Apart from the psychiatric symptoms, cognitive deficits are also the core symptoms of schizophrenia. Brain network control theory provided information on the role of a specific brain region in the cognitive control process, helping understand the neural mechanism of cognitive impairment in schizophrenia.

To characterize the control properties of functional brain network in first-episode untreated patients with schizophrenia and the relationships between controllability and psychiatric symptoms, as well as exploring the predictive value of controllability in differentiating patients from healthy controls (HCs).

Average and modal controllability of brain networks were calculated and compared between 133 first-episode untreated patients with schizophrenia and 135 HCs. The associations between controllability and clinical symptoms were evaluated using sparse canonical correlation analysis. Support vector machine (SVM) and SVM-recursive feature elimination combined with the controllability were performed to establish the individual prediction model.

Compared to HCs, the patients with schizophrenia showed increased average controllability and decreased modal controllability in dorsal anterior cingulate cortex (dACC). Brain controllability predominantly in somatomotor, default mode, and visual networks was associated with the positive symptomatology of schizophrenia. The established model could identify patients with an accuracy of 0.68. Furthermore, the most discriminative features were located in dACC, medial prefrontal lobe, precuneus and superior temporal gyrus.

Altered controllability in dACC may play a critical role in the neuropathological mechanisms of cognitive deficit in schizophrenia, which could drive the brain function to different states to cope with varied cognitive tasks. As symptom-related biomarkers, controllability could be also beneficial to individual prediction in schizophrenia.

No significant relationships.

There is a growing consensus on brain networks that it is not immutable but rather a dynamic complex system for adapting environment. The neuroimaging research studying how brain regions work collaboratively with dynamic methods had demonstrated its effectiveness in revealing the neural mechanisms of schizophrenia.

To investigate altered dynamic brain functional topology in first-episode untreated schizophrenia patients (SZs) and establish classification models to find objective brain imaging biomarkers.

Resting-state-functional magnetic resonance data for SZs and matched healthy controls were obtained(Table1).

Power-264-template was used to extract nodes and sliding-window approach was carried out to establish functional connectivity matrices. Functional topology was assessed by eigenvector centrality(EC) and node efficiency and its time-fluctuating was evaluated with coefficient of variation(CV). Group differences of dynamic topology and correlation analysis between Positive and Negative Syndrome Scale(PANSS) scores and topology indices showing group differences, which also were used in establishing classification models, was examed.

The CV of node efficiency in angular and paracingulate gyrus was larger in SZs. There are 13 nodes assigned into several brain networks displaying altered CV of EC between groups(Figure1.A). Fluctuation of EC of the node in DMN, which was lower in SZs, showed negative correlation with PANSS total scores(Figure1.B). Dynamic functional topology of above nodes was used to train classification models and demonstrated 80% and 71% accuracy for support vector classification(SVC) and random forest(RF), respectively(Figure2).

Dynamic functional topology illustrated a capability in identifying SZs. Aberrated dynamics of DMN relevant to severity of patient’s symptoms could reveal the reason why it contributed to classification.

No significant relationships.

The coronavirus disease 2019 (COVID-19) pandemic represents an unprecedented threat to mental health. Herein, we assessed the impact of COVID-19 on subthreshold depressive symptoms and identified potential mitigating factors.

Participants were from Depression Cohort in China (ChiCTR registry number 1900022145). Adults (n = 1722) with subthreshold depressive symptoms were enrolled between March and October 2019 in a 6-month, community-based interventional study that aimed to prevent clinical depression using psychoeducation. A total of 1506 participants completed the study in Shenzhen, China: 726 participants, who completed the study between March 2019 and January 2020 (i.e. before COVID-19), comprised the ‘wave 1’ group; 780 participants, who were enrolled before COVID-19 and completed the 6-month endpoint assessment during COVID-19, comprised ‘wave 2’. Symptoms of depression, anxiety and insomnia were assessed at baseline and endpoint (i.e. 6-month follow-up) using the Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder-7 (GAD-7) and Insomnia Severity Index (ISI), respectively. Measures of resilience and regular exercise were assessed at baseline. We compared the mental health outcomes between wave 1 and wave 2 groups. We additionally investigated how mental health outcomes changed across disparate stages of the COVID-19 pandemic in China, i.e. peak (7–13 February), post-peak (14–27 February), remission plateau (28 February−present).

