Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.

To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.

We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.

We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.

These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

Although a large number of studies have shown brain volumetric differences between men and women, only a few investigations to date have analyzed brain tissue volumes in representative samples of the general elderly population.

We investigated differences in gray matter (GM), white matter (WM) and intracranial volumes (ICVs) between sexes in individuals above 66 years old using structural magnetic resonance imaging (MRI).

Using FreeSurfer version 5.3, we automatically obtained the ICVs, GM and WM volumes from MRI datasets of 84 men and 92 women. To correct for interindividual variations in ICV, GM and WM volumes were adjusted with a method using the residuals of a least-square-derived linear regression between raw volumes and ICVs. We then performed an ANCOVA comparing men and woman including age and years of schooling as confounding factors.

Women had a lower socioeconomic status overall and fewer years of schooling than men. The comparison of unadjusted brain volumes showed larger GM and WM volumes in men. After the ICV correction, the adjusted volumes of GM and WM were larger in women.

After the ICV correction and taking into account differences in socioeconomic status and years of schooling, our results confirm previous findings of proportionally larger GM in women, as well as larger WM volumes. These results in an elderly population indicate that brain volumetric differences between sexes persist throughout the aging process. Additional studies combining MRI and other biomarkers are warranted to identify the hormonal and molecular bases influencing such differences.

Sex-related differences in psychopathology are known phenomena, with externalizing and internalizing symptoms typically more common in boys and girls, respectively. However, the neural correlates of these sex-by-psychopathology interactions are underinvestigated, particularly in adolescence.

Participants were 14 years of age and part of the IMAGEN study, a large (N = 1526) community-based sample. To test for sex-by-psychopathology interactions in structural grey matter volume (GMV), we used whole-brain, voxel-wise neuroimaging analyses based on robust non-parametric methods. Psychopathological symptom data were derived from the Strengths and Difficulties Questionnaire (SDQ).

We found a sex-by-hyperactivity/inattention interaction in four brain clusters: right temporoparietal-opercular region (p < 0.01, Cohen's d = −0.24), bilateral anterior and mid-cingulum (p < 0.05, Cohen's d = −0.18), right cerebellum and fusiform (p < 0.05, Cohen's d = −0.20) and left frontal superior and middle gyri (p < 0.05, Cohen's d = −0.26). Higher symptoms of hyperactivity/inattention were associated with lower GMV in all four brain clusters in boys, and with higher GMV in the temporoparietal-opercular and cerebellar-fusiform clusters in girls.

Using a large, sex-balanced and community-based sample, our study lends support to the idea that externalizing symptoms of hyperactivity/inattention may be associated with different neural structures in male and female adolescents. The brain regions we report have been associated with a myriad of important cognitive functions, in particular, attention, cognitive and motor control, and timing, that are potentially relevant to understand the behavioural manifestations of hyperactive and inattentive symptoms. This study highlights the importance of considering sex in our efforts to uncover mechanisms underlying psychopathology during adolescence.

Dietary lipids (omega-3 polyunsaturated fatty acids (n-3) PUFAs) and saturated fatty acids (SFA) seem to play an important role in brain health. (n-3) PUFAs have been shown to improve cerebral perfusion and to promote synaptogenesis. In this study, we investigated the relationship between dietary fat composition, cognitive performance and brain morphology in cognitively healthy individuals.

A total of 101 cognitively healthy participants (age: 42.3 ± 21.3 years, 62 females) were included in this study. Verbal memory was assessed using the California Verbal Learning Test (CVLT). Intake of (n-3) PUFA and SFA was calculated from food-frequency questionnaire-derived data (EPIC-FFQ). Magnetic resonance imaging (MRI) data were obtained (Siemens Trio 3T scanner) and grey matter volumes (GMV) were assessed by voxel-based morphometry (VBM/SPM8). We examined the association of SFA/(n-3) PUFA ratio and memory performance as well as GMV using regression models adjusted for age, sex, education, body mass index, apolipoprotein E (APOE) status and alcohol consumption. For VBM data, a multiple regression analysis was performed using the same covariates as mentioned before with intracranial volume as an additional covariate.

