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Anhedonia is an enduring symptom of subthreshold depression (StD) and predict later onset of major depressive disorder (MDD). Brain structural covariance describes the inter-regional distribution of morphological changes compared to healthy controls (HC) and reflects brain maturation and disease progression. We investigated neural correlates of anhedonia from the structural covariance. T1-weighted brain magnetic resonance images were acquired from 79 young adults (26 StD, 30 MDD, and 23 HC). Intra-individual structural covariance networks of 68 cortical surface area (CSAs), 68 cortical thicknesses (CTs), and 14 subcortical volumes were constructed. Group-level hubs and principal edges were defined using the global and regional graph metrics, compared between groups, and examined for the association with anhedonia severity. Global network metrics were comparable among the StD, MDD, and HC. StD exhibited lower centralities of left pallidal volume than HC. StD showed higher centralities than HC in the CSAs of right rostral anterior cingulate cortex (ACC) and pars triangularis, and in the CT of left pars orbitalis. Less anhedonia was associated with higher centralities of left pallidum and right amygdala, higher edge betweenness centralities in the structural covariance (EBSC) of left postcentral gyrus-parahippocampal gyrus and LIPL-right amygdala. More anhedonia was associated with higher centralities of left inferior parietal lobule (LIPL), left postcentral gyrus, left caudal ACC, and higher EBSC of LIPL-left postcentral gyrus, LIPL-right lateral occipital gyrus, and left caudal ACC-parahippocampal gyrus. This study has a cross-sectional design. Structural covariance of brain morphologies within the salience and limbic networks, and among the salience-limbic-default mode-somatomotor-visual networks, are possible neural correlates of anhedonia in depression. [Display omitted] • The first brain structural covariance(SC) study of anhedonia in subthreshold depression(StD) • Lowered global segregation and integration of SC in StD than healthy control (HC) • Less anhedonia associated with higher centrality of amygdala and pallidum in the SC • More anhedonia with lower centrality of inferior parietal lobule, anterior cingulate, postcentral gyrus • Inter-network SC among the default mode-limbic-somatomotor-visual networks underlie anhedonia [ABSTRACT FROM AUTHOR]

Structural covariance network disruption has been considered an important pathophysiological indicator for schizophrenia. Here, we introduced a novel individualized structural covariance network measure, referred to as a texture similarity network (TSN), and hypothesized that the TSN could reliably reveal unique intersubject heterogeneity and complex dysconnectivity patterns in schizophrenia. The TSN was constructed by measuring the covariance of 180 three-dimensional voxelwise gray-level co-occurrence matrix feature maps between brain areas in each participant. We first tested the validity and reproducibility of the TSN in characterizing the intersubject variability in 2 longitudinal test-retest healthy cohorts. The TSN was further applied to elucidate intersubject variability and dysconnectivity patterns in 10 schizophrenia case-control datasets (609 schizophrenia cases vs. 579 controls) as well as in a first-episode depression dataset (69 patients with depression vs. 69 control participants). The test-retest analysis demonstrated higher TSN intersubject than intrasubject variability. Moreover, the TSN reliably revealed higher intersubject variability in both chronic and first-episode schizophrenia, but not in depression. The TSN also reproducibly detected coexistent increased and decreased TSN strength in widespread brain areas, increased global small-worldness, and the coexistence of both structural hyposynchronization in the central networks and hypersynchronization in peripheral networks in patients with schizophrenia but not in patients with depression. Finally, aberrant intersubject variability and covariance strength patterns revealed by the TSN showed a missing or weak correlation with other individualized structural covariance network measures, functional connectivity, and regional volume changes. These findings support the reliability of a TSN in revealing unique structural heterogeneity and complex dysconnectivity in patients with schizophrenia. [ABSTRACT FROM AUTHOR]

The differential structural covariance of nucleus accumbens (NAcc), playing a vital role in etiology and treatment, remains unclear in depression. We aimed to investigate whether structural covariance of NAcc was altered and how it was modulated by illness duration and severity of symptom measured with Hamilton Depression scale (HAMD). T1-weighted anatomical images of never-treated first-episode patients with depression (n = 195) and matched healthy controls (HCs, n = 78) were acquired. Gray matter volumes were calculated using voxel-based morphometry analysis for each subject. Then, we explored abnormal structural covariance of NAcc and how the abnormality was modulated by illness duration and severity of symptom. Patients with depression exhibited altered structural covariance of NAcc connected to key brain regions in reward system including the medial orbitofrontal cortex, amygdala, insula, parahippocampa gyrus, precuneus, thalamus, hippocampus and cerebellum. In addition, the structural covariance of the NAcc was distinctly modulated by illness duration and the severity of symptom in patients with depression. What is more, the structural covariance of the NAcc connected to hippocampus was modulated by these two factors at the same time. These results elucidate altered structural covariance of the NAcc and its distinct modulation of illness duration and severity of symptom. • The structural covariance of the NAcc was distinctly modulated by illness duration and the severity of symptom in patients with depression. • The structural covariance of the NAcc connected to hippocampus was modulated by these two factors at the same time. [ABSTRACT FROM AUTHOR]