COVID-19 increased the risk for three mental outcomes: (1) depression (odds ratio [OR] = 1.30, 95% confidence interval [CI]: 1.04–1.62); (2) anxiety (OR = 1.47, 95% CI: 1.16–1.88) and (3) insomnia (OR = 1.37, 95% CI: 1.07–1.77). The highest proportion of probable depression and anxiety was observed post-peak, with 52.9% and 41.4%, respectively. Greater baseline resilience scores had a protective effect on the three main outcomes (depression: OR = 0.26, 95% CI: 0.19–0.37; anxiety: OR = 1.22, 95% CI: 0.14–0.33 and insomnia: OR = 0.18, 95% CI: 0.11–0.28). Furthermore, regular physical activity mitigated the risk for depression (OR = 0.79, 95% CI: 0.79–0.99).

The COVID-19 pandemic exerted a highly significant and negative impact on symptoms of depression, anxiety and insomnia. Mental health outcomes fluctuated as a function of the duration of the pandemic and were alleviated to some extent with the observed decline in community-based transmission. Augmenting resiliency and regular exercise provide an opportunity to mitigate the risk for mental health symptoms during this severe public health crisis.

White matter abnormalities have been repeatedly reported in both schizophrenia and bipolar disorder (BD) diseases from diffusion tensor imaging (DTI) studies respectively, while the empirical evidences about the diagnostic specificity of white matter abnormalities in these disorders are still limited.

25 patients with paranoid schizophrenia and 18 patients with bipolar mania were recruited from the in-patient unit of the Mental Health Centre, West China Hospital, China.

Patients were diagnosed according to the criteria of Diagnostic and Statistical Manual of Mental Disorders-Version IV (DSM- IV). 30 healthy controls were recruited from the community by means of leaflets distributed throughout Chengdu city.

This study sought to investigate the alterations in fractional anisotropy (FA) in white matter throughout the entire brain of patients from Chengdu, China with paranoid schizophrenia and bipolar mania.

Diffusion tensor imaging (DTI) was used to assess white matter integrity in patients with paranoid schizophrenia and bipolar mania, as well as in normal controls. The differences in FA were measured by use of voxel-based analysis.

Reduced FA was found in the left posterior corona radiate (PCR) in patients with bipolar mania and paranoid schizophrenia compared to the controls. Patients with bipolar mania also showed a significant reduction in FA in right posterior corona radiate and in right anterior thalamic radiation (ATR).

Common abnormalities in the left PCR might imply an overlap in white matter pathology of both diseases and might be related to the shared risk factors for both disorders.

Although the deviations of brain volume deficits in sporadic and familial first-episode schizophrenia patients (FEP) had been presented, the difference of brain asymmetries remained unidentified.

To assess the potential differences of volumetric asymmetries of gray matter (GM) and white matter (WM) between groups.

To find out the different injury alteration of sporadic FEP and familial FEP.

42 sporadic and 30 familiar drug-naïve FEP with and 72 matched normal controls (NC) were recruited. Participants were assessed with neuropsychological tests and scanned by a 3.0T MRI to obtain T1-weighted and DTI images. Lateralization distribution maps of GM and WM volume were generated by employing optimized voxel-based morphometry. The asymmetries were analyzed by comparing calculating Laterality Index (LI) voxel by voxel.

All three groups showed similar overall brain torque. Familiar FEP have more regional extensive GM asymmetry brain lesions compared to sporadic FEP. There was no shared regional lesion between two groups. LIGM and LIWM in right superior temporal were negatively correlated. Significant negative correlations were also found between LIGM of left superior parietal lobule and LIWM of right superior parietal lobule, and between LIGM of right inferior parietal lobule and LIWM of left inferior parietal lobule. The asymmetry in distinct brain regions were related to cognitive deficits especially in the domains of language and memory.

The two patient groups had different alteration in injuries of brain asymmetry. Familiar FEP has more GM extensive asymmetry brain region, which may correlate with their high genetic burdens.

Alterations in gray matter (GM) are commonly observed in schizophrenia. Accumulating studies suggest that the brain changes associated with schizophrenia are distributed rather than focal, involving interconnected networks of areas as opposed to single regions. In the current study we aimed to explore GM volume (GMV) changes in a relatively large sample of treatment-naive first-episode schizophrenia (FES) patients using optimized voxel-based morphometry (VBM) and covariation analysis.

