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Background: Structural and functional neurobiological abnormalities have been observed in schizophrenia. Previous studies have concentrated on specific illness stages, obscuring relationships between functional/structural changes and disorder progression. The present study aimed to quantify structural and functional abnormalities across different clinical stages using functional near-infrared spectroscopy (fNIRS) and structural magnetic resonance imaging (sMRI)., Methods: Fifty-four participants with first-episode schizophrenia (FES), 120 with clinically high risk of psychosis (CHR), and 111 healthy controls (HCs) underwent functional near-infrared spectroscopy (fNIRS) to measure oxyhemoglobin (Oxy-Hb) during the verbal fluency task. Among them, 28FES, 64CHR and 55HC also finished sMRI. Oxy-Hb and gray matter volume (GMV) were compared among the three groups while controlling for covariates, including age, sex, years of education, and task performance. Mediation analysis was utilized to determine the mediating effect of GMV on Oxy-Hb and cognition., Results: Compared with the HC group, CHR and FES groups showed significantly reduced brain activity. However, there were no significant differences between the FES and CHR. Pronounced GMV increase in the right frontal pole area (F = 4.234, p = 0.016) was identified in the CHR and FES groups. Mediation analysis showed a significant mediation effect of the right frontal pole GMV between Channel 31 Oxy-Hb and processing speed (z = 2.105, p = 0.035) and attention/vigilance (z = 1.992, p = 0.046)., Conclusions: Brain activation and anatomical deficits were observed in different brain regions, suggesting that anatomical and functional abnormalities are dissociated in the early stages of psychosis. The relationship between neural activity and anatomy may reflect a specific pathophysiology related to cognitive deterioration in schizophrenia., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Thalamic abnormalities in schizophrenia are recognized, alongside cognitive deficits. However, the current findings about these abnormalities during the prodromal period remain relatively few and inconsistent. This study applied multimodal methods to explore the alterations in thalamic function and structure and their relationship with cognitive function in first-episode schizophrenia (FES) patients and ultra-high-risk (UHR) individuals, aiming to affirm the thalamus's role in schizophrenia development and cognitive deficits., Methods: 75 FES patients, 60 UHR individuals, and 60 healthy controls (HC) were recruited. Among the three groups, gray matter volume (GMV) and functional connectivity (FC) were evaluated to reflect the structural and functional abnormalities in the thalamus. Pearson correlation was used to calculate the association between these abnormalities and cognitive impairments., Results: No significant difference in GMV of the thalamus was found among the abovementioned three groups. Compared with HC individuals, FES patients had decreased thalamocortical FC mostly in the thalamocortical triple network, including the default mode network (DMN), salience network (SN), and executive control network (ECN). UHR individuals had similar but milder dysconnectivity as the FES group. Furthermore, FC between the left thalamus and right putamen was significantly correlated with execution speed and attention in the FES group., Conclusions: Our findings revealed decreased thalamocortical FC associated with cognitive deficits in FES and UHR subjects. This improves our understanding of the functional alterations in thalamus in prodromal stage of schizophrenia and the related factors of the cognitive impairment of the disease., Trial Registration: ClinicalTrials.govNCT03965598; https://clinicaltrials.gov/ct2/show/NCT03965598., Competing Interests: Declaration of competing interest All authors declare that they have no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aim: While conservatism bias refers to the human need for more evidence for decision-making than rational thinking expects, the jumping to conclusions (JTC) bias refers to the need for less evidence among individuals with schizophrenia/delusion compared to healthy people. Although the hippocampus-midbrain-striatal aberrant salience system and the salience, default mode (DMN), and frontoparietal networks ("triple networks") are implicated in delusion/schizophrenia pathophysiology, the associations between conservatism/JTC and these systems/networks are