An anomalous pattern of structural covariance has been reported in schizophrenia, which has been suggested to represent connectome changes during brain maturation and neuroprogressive processes. It remains unclear whether similar differences exist in a clinical high-risk state for psychosis, and if they are associated with a prodromal phenotype and/or later psychosis onset. This multicenter magnetic resonance imaging study cross-sectionally examined structural covariance in a large at-risk mental state (ARMS) sample with different outcomes. The whole-brain structural covariance of four cortical measures (thickness, area, volume, and gyrification) was assessed in 155 individuals with ARMS, who were subclassified into 26 (16.8 %) with a later psychosis onset (ARMS-P), 44 with persistent subthreshold psychotic symptoms, and 53 with the remission of psychotic symptoms (ARMS-R) during the clinical follow-up, and 191 healthy controls. The relationships of changes in structural covariance with clinical symptoms and cognitive impairments were also investigated in the ARMS subsample. Structural covariance was significantly higher in widespread cortical regions in the ARMS group than in the controls, with each cortical measure having a different pattern in affected cortical regions. The higher structural covariance of the cortical area was partly related to severe suspiciousness–persecutory ideation. Structural covariance was significantly higher, mainly in fronto-parietal gyrification, in the ARMS-P group than in the ARMS-R group. The present results suggest that changes in structural covariance result in psychosis vulnerability and the excessive structural covariance of brain gyrification in ARMS subjects may contribute to their later clinical course. • We examined structural covariance of cortical indices in multicenter ARMS samples. • ARMS individuals showed increased structural covariance in diverse cortical regions. • Increased structural covariance in fronto-parietal LGI was specific to ARMS-P group. • Structural covariance of CA was associated with subthreshold psychotic symptoms. • Excessive LGI structural covariance may predict future psychosis transition in ARMS. [ABSTRACT FROM AUTHOR]

• A longitudinal study identified specific changes of ventral striatum-related brain structural covariance and gray matter volume in first-episode patients with major depression disorder. • Patients with MDD exhibit specific cortico-ventral striatum-related reward network changes over time at the onset and one-year effective treatment after. • These findings facilitate further understanding of the pathogenesis and neuroplasticity in the onset and development of the MDD. Empirical findings suggest reduced cortico-striatal structural connectivity in patients with major depressive disorder (MDD). However, the relationship between the abnormal structural covariance and one-year outcome of first-episode drug-naive patients has not been evaluated. This longitudinal study aimed to identify specific changes of ventral striatum-related brain structural covariance and grey matter volume in forty-two first-episode patients with major depression disorder compared with thirty-seven healthy controls at the baseline and the one-year follow-up conditions. At the baseline, patients showed decreased structural covariance between the left ventral striatum and the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), right supplementary motor area (SMA) and left precentral gyrus and increased grey matter volume at the left fusiform and left parahippocampus. At the one-year follow-up, patients showed decreased structural covariance between the left ventral striatum and the right SFG, right MFG, left precentral gyrus and left postcentral gyrus, and increased structural covariance between the right ventral striatum and the right amygdala, right hippocampus, right parahippocampus, right superior temporal pole, right insula and right olfactory bulb and decreased volume at the left SMA compared with controls. These findings suggest that specific ventral striatum connectivity changes contribute to the early brain development of the MDD. [ABSTRACT FROM AUTHOR]

Introduction: Although previous studies have revealed that dysfunctional brain organization is associated with internet gamingdisorder (IGD), the neuroanatomical basis that underlies IGD remains elusive. In this work, we aimed to investigate gray matter (GM) volume alterations and structural covariance patterns in relation to IGD severity.Methods: Structural magnetic resonance imaging data were acquired from two hundred and thirty young adults encompassing a wide range of IGD severity. Voxel-based morphometry (VBM) analysis was applied to examine GM volume changes associated with IGD severity. Furthermore, the organization of whole-brain structural covariance network (SCN) was analyzed using the regions identified as seeds from VBM analysis.Results: Individuals with greater IGD severity had increased GM volumes in the midline components of the default mode network (DMN), namely, the right medial prefrontal cortex (mPFC) and precuneus. More importantly, the SCN results revealed impaired patterns of structural covariance between the DMN-related regions and areas associated with visuospatial attention and reward craving processing as the addiction severity of IGD worsened.Limitations: Only young Chinese adults were enrolled in our study andthe extent to which findings generalize to samples in other age groups and diverse cultures is unclear.Conclusions: These results showed volume expansion of the DMN components and its weakened structural association with visuospatial attention and motivational craving regions with increasing IGD severity. This study deepens our understanding of the underlying neuroanatomical correlates of IGD, which may help to explain why some individuals are more vulnerable to compulsive gaming usage than others. [ABSTRACT FROM AUTHOR]

Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms' severity. Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated. Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms. Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection. [Display omitted] • Multivariate structural covariance distinguishes first-episode psychosis from controls, univariate morphometry does not. • Gray matter structural covariance of the salience network nodes shows opposite patterns in psychosis and healthy controls. • Variation of salience network's gray matter is related to early untreated psychosis and its clinical symptoms severity. [ABSTRACT FROM AUTHOR]