High-resolution T1-weighted images were obtained using 3.0-T magnetic resonance imaging (MRI) from 86 first-episode drug-naive patients with schizophrenia and 86 age- and gender-matched healthy volunteers. Symptom severity was evaluated using the Positive and Negative Syndrome Scale (PANSS). GMV was assessed using optimized VBM and in 16 regions of interest (ROIs), selected on the basis of a previous meta-analysis. The relationships between GMVs in the ROIs were examined using an analysis of covariance (ANCOVA).

The VBM analysis revealed that first-episode patients showed reduced GMV in the hippocampus bilaterally. The ROI analysis identified reductions in GMV in the left inferior frontal gyrus, bilateral hippocampus and right thalamus. The ANCOVA revealed different patterns of regional GMV correlations in patients and controls, including of inter- and intra-insula, inter-amygdala and insula–postcentral gyrus connections.

Schizophrenia involves regional reductions in GMV and changes in GMV covariance in the insula, amygdala and postcentral gyrus. These findings were evident at the onset of the disorder, before treatment, and therefore cannot be attributable to the effects of chronic illness progression or medication.

At present there are no objective, biological markers that can be used to reliably identify individuals with post-traumatic stress disorder (PTSD). This study assessed the diagnostic potential of structural magnetic resonance imaging (sMRI) for identifying trauma-exposed individuals with and without PTSD.

sMRI scans were acquired from 50 survivors of the Sichuan earthquake of 2008 who had developed PTSD, 50 survivors who had not developed PTSD and 40 healthy controls who had not been exposed to the earthquake. Support vector machine (SVM), a multivariate pattern recognition technique, was used to develop an algorithm that distinguished between the three groups at an individual level. The accuracy of the algorithm and its statistical significance were estimated using leave-one-out cross-validation and permutation testing.

When survivors with PTSD were compared against healthy controls, both grey and white matter allowed discrimination with an accuracy of 91% (p < 0.001). When survivors without PTSD were compared against healthy controls, the two groups could be discriminated with accuracies of 76% (p < 0.001) and 85% (p < 0.001) based on grey and white matter, respectively. Finally, when survivors with and without PTSD were compared directly, grey matter allowed discrimination with an accuracy of 67% (p < 0.001); in contrast the two groups could not be distinguished based on white matter.

These results reveal patterns of neuroanatomical alterations that could be used to inform the identification of trauma survivors with and without PTSD at the individual level, and provide preliminary support to the development of SVM as a clinically useful diagnostic aid.

It is not clear whether the progressive changes in brain microstructural deficits documented in previous longitudinal magnetic resonance imaging (MRI) studies might be due to the disease process or to other factors such as medication. It is important to explore the longitudinal alterations in white-matter (WM) microstructure in antipsychotic-naive patients with first-episode schizophrenia during the very early phase of treatment when relatively ‘free’ from chronicity.

Thirty-five patients with first-episode schizophrenia and 22 healthy volunteers were recruited. High-resolution diffusion tensor imaging (DTI) was obtained from participants at baseline and after 6 weeks of treatment. A ‘difference map’ for each individual was calculated from the 6-week follow-up fractional anisotropy (FA) of DTI minus the baseline FA. Differences in Positive and Negative Syndrome Scale (PANSS) scores and Global Assessment of Functioning (GAF) scores between baseline and 6 weeks were also evaluated and expressed as a 6-week/baseline ratio.

Compared to healthy controls, there was a significant decrease in absolute FA of WM around the bilateral anterior cingulate gyrus and the right anterior corona radiata of the frontal lobe in first-episode drug-naive patients with schizophrenia following 6 weeks of treatment. Clinical symptoms improved during this period but the change in FA did not correlate with the changes in clinical symptoms or the dose of antipsychotic medication.

During the early phase of treatment, there is an acute reduction in WM FA that may be due to the effects of antipsychotic medications. However, it is not possible to entirely exclude the effects of underlying progression of illness.

Evidence shows that cognitive deficits and white matter (WM) dysconnectivity can independently be associated with clinical manifestations in schizophrenia. It is important to explore this triadic relationship in order to investigate whether the triplet could serve as potential extended endophenotypes of schizophrenia.

Diffusion tensor images and clinical performances were evaluated in 122 individuals with first-episode schizophrenia and 122 age- and gender-matched controls. In addition, 65 of 122 of the patient group and 40 of 122 controls were measured using intelligence quotient (IQ) testing.