unclear., Methods: Thirty-seven patients with schizophrenia and 33 healthy controls performed the beads task, with large and small numbers of bead draws to decision (DTD) indicating conservatism and JTC, respectively. We performed independent component analysis (ICA) of resting functional magnetic resonance imaging (fMRI) data. For systems/networks above, we investigated interactions between diagnosis and DTD, and main effects of DTD. We similarly applied ICA to structural and diffusion MRI to explore the associations between DTD and gray/white matter., Results: We identified a significant main effect of DTD with functional connectivity between the striatum and DMN, which was negatively correlated with delusion severity in patients, indicating that the greater the anti-correlation between these networks, the stronger the JTC and delusion. We further observed the main effects of DTD on a gray matter network resembling the DMN, and a white matter network connecting the functional and gray matter networks (all P < 0.05, family-wise error [FWE] correction). Function and gray/white matter showed no significant interactions., Conclusion: Our results support the novel association of conservatism and JTC biases with aberrant salience and default brain mode., (© 2024 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

Aim: Identify grey- and white-matter-specific DNA-methylation differences between schizophrenia (SCZ) patients and controls in postmortem brain cortical tissue. Materials & methods: Grey and white matter were separated from postmortem brain tissue of the superior temporal and medial frontal gyrus from SCZ (n = 10) and control (n = 11) cases. Genome-wide DNA-methylation analysis was performed using the Infinium EPIC Methylation Array (Illumina, CA, USA). Results: Four differentially methylated regions associated with SCZ status and tissue type (grey vs white matter) were identified within or near KLF9 , SFXN1 , SPRED2 and ALS2CL genes. Gene-expression analysis showed differential expression of KLF9 and SFXN1 in SCZ. Conclusion: Our data show distinct differences in DNA methylation between grey and white matter that are unique to SCZ, providing new leads to unravel the pathogenesis of SCZ.

It is becoming clearer that the impact of brain diseases is more convincingly represented in terms of co-alterations rather than in terms of localization of alterations. In this context, areas characterized by a long mean distance of co-alteration may be considered as hubs with a crucial role in the pathology. We calculated meta-analytic transdiagnostic networks of co-alteration for the gray matter decreases and increases, and we evaluated the mean Euclidean, fiber-length, and topological distance of its nodes. We also examined the proportion of co-alterations between canonical networks, and the transdiagnostic variance of the Euclidean distance. Furthermore, disease-specific analyses were conducted on schizophrenia and Alzheimer's disease. The anterodorsal prefrontal cortices appeared to be a transdiagnostic hub of long-distance co-alterations. Also, the disease-specific analyses showed that long-distance co-alterations are more able than classic meta-analyses to identify areas involved in pathology and symptomatology. Moreover, the distance maps were correlated with the normative connectivity. Our findings substantiate the network degeneration hypothesis in brain pathology. At the same time, they suggest that the concept of co-alteration might be a useful tool for clinical neuroscience., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1-year follow-up was assessed in 30 individuals with a schizophrenia-spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all individuals at baseline. Machine learning classifiers were trained to predict whether individuals improved or worsened with respect to positive, negative, and overall symptom severity. Classifiers were trained using various combinations of predictors, including regional cortical thickness and gray matter volume, static and dynamic resting-state connectivity, and/or baseline clinical and demographic variables. Relative change in overall symptom severity between baseline and 1-year follow-up varied markedly among individuals (interquartile range: 55%). Dynamic resting-state connectivity measured within the default-mode network was the most accurate single predictor of change in positive (accuracy: 87%), negative (83%), and overall symptom severity (77%) at follow-up. Incorporating predictors based on regional cortical thickness, gray matter volume, and