Pain resilience and regional gray matter volume (rGMV) are established correlates of adaptation to chronic pain within cross-sectional studies. Extending such work, this prospective cohort study tested the status of baseline pain resilience dimension scores and rGMV as risk factors for subsequent exacerbations in chronic pain disability and intensity.

142 adults with chronic musculoskeletal pain completed an initial assessment comprising a structural magnetic resonance imaging scan and self-report measures of cognitive/affective positivity and behavioral perseverance pain resilience dimensions, disability, pain intensity, and demographics. Disability and pain intensity were outcomes re-assessed at a 6-month follow-up. The impact of pain resilience dimension scores and identified rGMV sites on follow-up outcomes was examined after controlling for other baseline correlates of outcomes. Mediating effects of identified rGMV sites on pain resilience dimension-follow-up outcome relations were also evaluated.

Aside from the significant multivariate effect of lower behavioral perseverance and cognitive/affective positivity scores, augmented left precuneus, temporal pole, superior temporal gyrus (STG), and precentral gyrus rGMV combined to predict higher follow-up disability levels, independent of covariates. Higher left fusiform gyrus rGMV levels predicted follow-up exacerbations in pain intensity, but pain resilience dimension scores did not. Finally, left precuneus and left temporal pole STG rGMV partially mediated cognitive/affective positivity-follow-up disability relations.

Findings underscore deficits in pain resilience and increased rGMV as potential risk factors for poorer subsequent outcomes of chronic musculoskeletal pain and provide foundations for further prospective extensions as well as targeted intervention research.

Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine.

We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort.

Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable.

Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.

Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

In 410 male and female participants aged 17–35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aβ) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD.

Older adults with major depression (N = 121, Ages 65–91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aβ standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity.

Greater anxiety severity was associated with lower OFC volume (β = −68.25, t = −2.18, p = .031) and greater cognitive dysfunction (β = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aβ SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (β = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety.

Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.

Geriatric depression (GD) is associated with cognitive impairment and brain atrophy. Tai-Chi-Chih (TCC) is a promising adjunct treatment to antidepressants. We previously found beneficial effects of TCC on resting state connectivity in GD. We now tested the effect of TCC on gray matter volume (GMV) change and the association between baseline GMV and clinical outcome.

Forty-nine participants with GD (>=60 y) underwent antidepressant treatment (38 women).

Participants completed 3 months of TCC (N = 26) or health and wellness education control (HEW; N = 23).

Depression and anxiety symptoms and MRI scans were acquired at baseline and 3-month follow-up. General linear models (GLMs) tested group-by-time interactions on clinical scores. Freesurfer 6.0 was used to process T1-weighted images and to perform voxel-wise whole-brain GLMs of group on symmetrized percent GMV change, and on the baseline GMV and symptom change association, controlling for baseline symptom severity. Age and sex served as covariates in all models.

There were no group differences in baseline demographics or clinical scores, symptom change from baseline to follow-up, or treatment-related GMV change. However, whole-brain analysis revealed that lower baseline GMV in several clusters in the TCC, but not the HEW group, was associated with larger improvements in anxiety. This was similar for right precuneus GMV and depressive symptoms.

While we observed no effect on GMV due to the interventions, baseline regional GMV predicted symptom improvements with TCC but not HEW. Longer trials are needed to investigate the long-term effects of TCC on clinical symptoms and neuroplasticity.

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.

A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.

Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen’s Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).

These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

The neuroanatomical alteration in bipolar II depression (BDII-D) and its associations with inflammation, childhood adversity, and psychiatric symptoms are currently unclear. We hypothesize that neuroanatomical deficits will be related to higher inflammation, greater childhood adversity, and worse psychiatric symptoms in BDII-D.

Voxel- and surface-based morphometry was performed using the CAT toolbox in 150 BDII-D patients and 155 healthy controls (HCs). Partial Pearson correlations followed by multiple comparison correction was used to indicate significant relationships between neuroanatomy and inflammation, childhood adversity, and psychiatric symptoms.

Compared with HCs, the BDII-D group demonstrated significantly smaller gray matter volumes (GMVs) in frontostriatal and fronto-cerebellar area, insula, rectus, and temporal gyrus, while significantly thinner cortices were found in frontal and temporal areas. In BDII-D, smaller GMV in the right middle frontal gyrus (MFG) was correlated with greater sexual abuse (r = −0.348, q < 0.001) while larger GMV in the right orbital MFG was correlated with greater physical neglect (r = 0.254, q = 0.03). Higher WBC count (r = −0.227, q = 0.015) and IL-6 levels (r = −0.266, q = 0.015) was associated with smaller GMVs in fronto-cerebellar area in BDII-D. Greater positive symptoms was correlated with larger GMVs of the left middle temporal pole (r = 0.245, q = 0.03).