A high SFA/(n-3) PUFA ratio was significantly (p < 0.05) correlated with poorer verbal memory performance and with lower GMV in areas of the left prefrontal cortex that support memory processes.

These findings suggest that a diet rich in PUFAs is likely to exert favourable effects on brain morphology in brain areas important for memory and executive functions. This could constitute a possible mechanism for maintaining cognitive health in older age.

Social and environmental factors such as poverty or violence modulate the risk and course of schizophrenia. However, how they affect the brain in patients with psychosis remains unclear.

We studied how environmental factors are related to brain structure in patients with schizophrenia and controls in Latin America, where these factors are large and unequally distributed.

This is a multicentre study of magnetic resonance imaging in patients with schizophrenia and controls from six Latin American cities. Total and voxel-level grey matter volumes, and their relationship with neighbourhood characteristics such as average income and homicide rates, were analysed with a general linear model.

A total of 334 patients with schizophrenia and 262 controls were included. Income was differentially related to total grey matter volume in both groups (P = 0.006). Controls showed a positive correlation between total grey matter volume and income (R = 0.14, P = 0.02). Surprisingly, this relationship was not present in patients with schizophrenia (R = −0.076, P = 0.17). Voxel-level analysis confirmed that this interaction was widespread across the cortex. After adjusting for global brain changes, income was positively related to prefrontal cortex volumes only in controls. Conversely, the hippocampus in patients with schizophrenia, but not in controls, was relatively larger in affluent environments. There was no significant correlation between environmental violence and brain structure.

Our results highlight the interplay between environment, particularly poverty, and individual characteristics in psychosis. This is particularly important for harsh environments such as low- and middle-income countries, where potentially less brain vulnerability (less grey matter loss) is sufficient to become unwell in adverse (poor) environments.

Whether borderline personality disorder (BPD) and bipolar disorder are the same or different disorders lacks consistency.

To detect whether grey matter volume (GMV) and grey matter density (GMD) alterations show any similarities or differences between BPD and bipolar disorder.

Web-based publication databases were searched to conduct a meta-analysis of all voxel-based studies that compared BPD or bipolar disorder with healthy controls. We included 13 BPD studies (395 patients with BPD and 415 healthy controls) and 47 bipolar disorder studies (2111 patients with bipolar disorder and 3261 healthy controls). Peak coordinates from clusters with significant group differences were extracted. Effect-size signed differential mapping meta-analysis was performed to analyse peak coordinates of clusters and thresholds (P < 0.005, uncorrected). Conjunction analyses identified regions in which disorders showed common patterns of volumetric alteration. Correlation analyses were also performed.

Patients with BPD showed decreased GMV and GMD in the bilateral medial prefrontal cortex network (mPFC), bilateral amygdala and right parahippocampal gyrus; patients with bipolar disorder showed decreased GMV and GMD in the bilateral medial orbital frontal cortex (mOFC), right insula and right thalamus, and increased GMV and GMD in the right putamen. Multi-modal analysis indicated smaller volumes in both disorders in clusters in the right medial orbital frontal cortex. Decreased bilateral mPFC in BPD was partly mediated by patient age. Increased GMV and GMD of the right putamen was positively correlated with Young Mania Rating Scale scores in bipolar disorder.

Our results show different patterns of GMV and GMD alteration and do not support the hypothesis that bipolar disorder and BPD are on the same affective spectrum.

None.

In patients with schizophrenia, distributed abnormalities are observed in grey matter volume. A recent hypothesis posits that these distributed changes are indicative of a plastic reorganisation process occurring in response to a functional defect in neuronal information transmission. We investigated the structural covariance across various brain regions in early-stage schizophrenia to determine if indeed the observed patterns of volumetric loss conform to a coordinated pattern of structural reorganisation.