baseline clinical variables did not markedly improve prediction accuracy and the prognostic utility of these predictors in isolation was moderate (<70%). Worsening negative symptoms at 1-year follow-up were predicted by hyper-connectivity and hypo-dynamism within the default-mode network at baseline assessment, while hypo-connectivity and hyper-dynamism predicted worsening positive symptoms. Given the modest sample size investigated, we recommend giving precedence to the relative ranking of the predictors investigated in this study, rather than the prediction accuracy estimates., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Background: Depressive symptoms and auditory hallucinations (AHs) are often accompanied by gray matter volume (GMV) alterations in schizophrenia. However, little is known about the effects of concurrent depressive symptoms and AHs on the GMV of patients with schizophrenia., Aim: To investigate the pathological features of gray brain matter in patients with first-episode untreated schizophrenia (FUSCH) who have concurrent moderate-to-severe depressive symptoms and AHs (FUSCH-DAH)., Methods: The Calgary Depression Scale for Schizophrenia (CDSS) and Auditory Hallucinations Rating Scale (AHRS) were adopted. Voxel-based morphometry (VBM)-based GMV analyses were used to measure cortical alterations. FUSCH-DAH patients were compared to FUSCH patients with depressive symptoms but without AHs, denoted as FUSCH-D, along with healthy controls., Results: GMV reductions were more substantial in the FUSCH-DAH patients than FUSCH-D patients or healthy controls. Both FUSCH-DAH and FUSCH-D groups showed GMV reductions of the parietal, frontal, and temporal lobes, which were not apparent in the healthy controls. Compared to FUSCH-D patients, FUSCH-DAH patients demonstrated more substantial GMV reductions in the Broca area, Wernicke region, insular lobe, and prefrontal lobe. The GMV reductions were 1.06% and 0.58% in FUSCH-DAH and FUSCH-D patients, respectively, as compared with the healthy controls., Conclusions: This is the first report showing that concurrent depressive symptoms and AHs leads to severe GMV deterioration in FUSCH-DAH patients. Hence, there is a reciprocal relationship between AHs and depressive symptoms in FUSCH-DAH patients. However, the potential additive effects of concurrent AHs and depressive symptoms require further investigation in order to identify future targeted therapies for schizophrenia., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Schizophrenia (SZ) and bipolar I disorder (BD) share common functional and structural brain abnormalities, as well as various degrees of social cognitive deficits, suggesting shared brain mechanisms. This study examined the relationship between social cognitive skills and structural brain integrity in 60 cases with SZ, 65 cases with psychotic BD, and 61 healthy controls (HCs). All participants underwent structural MRI and completed The Awareness of Social Inference Test (TASIT). Associations between social cognitive performance on each task of the TASIT (Emotion Recognition, Theory of Mind [ToM], and Complex ToM) and indices of gray matter volume and cortical thickness were investigated within three separate groups comprising (a) all cases with a history of psychosis (independently of their diagnostic status), (b) each diagnostic category separately, and (c) an HC group. Cases with psychosis showed worse social cognitive performance compared to the HC group, and SZ cases performed worse than BD on all ToM tasks, but not the Emotion Recognition subtest. Poor ToM performance was associated with thinner anterior temporal lobe in the combined group of cases with psychosis, and with decreased volume of the left fusiform gyrus/cerebellum in the HC group. In the BD group alone, poor ToM performance was associated with similar pattern of thinner anterior temporal lobe, as well as with increased volume in the mid- and posterior cingulate cortex/precuneus. However, there were no associations between brain morphometry and social cognition in the SZ group when considered alone. Taken together, ToM behavioral deficits were associated with thinner right anterior temporal lobe, a critical region from a larger affective ToM network among all cases with psychosis, but aberrant morphology of brain regions key for self-processing were specific to the BD group. These findings may have important implications for targeted interventions for the affective social brain network in BD., (© 2019 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.)