The schizophrenia group showed lower fractional anisotropy (FA) values than controls in the right cerebral frontal lobar sub-gyral (RFSG) WM. The schizophrenia group also showed a significant positive correlation between FA in the RFSG and performance IQ (PIQ); in turn, their PIQ score showed a significant negative correlation with negative syndromes.

Overall, these findings support the hypothesis that WM deficits may be a core deficit that contributes to cognitive deficits as well as to negative symptoms.

Given the important role of the default mode network (DMN) in cognitive function and the well-known neurocognitive deficit in schizophrenia, it is intriguing to examine systematically the relationship between neurocognitive dysfunction and aberrant intrinsic activities, and also functional connectivity, of the DMN in patients with schizophrenia.

First-episode, treatment-naive patients with schizophrenia (FES) (n = 115) and healthy controls (n = 113) underwent resting-state functional magnetic resonance imaging (fMRI) scans and neurocognitive tests. Intrinsic neural activities evaluated by using the fragment amplitude of low-frequency fluctuations (fALFF) and the resting-state functional connectivity assessed by seed-based correlational analysis were compared between patients and controls. Aberrant intrinsic activities and DMN connectivity in patients were then correlated to neurocognitive performance and clinical symptoms.

Compared to controls, patients with FES showed decreased fALFF in the bilateral medial prefrontal cortex (MPFC) and the orbitofrontal cortex (OFC), and increased fALFF in the bilateral putamen. Increased functional connectivity with the DMN was observed in the left insula and bilateral dorsolateral PFC (DLPFC) in patients with FES. In patients, aberrant fALFF in the bilateral OFC were correlated with cognitive processing speed; fALFF in the left OFC and right putamen were correlated with the clinical factors excited/activation and disorganization; and increased DMN functional connectivity in the left insula was correlated with the clinical factors positive, excited/activation, disorganization and neurocognitive deficit in the domain of sustained attention.

These associations between neurocognitive dysfunction and aberrant intrinsic activities, and also functional connectivity, of the DMN in patients with schizophrenia may provide important insights into the neural mechanism of the disease.

Brain structure appears to alter after antipsychotic administration, but it is unknown whether these alterations are associated with improvement of psychopathology in patients with schizophrenia. In this study, the authors explore this relationship.

Altogether, 66 first-episode, drug-naive patients with schizophrenia and 23 well-matched healthy controls underwent brain magnetic resonance imaging scans at baseline. All 23 healthy controls and 42 of the patients were rescanned after 6 weeks follow-up. The patients received regular antipsychotic treatment during the 6-week period and their psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and 6 weeks. The difference in PANSS scores between baseline and 6 weeks was expressed as a ratio of the scores at baseline – ‘PANSS reduction ratio’. A modified tensor-based morphometry procedure was applied to analyse longitudinal images. Correlations between regional volume changes, PANSS reduction ratio and antipsychotic drug dosages were explored.

Compared with healthy controls, there was a significant increase in grey-matter volume of the right putamen in patients after 6 weeks treatment. This volume change was positively correlated with a positive PANSS reduction score but not related to drug dosages.

Putaminal volume increased after 6 weeks antipsychotic treatment in first-episode schizophrenia. The increased volume was closely correlated with improved psychopathology, suggesting the putamen might be a biomarker to predict the treatment response in schizophrenia.

Abnormalities in the connectivity of white-matter (WM) tracts in schizophrenia are supported by evidence from post-mortem investigations, functional and structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). The aims of this study were to explore the microstructural changes in first-episode schizophrenia in a Han Chinese population and to investigate whether a family history of psychiatric disorder is related to the severity of WM tract integrity abnormalities in these patients.

T1-weighted MR and DT images were collected in 68 patients with first-episode schizophrenia [22 with a positive family history (PFH) and 46 with a negative family history (NFH)] and 100 healthy controls. Voxel-based analysis was performed and WM integrity was quantified by fractional anisotropy (FA). Cluster- and voxel-level analyses were performed by using two-sample t tests between patients and controls and/or using a full factorial model with one factor and three levels among the three sample groups (patients with PFH or NFH, and controls), as appropriate.

FA deficits were observed in the patient group, especially in the left temporal lobe and right corpus callosum. This effect was more severe in the non-familial schizophrenia than in the familial schizophrenia subgroup.

Overall, these findings support the hypothesis that loss of WM integrity may be an important pathophysiological feature of schizophrenia, with particular implications for brain dysmaturation in non-familial and familial schizophrenia.