• PS induced longitudinal GMV atrophy in bilateral cerebellar posterior lobes. • GMV decreased from 1 month, then continued to decrease after PS. • More covariant brain regions and structural connections were induced in PS groups. • The GMV changes of covariant brain regions were correlated with behavioral recovery. Our aim was to identify the longitudinal changes in gray matter volume (GMV) and secondary alterations of structural covariance after pontine stroke (PS). Structural MRI and behavioral scores were obtained at 1 week, 1 month, 3 months, 6 months in 11 patients with PS. Twenty healthy subjects underwent the same examination only once. We used voxel-based morphometry and seed-based structural covariance to investigate the altered GMV and structural covariance patterns. Furthermore, the associations between the GMV changes and behavioral scores were assessed. With the progression of the disease, GMV decreased significantly in the bilateral cerebellar posterior lobe (ipsilateral Crus II (CBE Crus II_IL) and contralateral Crus I (CBE Crus I_CL)), which were initially detected at the first month and then continued to decrease during the following 6 months. Based on the CBE Crus II_IL and CBE Crus I_CL as seed regions, structural covariance analysis revealed that there were more positively and negatively correlated brain regions in PS group, mainly distributed in the bilateral prefrontal lobe, parietal lobe, temporal lobe, paralimbic system and cerebellum. In addition, PS group showed more additional correlations between these covariant brain regions, and the changes of GMV in these regions were correlated with behavioral scores related to motor and cognitive functions. These findings indicate that PS could lead to significant GMV atrophy in the bilateral cerebellar posterior lobe at the early stage, accompanied by anomalous structural covariance patterns with more covariant brain regions and additional structural connectivity, which may provide useful information for understanding the neurobiological mechanisms of behavioral recovery after PS. [ABSTRACT FROM AUTHOR]

In this study, we applied brain grey matter volume and structural covariance methods on T1 weighted images to delineate potential structural brain changes in individuals with high schizotypy, who were defined as healthy individuals scoring in the top tenth percentile of the Schizotypal Personality Questionnaire (SPQ). Eighty-seven college students with high schizotypy and 122 controls were recruited in China. Differences in grey matter volume and volume covariance between the two groups, and correlations of grey matter volume with SPQ scores in the high schizotypy group were examined. We found that individuals with high schizotypy had decreased grey matter volume at the left medial superior frontal gyrus (medsFG) extending towards the superior frontal gyrus, decreased structural covariance within the right medsFG, between the right superior frontal gyrus (sFG), the right superior temporal gyrus and the right anterior insula; and increased structural covariance between the caudate and the right inferior temporal gyrus. Correlation analysis revealed that grey matter volume of the left middle temporal pole and the right sFG correlated positively with the SPQ total scores, volume of the bilateral cerebellum 9 sub-region correlated negatively with the SPQ cognitive-perceptual sub-scale scores, volume of the bilateral striatum correlated positively with the SPQ interpersonal sub-scale scores, and volume of the bilateral superior temporal pole correlated positively with the SPQ disorganization sub-scale scores in the high schizotypy group. These results highlight important grey matter structural changes in the medsFG in individuals with high schizotypy. [ABSTRACT FROM AUTHOR]

• First, a novel technique of causal structural covariance network density (CaSCNd)CaSCNd was proposed to map the epicenter of progressive structural damage in brain disease. Second, Our work provided new insights into progressive network damages in generalized epilepsies with different syndromes from structural domain. • Third, we contributed a viewpoint that IGTCS had an out-effect epicenter in the thalamus, whereas the SGTCS had equipotent in- and out-effects in the thalamus, cortex, and basal ganglia. Mapping progressive patterns of structural damage in epilepsies with idiopathic and secondarily generalized tonic-clonic seizures with causal structural covariance networks and multiple analysis strategies. Patients with idiopathic generalized tonic-clonic seizures (IGTCS) (n = 114) and secondarily generalized tonic-clonic seizures (SGTCS) (n = 125) were recruited. Morphometric parameter of gray matter volume was analyzed on structural MRI. Structural covariance network based on granger causality analysis (CaSCN) was performed on the cross-sectional morphometric data sorted by disease durations of patients. Seed-based CaSCN analysis was firstly carried out to map the progressive and influential patterns of damage to thalamus-related structures. A novel technique for voxel-based CaSCN density (CaSCNd) analysis was further proposed, enabling for identifying the epicenter of structural brain damage during the disease process. The thalamus-associated CaSCNs demonstrated different patterns of progressive damage in two types of generalized tonic-clonic seizures. In IGTCS, the structural damage was predominantly driven from the thalamus, and expanded to the cortex, while in SGTCS, the damage was predominantly driven from the cortex, and expanded to the thalamus through the basal ganglia. CaSCNd analysis revealed that the IGTCS had an out-effect epicenter in the thalamus, whereas the SGTCS had equipotent in- and out-effects in the thalamus, cortex, and basal ganglia. CaSCN revealed distinct damage patterns in the two types of GTCS, featuring with measurement of structural brain damage from the accumulating effect over a relatively long time period. Our work provided evidence for understanding network impairment mechanism underlying different GTCSs. [ABSTRACT FROM AUTHOR]