Neuroanatomical alterations in frontostriatal and fronto-cerebellar area, insula, rectus, temporal gyrus volumes, and frontal-temporal thickness may reflect a core pathophysiological mechanism of BDII-D, which are related to inflammation, trauma, and psychiatric symptoms in BDII-D.

Childhood adversity is associated with abnormalities in brain structure, but this association has not been tested for childhood unpredictability, one form of adversity. We studied whether abnormalities in gray matter volume (GMV) could be a mechanism linking childhood unpredictability and psychopathology, over and above the effect of childhood trauma.

Participants were 158 right-handed healthy young adults (aged 17–28 years, M = 22.07, s.d. = 2.08; 66.46% female) who underwent structural magnetic resonance imaging measurements and provided retrospective reports of childhood unpredictability. The anxiety and depression subscales of the self-report Brief Symptom Inventory-53 were used to index psychopathology.

Whole-brain voxel-based morphometric analyses showed that after controlling for the effect of childhood trauma, childhood unpredictability was correlated with greater GMV in bilateral frontal pole, bilateral precuneus, bilateral postcentral gyrus, right hemisphere of fusiform, and lingual gyrus, and left hemisphere of ventrolateral prefrontal cortex as well as occipital gyrus. Greater GMV in bilateral frontal pole, bilateral precuneus, and bilateral postcentral gyrus mediated associations between unpredictability and symptoms of depression and anxiety.

The findings suggest that childhood unpredictability could exact unique effects on neural development, over and above the effect of childhood trauma. These findings are relevant for understanding the occurrence of psychopathology following childhood unpredictability and have implications for intervention.

Characteristic changes in the asymmetric nature of the human brain are associated with neurodevelopmental differences related to autism. In people with autism, these differences are thought to affect brain structure and function, although the structural and functional bases of these defects are yet to be fully characterized.

We applied a comprehensive meta-analysis to resting-state functional and structural magnetic resonance imaging datasets from 370 people with autism and 498 non-autistic controls using seven datasets of the Autism Brain Imaging Data Exchange Project. We studied the meta-effect sizes based on standardized mean differences and standard deviations (s.d.) for lateralization of gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo). We examined the functional correlates of atypical laterality through an indirect annotation approach followed by a direct correlation analysis with symptom scores.

In people with autism, 85, 51, and 51% of brain regions showed a significant diagnostic effect for lateralization in GMV, fALFF, and ReHo, respectively. Among these regions, 35.7% showed overlapping differences in lateralization in GMV, fALFF, and ReHo, particularly in regions with functional annotations for language, motor, and perceptual functions. These differences were associated with clinical measures of reciprocal social interaction, communication, and repetitive behaviors. A meta-analysis based on s.d. showed that people with autism had lower variability in structural lateralization but higher variability in functional lateralization.

These findings highlight that atypical hemispheric lateralization is a consistent feature in autism across different sites and may be used as a neurobiological marker for autism.

Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.

T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.

As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.

In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Functional impairment in daily activity is a cornerstone in distinguishing the clinical progression of dementia. Multiple indicators based on neuroimaging and neuropsychological instruments are used to assess the levels of impairment and disease severity; however, it remains unclear how multivariate patterns of predictors uniquely predict the functional ability and how the relative importance of various predictors differs.

In this study, 881 older adults with subjective cognitive complaints, mild cognitive impairment (MCI), and dementia with Alzheimer’s type completed brain structural magnetic resonance imaging (MRI), neuropsychological assessment, and a survey of instrumental activities of daily living (IADL). We utilized the partial least square (PLS) method to identify latent components that are predictive of IADL.

The result showed distinct brain components (gray matter density of cerebellar, medial temporal, subcortical, limbic, and default network regions) and cognitive–behavioral components (general cognitive abilities, processing speed, and executive function, episodic memory, and neuropsychiatric symptoms) were predictive of IADL. Subsequent path analysis showed that the effect of brain structural components on IADL was largely mediated by cognitive and behavioral components. When comparing hierarchical regression models, the brain structural measures minimally added the explanatory power of cognitive and behavioral measures on IADL.

Our finding suggests that cerebellar structure and orbitofrontal cortex, alongside with medial temporal lobe, play an important role in the maintenance of functional status in older adults with or without dementia. Moreover, the significance of brain structural volume affects real-life functional activities via disruptions in multiple cognitive and behavioral functions.

Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain regions may be impacted by trauma as well, and effects may be independent of diagnosis. This cross-sectional study investigated cortical and subcortical gray matter volume in relation to childhood trauma severity.

We included 554 participants: 250 bipolar-I patients, 84 schizophrenia-spectrum patients and 220 healthy individuals without a psychiatric history. Participants filled in the Childhood Trauma Questionnaire. Anatomical T1 MRI scans were acquired at 3T, regional brain morphology was assessed using Freesurfer.

In the total sample, trauma-related gray matter reductions were found in the frontal lobe (β = −0.049, p = 0.008; q = 0.048), this effect was driven by the right medial orbitofrontal, paracentral, superior frontal regions and the left precentral region. No trauma-related volume reductions were observed in any other (sub)cortical lobes nor the hippocampus or amygdala, trauma-by-group (i.e. both patient groups and healthy subjects) interaction effects were absent. A categorical approach confirmed a pattern of more pronounced frontal gray matter reductions in individuals reporting multiple forms of trauma and across quartiles of cumulative trauma scores. Similar dose−response patterns were revealed within the bipolar and healthy subgroups, but did not reach significance in schizophrenia-spectrum patients.

Findings show that childhood trauma is linked to frontal gray matter reductions, independent of psychiatric morbidity. Our results indicate that childhood trauma importantly contributes to the neurobiological changes commonly observed across psychiatric disorders. Frontal volume alterations may underpin affective and cognitive disturbances observed in trauma-exposed individuals.

Clinical high-risk (CHR) for psychosis is indicated by ultra-high risk (UHR) and basic symptom (BS) criteria; however, conversion rates are highest when both UHR and BS criteria are fulfilled (UHR&BS). While BSs are considered the most immediate expression of neurobiological aberrations underlying the development of psychosis, research on neurobiological correlates of BS is scarce.

We investigated gray matter volumes (GMV) of 20 regions of interest (ROI) previously associated with UHR criteria in 90 patients from the Bern early detection service: clinical controls (CC), first-episode psychosis (FEP), UHR, BS and UHR&BS. We expected lowest GMV in FEP and UHR&BS, and highest volume in CC with UHR and BS in-between.

Significantly, lower GMV was detected in FEP and UHR&BS patients relative to CC with no other significant between-group differences. When ROIs were analyzed separately, seven showed a significant group effect (FDR corrected), with five (inferior parietal, medial orbitofrontal, lateral occipital, middle temporal, precuneus) showing significantly lower GM volume in the FEP and/or UHR&BS groups than in the CC group (Bonferroni corrected). In the CHR group, only COGDIS scores correlated negatively with cortical volumes.

This is the first study to demonstrate that patients who fulfill both UHR and BS criteria – a population that has been associated with higher conversion rates – exhibit more severe GMV reductions relative to those who satisfy BS or UHR criteria alone. This result was mediated by the BS in the UHR&BS group, as only the severity of BS was linked to GMV reductions.

We investigated if alterations in higher-order association areas related to schizophrenia, namely the heteromodal association cortex (HASC), are also observable in subjects with autism spectrum disorder (ASD).

A group of 18 children with ASD and 18 healthy controls (HC) underwent magnetic resonance imaging (MRI). The examination comprised an analysis of group differences in gray matter (GM) volume, surface area (SA) and hemispheric lateralization.

Differences in GM volumes in children with ASD and HC were detected in frontal and parietal areas related to the HASC. No HASC structure that showed changes in GM volume exhibited differences in SA. Alterations in hemispheric lateralization between ASD and HC are seen in a frontal area of the HASC.

Our results indicate that changes in HASC areas are not restricted to schizophrenia, but extend to other psychiatric disorders, namely ASD. The lacking group differences in SA indicate that changes in GM volume are possibly evoked by other variables than SA in children with ASD.

Social anxiety disorder (SAD) is a prevalent mental disorder diagnosed in childhood and adolescence. Theories regarding brain development and SAD suggest a close link between neurodevelopmental dysfunction at the adolescent juncture and SAD, but direct evidence is rare. This study aims to examine brain structural abnormalities in adolescents with SAD.

High-resolution T1-weighted images were obtained from 31 adolescents with SAD (15–17 years) and 42 matching healthy controls (HC). We evaluated symptom severity with the Social Anxiety Scale for Children (SASC) and the Screen for Child Anxiety Related Emotional Disorders (SCARED). We used voxel-based morphometry analysis to detect regional gray matter volume abnormalities and structural co-variance analysis to investigate inter-regional coordination patterns.