Aim: Previous studies have reported different brain morphologies in different cognitive subgroups of patients with schizophrenia. We aimed to examine the brain structures and functional connectivity in these cognitive subgroups of schizophrenia., Methods: We compared brain structures among healthy controls and cognitively deteriorated and preserved subgroups of patients with schizophrenia according to the decline in IQ. Connectivity analyses between subcortical regions and other brain areas were performed using resting-state functional magnetic resonance imaging among the groups., Results: Whole brain and total cortical gray matter, right fusiform gyrus, left pars orbitalis gyrus, right pars triangularis, left superior temporal gyrus and left insula volumes, and bilateral cortical thickness were decreased in the deteriorated group compared to the control and preserved groups. Both schizophrenia subgroups had increased left lateral ventricle, right putamen and left pallidum, and decreased bilateral hippocampus, left precentral gyrus, right rostral middle frontal gyrus, and bilateral superior frontal gyrus volumes compared with controls. Hyperconnectivity between the thalamus and a broad range of brain regions was observed in the deteriorated group compared to connectivity in the control group, and this hyperconnectivity was less evident in the preserved group. We also found hyperconnectivity between the accumbens and the superior and middle frontal gyri in the preserved group compared with connectivity in the deteriorated group., Conclusion: These findings provide evidence of prominent structural and functional brain abnormalities in deteriorated patients with schizophrenia, suggesting that cognitive subgroups in schizophrenia might be useful biotypes to elucidate brain pathophysiology for new diagnostic and treatment strategies., (© 2019 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

Catatonia is a nosologically unspecific syndrome, which subsumes a plethora of mostly complex affective, motor, and behavioral phenomena. Although catatonia frequently occurs in schizophrenia spectrum disorders (SSD), specific patterns of abnormal brain structure and function underlying catatonia are unclear at present. Here, we used a multivariate data fusion technique for multimodal magnetic resonance imaging (MRI) data to investigate patterns of aberrant intrinsic neural activity (INA) and gray matter volume (GMV) in SSD patients with and without catatonia. Resting-state functional MRI and structural MRI data were collected from 87 right-handed SSD patients. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). A multivariate analysis approach was used to examine co-altered patterns of INA and GMV. Following a categorical approach, we found predominantly frontothalamic and corticostriatal abnormalities in SSD patients with catatonia (NCRS total score ≥ 3; n = 24) when compared to SSD patients without catatonia (NCRS total score = 0; n = 22) matched for age, gender, education, and medication. Corticostriatal network was associated with NCRS affective scores. Following a dimensional approach, 33 SSD patients with catatonia according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision were identified. NCRS behavioral scores were associated with a joint structural and functional system that predominantly included cerebellar and prefrontal/cortical motor regions. NCRS affective scores were associated with frontoparietal INA. This study provides novel neuromechanistic insights into catatonia in SSD suggesting co-altered structure/function-interactions in neural systems subserving coordinated visuospatial functions and motor behavior., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Novel methods for measuring large-scale dynamic brain organisation are needed to provide new biomarkers of schizophrenia. Using a method for modelling dynamic modular organisation (Mucha et al., 2010), evidence suggests higher 'flexibility' (switching between multilayer network communities) to be a feature of schizophrenia (Braun et al., 2016). The current study compared flexibility between 55 patients with schizophrenia and 72 controls (the COBRE Dataset). In addition, novel methods of 'between resting state network synchronisation' (BRSNS) and the probability of transition from one community to another were used to further describe group differences in dynamic community structure. There was significantly higher schizophrenia group flexibility scores in cerebellar (F (1124) = 9.33, p (FDR) = 0.017), subcortical (F (1124) = 13.14, p (FDR) = 0.005), and fronto-parietal task control (F (1124) = 7.19, p (FDR) = 0.033) resting state networks (RSNs), as well as in the left thalamus (MNI XYZ: -2, -13, 12; F(1, 124) = 17.1, p (FDR) < 0.001) and the right crus I (MNI XYZ: 35, -67, -34; F (1, 124) = 19.65, p (FDR) < 0.001). Flexibility in the left thalamus reflected transitions between communities covering default mode and sensory-somatomotor RSNs. BRSNS scores suggested altered dynamic inter-RSN modular configuration in schizophrenia. This study suggests less stable community structure in a schizophrenia group at an RSN and node level and provides novel methods of exploring dynamic community structure. Mediation of group differences by mean time window correlation did however suggest flexibility to be no better as a schizophrenia biomarker than simpler measures and a range of methodological choices affected results., Competing Interests: Declarations of Competing Interest The authors declare no competing interests for the current study., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