A growing body of evidences reveal that abnormal gray matter morphology is constrained by normal brain network architecture in neurodegenerative and psychiatric disorders. However, whether this finding holds true in obsessive-compulsive disorder (OCD) remains unknown. In the current study, we aimed to investigate the association between gray matter morphological abnormities and normal structural covariance network architecture in OCD. First, gray matter morphological abnormities were obtained between 98 medicine-naive and first-episode patients with OCD and 130 healthy controls (HCs). Then, putative disease epicenters whose structural connectome profiles in HCs most resembled the morphological differences pattern were identified using a backfoward stepwise regression analysis. A set of brain regions were identified as putative disease epicenters whose structural connectome architecture significantly explained 59.94% variance of morphological abnormalities. These disease epicenters comprised brain regions implicated in high-order cognitive functions and sensory/motor processing. Other brain regions with stronger structural connections to disease epicenters exhibited greater vulnerability to disease. Together, these results suggest that gray matter abnormities are constrained by structural connectome and provide new insights into the possible pathological progression in OCD. • Structural connectome architecture significantly explains 59.94% variance of morphological abnormalities. • Disease epicenters comprise brain regions implicated in high-order cognitive functions and sensory/motor processing. • This study provides new insights into pathological progression in OCD. [ABSTRACT FROM AUTHOR]

Very few studies have investigated longitudinal clinical cohorts of attention-deficit/hyperactivity disorder (ADHD). Moreover, how baseline brain changes could affect the development of ADHD symptoms later in life remains elusive. Therefore, we aimed to fill this gap by exploring brain and clinical changes in youth with ADHD using a longitudinal design. This prospective study consisted of 74 children and adolescents with ADHD and 50 age-, sex-, intelligence-matched typically developing controls (TDC), evaluated at baseline (aged 7–19 years) and re-evaluated 5.3 years later (a mean follow-up latency). We applied voxel-based morphometry to characterize brain structures, followed by both mass-univariate and multivariate structural covariance statistics to identify brain regions with significant diagnosis-by-time interactions from late childhood/adolescence to early adulthood. We used the cross-lagged panel model to investigate the longitudinal association between structural brain metrics and core ADHD symptoms. The mass-univariate statistic revealed significant diagnosis-by-time interactions in the right striatum and the sixth lobule of the cerebellum. This was expressed by increased striatal and decreased cerebellar volume in ADHD, while TDC showed inverse volume changes over time. The multivariate method showed significant diagnosis-by-time interactions in a structural covariance network consisting of the regions involved in the functional sensory-motor and default-mode networks. Higher baseline right striatal and cerebellar volumes were associated with elevated ADHD symptoms at follow-up. Our findings suggest a temporal association between the divergent development of striatal and cerebellar regions and dynamical ADHD phenotypic expression through young adulthood. These results highlight a potential brain marker of future outcomes. • Brain structural changes in ADHD were investigated from childhood to young adulthood. • Structures were estimated using voxel-based morphometry and structural covariance. • Diagnosis-by-time interactions were observed in the right striatum and cerebellum. • Baseline striatal/cerebellar volumes predicted ADHD symptom severity later in life. [ABSTRACT FROM AUTHOR]

Background: Anxiety is highly prevalent in Parkinson's disease (PD) and has great negative impact on quality of life. Functional and structural neuroimaging studies have contributed to our understanding of the symptomatology of PD but still little is known about the pathophysiology of PD-related anxiety.Methods: We used seed-based structural covariance analysis to study the anatomical network correlates of anxiety in PD. Structural covariance analysis is based on the statistical correlation between regional brain volumes measured on T1-weighted magnetic resonance images. We investigated the association between anxiety symptoms, as measured by the Beck Anxiety Inventory (BAI), and seed-to-whole-brain structural covariance networks in 115 patients with idiopathic PD using five bilateral seeds: basolateral amygdala, centromedial-superficial amygdala, dorsal caudate nucleus, dorsal-caudal putamen, and nucleus accumbens.Results: Severity of anxiety correlated negatively with structural covariance between the left striatal sub-regions and the contralateral caudate nucleus. Moreover, severity of anxiety was associated with reduced structural covariance between the right dorsal caudate nucleus and ipsilateral ventrolateral prefrontal cortex and between the left nucleus accumbens and ipsilateral dorsolateral prefrontal cortex. Structural covariance of the amygdalar seeds did not correlate with anxiety.Conclusions: We interpret these findings as a reduced interhemispheric cooperation between the left and right striatum and reduced prefrontal-striatal connectivity, possibly related to impaired 'top-down' regulation of emotions. These findings shed more light on the pathophysiology of PD-related anxiety LIMITATIONS: This study did not include PD patients with an anxiety disorder. [ABSTRACT FROM AUTHOR]

Background: Functional brain abnormalities have been noted in premenstrual syndrome (PMS). However, the brain structural alterations related to PMS remain unclear. This study aimed to identify possible abnormalities in gray matter (GM) volumes and structural covariance patterns among PMS patients.Methods: Structural magnetic resonance imaging data were obtained from 20 PMS patients and 20 healthy controls. Voxel-based morphometry (VBM) analysis was applied to examine GM volumes changes between the two groups. Receiver operating characteristic (ROC) curve was used to investigate the most reliable biomarker for distinguishing PMS patients from health controls based on the intergroup differences. Correlation analysis was then performed to assess relationships between the daily rating of severity of problems (DRSP) and abnormal brain regions. Finally, the regions identified from VBM analysis were served as seeds to characterize the whole-brain structural covariance patterns.Results: Compared with healthy controls, PMS patients showed increased GM volumes in the precuneus/posterior cingulate cortex (precuneus/PCC) and thalamus, and decreased GM volumes in the insula. The precuneus/PCC exhibited the highest classification power by ROC analysis and positively correlated with the DRSP. Moreover, different patterns of structural covariance in the two groups were mainly located in the dorsolateral prefrontal cortex, anterior cingulate cortex, angular gyrus and hippocampus.Limitations: This study is limited by a small sample and narrow age range of participants.Conclusions: Our findings may provide preliminary evidence for brain morphology alterations in PMS patients and contribute to a better understanding of the pathophysiology of PMS. [ABSTRACT FROM AUTHOR]

