in patients with schizophrenia by using the cortical thickness measurement from magnetic resonance imaging. Brain networks were constructed by thresholding cortical thickness correlation matrices of 78 regions and analyzed using graph theoretical approaches. Compared to healthy controls, patients showed increased characteristic path length and clustering coefficient in the structural cortical networks. Moreover, schizophrenia patients were associated with reduced nodal centrality in several regions of the default network and increased nodal centrality mainly in primary cortex and paralimbic cortex regions. These findings suggest that the structural networks of schizophrenic patients have a less optimal topological organization, resulting in reduced capacity to integrate information across brain regions.

Developmental Changes in Organization of Structural Brain Networks

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

Age‐related changes in topological organization of structural brain networks in healthy individuals

The aim of this study was to examine structural brain networks using regional gray matter volume, as well as to investigate changes in small-world and modular organization with normal aging. We constructed structural brain networks composed of 90 regions in young, middle, and old age groups. We randomly selected 350 healthy subjects for each group from a Japanese magnetic resonance image database. Structural brain networks in three age groups showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection cost. The small-world efficiency and node betweenness varied significantly and revealed a U- or inverted U-curve model tendency among three age groups. Results also demonstrated that structural brain networks exhibited a modular organization in which the connections between regions are much denser within modules than between them. The modular organization of structural brain networks was similar between the young and middle age groups, but quite different from the old group. In particular, the old group showed a notable decrease in the connector ratio and the intermodule connections. Combining the results of small-world efficiency, node betweenness and modular organization, we concluded that the brain network changed slightly, developing into a more distributed organization from young to middle age. The organization eventually altered greatly, shifting to a more localized organization in old age. Our findings provided quantitative insights into topological principles of structural brain networks and changes related to normal aging.