The relationship between the cognitive impairment and the structural and functional abnormalities in the brains of patients with schizophrenia (SZ) is not yet clear. This study aims to investigate the relationship, thereby exploring the neuromechanism underlying SZ. We collected multimodal MRI data from 68 first-episode, drug-naïve patients with SZ, and 64 well-matched healthy controls, and used regional homogeneity (ReHo) and gray matter volume (GMV) to assess the functional and structural integrity of the brains, respectively. We then evaluated in the entire brain the correlations between ReHo/GMV and the participants' neuropsychological assessment scores for each group using a partial correlation analysis controlling for age and sex. We found significant uncoupling between attention performance and mean ReHo in the left middle frontal gyrus, right superior/inferior parietal lobe (IPL), right angular gyrus (AG) and right middle/inferior temporal lobe (ITG) in SZ compared with healthy controls. Moreover, we found that the SZ group showed decreased GMV in the right IPL and AG, and a significant coupling between ReHo and GMV in the right ITG. Our findings suggest that the attention dysfunction found in SZ may be associated with the structural and functional abnormalities as well as the structure-function interrelation in several SZ-related brain regions., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Prospection, which has a close relationship with motivation and goal-directed behavior, could be a potential target for alleviating negative symptoms. The present study aimed to examine the structural neural correlates of prospection impairments and the involvement of working memory in prospection in schizophrenia patients. Thirty-seven patients with schizophrenia and 28 healthy controls were recruited and all of them completed a prospection task. Working memory was assessed with the Letter Number Span test. In addition, all participants underwent a structural MRI scan. Voxel-based morphometry (VBM) analysis was used to measure grey matter (GM) volume. We found that in schizophrenia patients, GM loss in the right lateral prefrontal cortex (PFC) and the right ventral medial PFC was correlated with decreased internal details in the prospection task. Moreover, GM volume of the right lateral PFC was found to mediate the relationship between working memory and internal details in these patients. In conclusion, GM loss in the PFC is associated with prospection impairments in schizophrenia patients. Working memory deficits may partially account for prospection impairments in schizophrenia patients., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Resting-state functional MRI (rsfMRI) is a useful technique for investigating the functional organization of human gray-matter in neuroscience and neuropsychiatry. Nevertheless, most studies have demonstrated the functional connectivity and/or task-related functional activity in the gray-matter. White-matter functional networks have been investigated in healthy subjects. Schizophrenia has been hypothesized to be a brain disorder involving insufficient or ineffective communication associated with white-matter abnormalities. However, previous studies have mainly examined the structural architecture of white-matter using MRI or diffusion tensor imaging and failed to uncover any dysfunctional connectivity within the white-matter on rsfMRI. The current study used rsfMRI to evaluate white-matter functional connectivity in a large cohort of ninety-seven schizophrenia patients and 126 healthy controls. Ten large-scale white-matter networks were identified by a cluster analysis of voxel-based white-matter functional connectivity and classified into superficial, middle and deep layers of networks. Evaluation of the spontaneous oscillation of white-matter networks and the functional connectivity between them showed that patients with schizophrenia had decreased amplitudes of low-frequency oscillation and increased functional connectivity in the superficial perception-motor networks. Additionally, we examined the interactions between white-matter and gray-matter networks. The superficial perception-motor white-matter network had decreased functional connectivity with the cortical perception-motor gray-matter networks. In contrast, the middle and deep white-matter networks had increased functional connectivity with the superficial perception-motor white-matter network and the cortical perception-motor gray-matter network. Thus, we presumed that the disrupted association between the gray-matter and white-matter networks in the perception-motor system may be compensated for through the middle-deep white-matter networks, which may be the foundation of the extensively disrupted connections in schizophrenia., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: This study investigated characteristic large-scale brain changes in schizophrenia. Numerous imaging studies have demonstrated brain changes in schizophrenia, particularly aberrant intrinsic functional connectivity (iFC) of ongoing brain activity, measured by resting-state functional magnetic resonance imaging, and aberrant gray matter volume (GMV) of distributed brain regions, measured by structural magnetic resonance