Apolipoprotein E ( APOE ) ε4 has been associated with smaller hippocampal volumes in healthy aging, while findings in young adults are inconclusive. Previous studies have mostly used univariate methods, and without considering potential anterior/posterior differences. Here, we used a multivariate method, partial least squares, and assessed whole-brain structural covariance of the anterior (aHC) and posterior (pHC) hippocampus in young adults ( n = 97) as a function of APOE ε4 status and sex. Two significant patterns emerged: (1) specific structural covariance of the aHC with frontal regions, temporal and occipital areas in APOE ε4 women, whereas the volume of both the aHC and pHC in all other groups co-varied with frontal, parietal and cerebellar areas; and (2) opposite structural covariance of the pHC in ε4 carriers compared to the aHC in non-carriers, with the pHC of ε4 carriers covarying with parietal and frontal areas, and the aHC of ε4 non-carriers covarying with motor areas and the middle frontal gyrus. APOE ε4 has in young adults been associated with better episodic and spatial memory, functions involving the aHC and pHC, respectively. We found no associations between structural covariance and performance, suggesting that other factors underlie the performance differences seen between carriers and non-carriers. Our findings indicate that APOE ε4 carriers and non-carriers differ in hippocampal organization and that there are differences as a function of sex and hippocampal segment. They stress the need to consider the hippocampus as a heterogeneous structure, and highlight the benefits of multivariate methods in assessing group differences in the brain. [ABSTRACT FROM AUTHOR]

Hippocampal-cortical networks play an important role in neurocognitive development. Applying the method of Connectivity-Based Parcellation (CBP) on hippocampal-cortical structural covariance (SC) networks computed from T1-weighted magnetic resonance images, we examined how the hippocampus differentiates into subregions during childhood and adolescence (N = 1105, 6–18 years). In late childhood, the hippocampus mainly differentiated along the anterior-posterior axis similar to previous reported functional differentiation patterns of the hippocampus. In contrast, in adolescence a differentiation along the medial-lateral axis was evident, reminiscent of the cytoarchitectonic division into cornu ammonis and subiculum. Further meta-analytical characterization of hippocampal subregions in terms of related structural co-maturation networks, behavioural and gene profiling suggested that the hippocampal head is related to higher order functions (e.g. language, theory of mind, autobiographical memory) in late childhood morphologically co-varying with almost the whole brain. In early adolescence but not in childhood, posterior subicular SC networks were associated with action-oriented and reward systems. The findings point to late childhood as an important developmental period for hippocampal head morphology and to early adolescence as a crucial period for hippocampal integration into action- and reward-oriented cognition. The latter may constitute a developmental feature that conveys increased propensity for addictive disorders. • In late childhood, the HF mainly differentiated along the anterior-posterior axis. • In adolescence, the HF differentiated along the medial-lateral axis. • Late childhood is an important developmental period for hippocampal head morphology. • Early adolescence is a crucial period for HF related to action- and reward-systems. [ABSTRACT FROM AUTHOR]

• Multiple sclerosis patients exhibited extensive atrophy of subcortical regions. • Multiple sclerosis patients had more additional connections in structural covariance. • More missing connections were found in NMOSD patients. • The structural covariance can use multi-atlas-based anatomical segmentation method. This study aimed to investigate the alterations of brain volumetry and associated structural covariance in subcortical regions in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). Fourty MS patients, 35 NMOSD patients and 34 healthy controls (HC) underwent 3D T1-weighted image and 3D T2 FLAIR of MRI. The volume differences in subcortical regions were compared between the MS, NMOSD, and HC groups by automated brain volumetry. Structural covariance analysis was performed with each pair of these regions to investigate the alterations of anatomical connections in MS and NMOSD compared to HC. Compared with HC, MS patients presented significantly smaller volume in some subcortical and infratentorial regions (P <0.05), while NMOSD patients showed no significant difference of volumetry in any of the brain regions (P >0.05), although they had no significant difference in disease duration (MS 3.95±3.73 ys; NMOSD 3.11±4.61 ys; P >0.05). In addition, the structural covariance analyses revealed synergic volume alteration in subcortical regions both in the MS and NMOSD groups. More extensive additional connections compared with HC were found in MS patients and more extensive missing connections compared with HC were found in NMOSD patients. This study revealed distinct patterns of brain structural damage and reorganization in MS and NMOSD, which could facilitate a better distinction between these two entities. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a common psychiatric disorder that is characterized by cognitive deficits and affective symptoms. To date, an increasing number of neuroimaging studies have focused on emotion regulation and have consistently shown that emotion dysregulation is one of the central features and underlying mechanisms of MDD. Although gray matter morphological abnormalities in regions within emotion regulation networks have been identified in MDD, the interactions and relationships between these gray matter structures remain largely unknown. Thus, in this study, we adopted a structural covariance method based on gray matter volume to investigate the brain morphological abnormalities within the emotion regulation networks in a large cohort of 65 MDD patients and 65 age- and gender-matched healthy controls. A permutation test with p < 0.05 was used to identify the significant changes in covariance connectivity strengths between MDD patients and healthy controls. The structural covariance analysis revealed an increased correlation strength of gray matter volume between the left angular gyrus and the left amygdala and between the right angular gyrus and the right amygdala, as well as a decreased correlation strength of the gray matter volume between the right angular gyrus and the posterior cingulate cortex in MDD. Our findings support the notion that emotion dysregulation is an underlying mechanism of MDD by revealing disrupted structural covariance patterns in the emotion regulation network. [ABSTRACT FROM AUTHOR]