Structural magnetic resonance imaging scans were obtained from 40 healthy adults and 41 age, gender and parental socioeconomic status matched patients with schizophrenia. Volumes of grey matter tissue were estimated at the regional level across 90 atlas-based parcellations. Group-level structural covariance was studied using a graph theoretical framework.

Patients had distributed reduction in grey matter volume, with high degree of localised covariance (clustering) compared with controls. Patients with schizophrenia had reduced centrality of anterior cingulate and insula but increased centrality of the fusiform cortex, compared with controls. Simulating targeted removal of highly central nodes resulted in significant loss of the overall covariance patterns in patients compared with controls.

Regional volumetric deficits in schizophrenia are not a result of random, mutually independent processes. Our observations support the occurrence of a spatially interconnected reorganisation with the systematic de-escalation of conventional ‘hub’ regions. This raises the question of whether the morphological architecture in schizophrenia is primed for compensatory functions, albeit with a high risk of inefficiency.

Patients with 22q11.2 deletion syndrome (22q11DS) present a high risk of developing psychosis. While clinical and cognitive predictors for the conversion towards a full-blown psychotic disorder are well defined and largely used in practice, neural biomarkers do not yet exist. However, a number of investigations indicated an association between abnormalities in cortical morphology and higher symptoms severities in patients with 22q11DS. Nevertheless, few studies included homogeneous groups of patients differing in their psychotic symptoms profile.

In this study, we included 22 patients meeting the criteria for an ultra-high-risk (UHR) psychotic state and 22 age-, gender- and IQ-matched non-UHR patients. Measures of cortical morphology, including cortical thickness, volume, surface area and gyrification, were compared between the two groups using mass-univariate and multivariate comparisons. Furthermore, the development of these measures was tested in the two groups using a mixed-model approach.

Our results showed differences in cortical volume and surface area in UHR patients compared with non-UHR. In particular, we found a positive association between surface area and the rate of change of global functioning, suggesting that higher surface area is predictive of improved functioning with age. We also observed accelerated cortical thinning during adolescence in UHR patients with 22q11DS.

These results, although preliminary, suggest that alterations in cortical volume and surface area as well as altered development of cortical thickness may be associated to a greater probability to develop psychosis in 22q11DS.

Because cerebral morphological abnormalities in major depressive disorder (MDD) may be modulated by antidepressant treatment, inclusion of medicated patients may have biased previous meta-analyses of voxel-based morphometry (VBM) studies. A meta-analysis of VBM studies on medication-free MDD patients should be able to distinguish the morphological features of the disease itself from those of treatment.

A systematic search was conducted for the relevant studies. Effect-size signed differential mapping was applied to analyse the grey matter differences between all medication-free MDD patients and healthy controls. Meta-regression was used to explore the effects of demographics and clinical characteristics.

A total of 14 datasets comprising 400 medication-free MDD patients and 424 healthy controls met the inclusion criteria. The pooled meta-analysis and subgroup meta-analyses showed robustly reduced grey matter in prefrontal and limbic regions in MDD. Increased right thalamus volume was only seen in first-episode medication-naive patients, and increased grey matter in the bilateral anterior cingulate cortex only in medication wash-out patients. In meta-regression analyses the percentage of female patients in each study was negatively correlated with reduced grey matter in the right hippocampus.

By excluding interference from medication effects, the present study identified grey matter reduction in the prefrontal–limbic network in MDD. The subgroup meta-analysis results suggest that an increased right thalamus volume might be a trait directly related to MDD, while an increased anterior cingulate cortex volume might be an effect of medication. The meta-regression results perhaps reveal the structural underpinning of the sex differences in epidemiological and clinical aspects of MDD.

Brain structure alterations have been reported in anorexia nervosa, but findings have been inconsistent. This may be due to inadequate sample size, sample heterogeneity or differences in methodology.

High resolution magnetic resonance images were acquired of 33 adult participants with anorexia nervosa and 33 healthy participants, the largest study sample to date, in order to assess whole-brain volume, ventricular cerebrospinal fluid, white matter and grey matter volume. Voxel-based morphometry was conducted to assess regional grey matter volume. Levels of depression, anxiety, obsessionality and eating disorder-related symptoms were measured and used to explore correlations with brain structure.