We found significantly higher gray matter volume in the orbitofrontal cortex (OFC) and the insula in adolescents with SAD compared to HC. We also observed significant co-variance of the gray matter volume between the OFC and amygdala, and the OFC and insula in HC, but these co-variance relationships diminished in SAD.

These findings provide the first evidence that the brain structural deficits in adolescents with SAD are not only in the core regions of the fronto-limbic system, but also represented by the diminished coordination in the development of these regions. The delayed and unsynchronized development pattern of the fronto-limbic system supports SAD as an adolescent-sensitive developmental mental disorder.

The dopamine transporter gene (DAT1) and visual memory deficits have been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). This study aimed to examine whether a DAT1 haplotype affected functional and structural brain alterations in children with ADHD and whether those alterations were associated with visual memory.

We recruited a total of 37 drug-naïve children with ADHD (17 with the DAT1 rs27048 (C)/rs429699 (T) haplotype and 20 without the CT haplotype) and 37 typically developing children (17 with the CT haplotype and 20 without the CT haplotype). Visual memory was assessed by the pattern recognition memory (PRM) and spatial recognition memory (SRM) tasks. We analyzed functional and structural brain architecture with regional homogeneity (ReHo) and gray matter volume (GMV).

The CT haplotype was associated with decreased ReHo in the left superior occipital gyrus, cuneus, and precuneus; and decreased GMV in the left superior occipital gyrus, cuneus, and precuneus, and in the right angular gyrus. Significant interactions of ADHD and the CT haplotype were found in the right postcentral gyrus for ReHo and in the right supplementary motor area for GMV. For the ADHD-CT group, we found negative correlations of total correct responses in PRM and SRM and positive correlations of mean latency of correct responses in PRM with the GMV in the left superior occipital gyrus, cuneus, and precuneus.

Our findings suggest that the DAT1-related GMV alterations in the posterior cortical regions may contribute to visual memory performance in children with ADHD.

Cortical glutamatergic dysfunction is thought to be fundamental for psychosis development, and may lead to structural degeneration through excitotoxicity. Glutamate levels have been related to gray matter volume (GMV) alterations in people at ultra-high risk of psychosis, and we previously reported GMV changes in individuals with high schizotypy (HS), which refers to the expression of schizophrenia-like characteristics in healthy people. This study sought to examine whether GMV changes in HS subjects are related to glutamate levels.

We selected 22 healthy subjects with HS and 23 healthy subjects with low schizotypy (LS) based on their rating on a self-report questionnaire for psychotic-like experiences. Glutamate levels were measured in the bilateral anterior cingulate cortex (ACC) using proton magnetic resonance spectroscopy, and GMV was assessed using voxel-based morphometry.

Subjects with HS showed GMV decreases in the rolandic operculum/superior temporal gyrus (pFWE = 0.045). Significant increases in GMV were also detected in HS, in the precuneus (pFWE = 0.043), thereby replicating our previous finding in a separate cohort, as well as in the ACC (pFWE = 0.041). While the HS and LS groups did not differ in ACC glutamate levels, in HS subjects ACC glutamate was negatively correlated with ACC GMV (pFWE = 0.026). Such association was absent in LS.

Our study shows that GMV findings in schizotypy are related to glutamate levels, supporting the hypothesis that glutamatergic function may lead to structural changes associated with the expression of psychotic-like experiences.

Rumination is an important cognitive risk factor for onset and relapse of depression. However, no studies have employed a dimensional approach in investigating the neural correlates of rumination and the relationship with depression.

Non-clinical healthy subjects (n = 306), who completed the classical rumination and depression scales, were studied using voxel-based morphometry and regional homogeneity (ReHo). Subsequently, mediation analysis was conducted to examine the influence of rumination on the relationship between brain structure and depression. Moreover, depressive patients (n = 60) and a control group (n = 63) of comparable age and education were studied with regions of interest that were identified in the healthy individuals.

For healthy individuals, regional grey-matter volume (rGMV) of dorsolateral prefrontal cortex (DLPFC) and parahippocampal gyrus (PHG) were positively correlated with rumination. In addition, rumination had a mediating effect on the relationship between the DLPFC and PHG and depression. Moreover, ReHo analysis showed that rumination had a significantly negative correlation with functional homogeneity of DLPFC. However, compared to the control group, depressed patients showed significant decrease of rGMV in the DLPFC and PHG and there was a significant negative correlation between DLPFC volume and depressive rumination.

Increased DLPFC volume (decreased ReHo) in healthy individuals while decreased in depression indicated the trend of DLPFC from inefficient inhibition (‘overload state’) to impaired regulatory mechanism (‘paralysis state’). This finding might elucidate when and why healthy individuals would develop sustained negative mood and depression eventually.