The relationship between structural brain alterations and prediction of clinical improvement in first-episode psychosis (FEP) has been scarcely studied. We investigated whether structural covariance, a well-established approach to identify abnormal patterns of volumetric correlation across distant brain regions, which allows incorporating network-level information to structural assessments, is associated with longitudinal clinical course. We assessed a sample of 74 individuals from a multicenter study. Magnetic resonance imaging scans were acquired at baseline, and clinical assessments at baseline and at a 2-year follow-up. Participants were split in two groups as a function of their clinical improvement after 2 years (i.e., ≥ < 40% reduction in psychotic symptom severity, (n = 29, n = 45)). We performed a seed-based approach and focused our analyses on 3 cortical and 4 subcortical regions of interest to identify alterations in cortical and cortico-subcortical networks. Improvers presented an increased correlation between the volumes of the right posterior cingulate cortex (PCC) and the left precentral gyrus, and between the left PCC and the left middle occipital gyrus. They also showed an increased correlation between right posterior hippocampus and left angular gyrus volumes. Our study provides a novel mean to identify structural correlates of clinical improvement in FEP, describing clinically-relevant anatomical differences in terms of large-scale brain networks, which is better aligned with prevailing neurobiological models of psychosis. The results involve brain regions considered to participate in the multisensory processing of bodily signals and the construction of bodily self-consciousness, which resonates with recent theoretical accounts in psychosis research. • Structural covariance identifies network-level correlates of improvement in FEP. • Changes in posterior brain networks relate to clinical improvement. • Such networks involve bodily signals and self-consciousness processing regions. • Results align with neurobiological models and theoretical accounts of psychosis. [ABSTRACT FROM AUTHOR]

Structural covariance, the examination of anatomic correlations between brain regions, has emerged recently as a valid and useful measure of developmental brain changes. Yet the exact biological processes leading to changes in covariance, and the relation between such covariance and behavior, remain largely unexplored. The steroid hormone testosterone represents a compelling mechanism through which this structural covariance may be developmentally regulated in humans. Although steroid hormone receptors can be found throughout the central nervous system, the amygdala represents a key target for testosterone-specific effects, given its high density of androgen receptors. In addition, testosterone has been found to impact cortical thickness (CTh) across the whole brain, suggesting that it may also regulate the structural relationship, or covariance, between the amygdala and CTh. Here, we examined testosterone-related covariance between amygdala volumes and whole-brain CTh, as well as its relationship to aggression levels, in a longitudinal sample of children, adolescents, and young adults 6–22 years old. We found: (1) testosterone-specific modulation of the covariance between the amygdala and medial prefrontal cortex (mPFC); (2) a significant relationship between amygdala-mPFC covariance and levels of aggression; and (3) mediation effects of amygdala-mPFC covariance on the relationship between testosterone and aggression. These effects were independent of sex, age, pubertal stage, estradiol levels and anxious-depressed symptoms. These findings are consistent with prior evidence that testosterone targets the neural circuits regulating affect and impulse regulation, and show, for the first time in humans, how androgen-dependent organizational effects may regulate a very specific, aggression-related structural brain phenotype from childhood to young adulthood. [ABSTRACT FROM AUTHOR]

Schizophrenia is a neurodevelopmental disorder that produces abnormalities across different brain regions. Measuring structural covariance with MRI is a well-established approach to investigate common changes in distinct systems. We investigated structural covariance in schizophrenia in a large Brazilian sample of individuals with chronic schizophrenia (n = 143), First Episode Psychosis (n = 32), and matched healthy controls (n = 82) using a combination of graph analysis and computational neuroanatomy. Firstly, we proposed the connectivity-closeness and integrity-closeness centrality measures and them compared healthy controls with chronic schizophrenia regarding these metrics. We then conducted a second analysis on the mapped regions comparing the pairwise difference between the three groups. Our results show that compared with controls, both patient groups (in pairwise comparisons) had a reduced integrity-closeness in pars orbitalis and insula, suggesting that the relationship between these areas and other brain regions is increased in schizophrenia. No differences were found between the First Episode Psychosis and Schizophrenia groups. Since in schizophrenia the brain is affected as a whole, this may mirror that these regions may be related to the generalized structural alteration seen in schizophrenia. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by atypical structural and functional brain connectivity. Complex network analysis has been mainly used to describe altered network-level organization for functional systems and white matter tracts in ASD. However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems level. In this study, we examined network centrality properties of gray matter networks in adults with ASD (n = 84) and neurotypical controls (n = 84) using graph theoretical analysis. We derived a structural covariance network for each group using interregional correlation matrices of cortical volumes extracted from a surface-based parcellation scheme containing 68 cortical regions. Differences between groups in closeness network centrality measures were evaluated using permutation testing. We identified several brain regions in the medial frontal, parietal and temporo-occipital cortices with reductions in closeness centrality in ASD compared to controls. We also found an association between an increased number of autistic traits and reduced centrality of visual nodes in neurotypicals. Our study shows that ASD are accompanied by atypical organization of structural covariance networks by means of a decreased centrality of regions relevant for social and sensorimotor processing. These findings provide further evidence for the altered network-level connectivity model of ASD. [ABSTRACT FROM AUTHOR]