Participants with anorexia nervosa had smaller brain volumes as well as a global decrease in grey matter volume with ventricular enlargement. Voxel-based morphometry revealed a decrease in grey matter volume spanning across the cerebellum, temporal, frontal and occipital lobes. A correlation was found between grey matter volume loss and duration of illness in the cerebellum and mesencephalon. No correlations were found with clinical measures.

Findings are in accordance with several previous studies on brain structure and match functional studies that have assessed the symptomatology of anorexia nervosa, such as body image distortion and cognitive bias to food. The correlation with duration of illness supports the implication of cerebellar atrophy in the maintenance of low weight and disrupted eating behaviour and illustrates its role in the chronic phase of anorexia nervosa. The lack of other correlations suggests that these findings are not related to the presence of co-morbid disorders.

Recent evidence from genetic and familial studies revitalized the debate concerning the validity of the distinction between schizophrenia and bipolar disorder. Comparing brain imaging findings is an important avenue to examine similarities and differences and, therefore, the validity of the distinction between these conditions. However, in contrast to bipolar disorder, most patient samples in studies of schizophrenia are predominantly male. This a limiting factor for comparing schizophrenia and bipolar disorder since male gender is associated with more severe neurodevelopmental abnormalities, negative symptoms and cognitive deficits in schizophrenia.

We used a coordinate-based meta-analysis technique to compare grey matter (GM) abnormalities in male-dominated schizophrenia, gender-balanced schizophrenia and bipolar disorder samples based on published voxel-based morphometry (VBM) studies. In total, 72 English-language, peer reviewed articles published prior to January 2011 were included. All reports used VBM for comparing schizophrenia or bipolar disorder with controls and reported whole-brain analyses in standard stereotactic space.

GM reductions were more extensive in male-dominated schizophrenia compared to gender-balanced bipolar disorder and schizophrenia. In gender-balanced samples, GM reductions were less severe. Compared to controls, GM reductions were restricted to dorsal anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex in schizophrenia and ACC and bilateral fronto-insular cortex in bipolar disorder.

When gender is controlled, GM abnormalities in bipolar disorder and schizophrenia are mostly restricted to regions that have a role in emotional and cognitive aspects of salience respectively. Dorsomedial and dorsolateral prefrontal cortex were the only regions that showed greater GM reductions in schizophrenia compared to bipolar disorder.

Despite behavioural signs of flattened affect, patients affected by schizophrenia show enhanced sensitivity to negative stimuli. The current literature concerning neural circuitry for emotions supports dysregulations of cortico-limbic networks, but gives contrasting results. Adverse childhood experiences (ACEs) could persistently influence emotional regulation and neural correlates of response to emotional stimuli in healthy humans. This study evaluated the effect of ACEs and chronic undifferentiated schizophrenia on neural responses to emotional stimuli (negative facial expression).

Brain blood-oxygen-level-dependent functional magnetic resonance imaging neural responses to a face-matching paradigm, and regional grey matter (GM) volumes were studied at 3.0 T in the amygdala, hippocampus, anterior cingulated cortex (ACC) and prefrontal cortex (PFC). The severity of ACEs was assessed. Participants included 20 consecutively admitted in-patients affected by chronic undifferentiated schizophrenia, and 20 unrelated healthy volunteers from the general population.

Patients reported higher ACEs than controls. Worse ACEs proportionally led to decreasing responses in the amygdala and hippocampus, and to increasing responses in the PFC and ACC in all participants. Patients showed higher activations in the amygdala and hippocampus, and lower activations in the PFC and ACC. Higher ACEs were associated with higher GM volumes in the PFC and ACC, and schizophrenia was associated with GM reduction in all studied regions.

Structural and functional brain correlates of emotional reactivity are influenced by both current chronic undifferentiated schizophrenia and the severity of past ACEs.