Background Investigation of aberrant large-scale brain networks offers novel insight into the role these networks play in diverse psychiatric disorders such as schizophrenia. Although studies report altered functional brain connectivity in participants at ultra-high risk (UHR) for psychosis, it is unclear whether these alterations extend to structural brain networks. Methods Whole-brain structural covariance patterns of 133 participants at UHR for psychosis (51 of whom subsequently developed psychosis) and 65 healthy control (HC) subjects were studied. Following data preprocessing (using VBM8 toolbox), the mean signal in seed regions relating to specific networks (visual, auditory, motor, speech, semantic, executive control, salience, and default-mode) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain signal and each seed region for UHR and HC individuals. The UHR participants who transitioned to psychosis were compared with the UHR participants who did not. Results Significantly reduced structural covariance was observed in the UHR sample compared with the HC sample for the default-mode network, and increased covariance was observed for the motor and executive control networks. When the UHR participants who transitioned to psychosis were compared with the UHR participants who did not, aberrant structural covariance was observed in the salience, executive control, auditory, and motor networks. Conclusions Whole-brain structural covariance analyses revealed subtle changes of connectivity of the default-mode, executive control, salience, motor, and auditory networks in UHR individuals for psychosis. Although we found significant differences, these are small changes and tend to reflect largely intact structural networks. [ABSTRACT FROM AUTHOR]

Many studies point toward volume reductions in the amygdala as a potential neurostructural marker for trait aggression. However, most of these findings stem from clinical samples, rendering unclear whether the findings generalize to non-clinical populations. Furthermore, the notion of neural networks suggests that interregional correlations in gray matter volume (i.e., structural covariance) can explain individual differences in aggressive behavior beyond local univariate associations. Here, we tested whether structural covariance between amygdala subregions and the rest of the brain is associated with self-reported aggression in a large sample of healthy young students (n = 263; 49% women). Salivary testosterone concentrations were measured for a subset of n = 40 male and n = 36 female subjects, allowing us to investigate the influence of endogenous testosterone on structural covariance. Aggressive individuals showed enhanced covariance between left superficial amygdala (SFA) and left dorsal anterior insula (dAI), but lower covariance between right laterobasal amygdala (LBA) and right dorsolateral prefrontal cortex (dlPFC). These structural patterns overlap with functional networks involved in the genesis and regulation of aggressive behavior, respectively. With increasing endogenous testosterone, we observed stronger structural covariance between right centromedial amygdala (CMA) and right medial prefrontal cortex in men and between left CMA and bilateral orbitofrontal cortex in women. These results speak for structural covariance of amygdala subregions as a robust correlate of trait aggression in healthy individuals. Moreover, regions that showed structural covariance with the amygdala modulated by either testosterone or aggression did not overlap, suggesting a complex role of testosterone in human social behavior beyond facilitating aggressiveness. [ABSTRACT FROM AUTHOR]

• Studies in individuals with attenuated psychosis syndrome (APS) could help in the understanding of the development of psychosis. • Although cerebellar structural changes have been identified in schizophrenia patients, little is known for individuals with APS. • In this study, we examined cerebellar volumes and cerebello-cerebral structural covariance in APS individuals, the results suggest that prefrontal and striatal structural changes as well as cerebellar structural covariance at the medial prefrontal gyrus may underpin the risk for psychosis and may serve as a potential target for early intervention in individuals at-risk for psychosis. Reduced cerebellar volumes and altered cerebellocerebral structural covariance have been reported in patients with schizophrenia. However, it is not clear whether such altered cerebellocerebral structural covariance would be observed before the onset of psychosis. We examined brain structural changes, including cerebral and cerebellar volumes, and cerebellocerebral structural covariance in individuals with attenuated psychosis syndrome (APS). Twenty-one individuals with APS and 24 healthy controls (HC) were recruited and underwent structural MRI brain scan. Differences in voxel-based grey matter (GM) volume and cerebellar volume between the APS and HC groups were examined. The correlation between cerebellar volumes and voxel-based cerebral GM volumes were calculated to measure cerebellocerebral structural covariance in each group followed by group comparisons. Compared with HC, individuals with APS exhibited extensive GM volume reduction in the frontal and striatal areas and reduced cerebellar volume. Structural covariance analysis indicated that the anterior and posterior parts of the cerebellum showed disparate correlation with cerebral voxel-based GM volumes. Abnormal cerebellar-cerebral correlation was also found in individuals with APS at the medial prefrontal gyrus. Our findings suggest that prefrontal and striatal structural changes as well as cerebellar structural covariance at the medial prefrontal gyrus may underpin the risk for psychosis and may serve as a potential target for early intervention in individuals at-risk for psychosis. [ABSTRACT FROM AUTHOR]

Individuals with sub-threshold psychotic symptoms (STPS) are considered at clinical high risk for psychosis (CHR). Imaging studies comparing CHR and patients shortly after a first episode of psychosis (FEP) support progressive cortical thinning by illness stage. However, at least 30% of FEP patients deny pre-onset STPS, suggesting no history of CHR. This calls into question the generalizability of previous imaging findings. To better understand the physiology of early psychosis symptomology, we investigated the relationship between pre-onset STPS and cortical thickness (CT) among FEP patients, examining regional CT and structural covariance (SC). Patients (N = 93) were recruited from PEPP-Montreal, a FEP clinic at the Douglas Mental Health University Institute. The Circumstances of Onset and Relapse Schedule was administered to retrospectively identify patients who recalled at least one of nine expert-selected STPS prior to their FEP (STPS+, N = 67) and to identify those who did not (STPS-, N = 26). Age and sex-matched healthy controls (HC) were recruited (N = 84) for comparison. Participants were scanned between one and three times over the course of two years. CT values of 320 scans (143 HC, 123 STPS+, 54 STPS-) that passed quality control were extracted for group analysis. Linear mixed effects models accounting for effects of age, sex, education, and mean thickness were applied for vertex-wise, group comparisons of cortical thickness and SC. Multiple comparison corrections were applied with Random Field Theory (p-cluster = 0.001). Compared to controls, only STPS- patients exhibited significantly reduced CT in a cluster of the right ventral lateral prefrontal cortex. The vertex with the highest t-statistic within this cluster was employed as a seed in the subsequent SC analysis. After RFT-correction, STPS+ patients exhibited significantly stronger SC between the seed and right pars orbitalis compared to STPS- patients, and HC exhibited significantly stronger SC between the seed and right middle temporal gyrus compared to STPS- patients. Our results revealed patterns of SC that differentiated patient subgroups and patterns of cortical thinning unique to STPS- patients. Our study demonstrates that the early course of sub-threshold psychotic symptoms holds significance in predicting patterns of CT during FEP. • Whether patients in a first episode of psychosis had prior subthreshold psychotic symptoms (STPS) predicted neural trends. • Pre-onset STPS is associated with greater structural covariance in regions within the right prefrontal cortex (rPFC). • Compared to controls, patients without prior STPS had increased rPFC cortical thinning while those with prior STPS did not. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the alterations of brain volumetry and associated structural covariance at lobar level in cerebral small-vessel disease (CSVD) with and without cognitive impairment.Method: Twenty-seven CSVD patients with mild cognitive impairment (CSVD-MCI), 37 CSVD patients with normal cognition (CSVD-NC), and 35 controls, underwent T1-weighted imaging of magnetic resonance. Volume of gray matter (GM) and white matter (WM) and a lobar atrophy index that measures the ratio of cerebrospinal fluid to brain parenchyma were quantified for each lobe. One-way ANOVA with multiple comparison corrections was performed to compare these volumetric measures. Volumetric structural covariance analyses were performed with lobar atrophy indexes to investigate the alterations of anatomical covariance within each pair of lobar regions in CSVD-NC and CSVD-MCI subjects compared with controls.Results: CSVD-NC subjects presented no significant volumetric differences with controls in any of the lobar regions. Compared with controls, CSVD-MCI patients presented significantly smaller volume of GM in bilateral frontal and parietal lobes, significantly smaller volume of WM in right cingulate lobe, and significantly larger lobar atrophy indexes of bilateral temporal, insular lobes and left cingulate lobe (P < 0.05). Both CSVD-NC group and CSVD-MCI group showed significant differences of structural covariance as measured by lobar atrophy index compared with controls. In particular, CSVD-MCI group showed even more extensive alterations of structural covariance, especially in bilateral cingulate and temporal lobes.Conclusions: There are alterations of brain volumetry and associated structural covariance within lobar regions in CSVD, which indicates the potential brain structural reorganization in CSVD. [ABSTRACT FROM AUTHOR]

Abnormalities in the structure of subcortical regions are central to numerous behaviors affected by autism spectrum disorder (ASD), and these regions may undergo atypical coordinated neurodevelopment. However, relatively little is known about morphological correlations among subcortical structures in young children with ASD. In this study, using volumetric-based methodology and structural covariance approach, we investigated structural covariance of subcortical brain volume in 40 young children with ASD (<7.5 years old) and 38 age-, gender-, and handedness-matched typically developing (TD) children. Results showed that compared with TD children, children with ASD exhibited decreased structural covariation between the left and right cerebral hemispheres, specifically between the left and right thalami, right globus pallidus and left nucleus accumbens, and left globus pallidus and right nucleus accumbens. Compared with TD children, children with ASD exhibited increased structural covariation between adjacent regions, such as between the right globus pallidus and right putamen. Additionally, abnormalities in subcortical structural covariance can predict social communication and repetitive and stereotypic behavior in young children with ASD. Overall, these results suggest decreased long-range structural covariation and enhanced local covariation in subcortical structures in children with ASD, highlighting aberrant developmental coordination or synchronized maturation between subcortical regions that play crucial roles in social cognition and behavior in ASD. • Decreased inter-hemispheric structural covariation in ASD. • Increased intra-hemispheric structural covariation in ASD. • Abnormalities in subcortical structural covariance can predict behavior of ASD. [ABSTRACT FROM AUTHOR]