imaging. It is unclear, however, which iFC changes are specific to schizophrenia compared with those of other disorders and whether such specific iFC changes converge with GMV changes. To address this question of specific substantial dysconnectivity in schizophrenia, we performed a transdiagnostic multimodal meta-analysis of resting-state functional and structural magnetic resonance imaging studies in schizophrenia and other psychiatric disorders., Methods: Multiple databases were searched up to June 2017 for whole-brain seed-based iFC studies and voxel-based morphometry studies in schizophrenia, major depressive disorder, bipolar disorder, addiction, and anxiety. Coordinate-based meta-analyses were performed to detect 1) schizophrenia-specific hyperconnectivity or hypoconnectivity of intrinsic brain networks (compared with hyperconnectivity or hypoconnectivity of each other disorder both separately and combined across comparisons) and 2) the overlap between dysconnectivity and GMV changes (via multimodal conjunction analysis)., Results: For iFC meta-analysis, 173 publications comprising 4962 patients and 4575 control subjects were included, and for GMV meta-analysis, 127 publications comprising 6311 patients and 6745 control subjects were included. Disorder-specific iFC dysconnectivity in schizophrenia (consistent across comparisons with other disorders) was found for limbic, frontoparietal executive, default mode, and salience networks. Disorder-specific dysconnectivity and GMV reductions converged in insula, lateral postcentral cortex, striatum, and thalamus., Conclusions: Results demonstrated specific substantial dysconnectivity in schizophrenia in insula, lateral postcentral cortex, striatum, and thalamus. Data suggest that these regions are characteristic targets of schizophrenia., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Although modified electroconvulsive therapy (MECT) has been employed as a treatment strategy and to resolve medication resistant symptoms in schizophrenia (SZ), its action mechanisms remain unclear. The insula has been demonstrated to associate with clinical symptoms and neuropathology in SZ. This study examined whether insular changes response to MECT outcomes in SZ. Forty-two SZ were divided into two groups according to their treatment strategies. One group (MSZ, n = 21) received 4-weeks MECT together with antipsychotics; another group (DSZ, n = 21) was treated only with antipsychotics. Twenty-three healthy controls (HC) were also included. Structural and functional MRI were scanned twice (baseline and after 4-week treatment) for SZ and once for HC. Firstly, the insula was divided into three subregions based on resting-state functional connectivity (FC). Subsequently, gray matter volume (GMV) and voxel-wise FC were assessed in each subregion. Finally, the relationship between insular changes and symptom improvements was also investigated. Compared with baseline, the DSZ group showed reduced GMV in insular subregions. In contrast, the MSZ group exhibited increased GMV in bilateral posterior insula (PIns); furthermore, the increase in the PIns was correlated with symptom improvements. Second, the decreased FC between right PIns and left orbitofrontal cortex, and left PIns and middle occipital gyrus was observed only in the MSZ group; moreover, these FC changes were associated with symptom improvements. The present study demonstrated that MECT induced insular changes, which may contribute to the mechanisms of MECT., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Electroconvulsive therapy (ECT) is often considered as an augmentation of antipsychotic treatment for schizophrenia in drug-refractory cases. However, the mechanisms underlying the observed therapeutic effects are still not understood., Objective: We aimed to investigate changes in whole brain grey matter volume (GMV) before and after modified ECT. GMV was determined using voxel-based morphometry (VBM) whole brain analysis. Correlations of brain structural changes with clinical improvement were also investigated., Methods: Twenty-one schizophrenia patients treated with a full course of ECT combined with antipsychotics (ECT group) and 21 schizophrenia patients treated only with antipsychotics (Drug group) were observed in parallel. Magnetic resonance imaging scans were performed at baseline (T1) and follow-up (T2) for each patient. Data were compared to a healthy control group (HC group) of 23 persons who were only scanned at baseline. Demographic data were matched between the three groups., Results: Significant interactions of group by time were found within four brain regions: the left parahippocampal gyrus/hippocampus, right parahippocampal gyrus/hippocampus, right temporal&#95;pole&#95;mid/superior temporal gyrus, and right insula. Post-hoc analysis revealed an increase of GMV across all four regions amongst ECT group, but a decrease of GMV within the Drug group. Furthermore, the ECT group showed a significant positive correlation of GMV change in the right parahippocampal gyrus/hippocampus with a reduction of positive subscore in the positive and negative syndrome scale. Both treatment groups did not differ significantly in terms of GMV from the HC group in these regions either at T1 or at T2., Conclusion: Our findings indicate that ECT may induce brain plasticity as indexed by grey matter volume change during the treatment of schizophrenia via distinct mechanics from those by antipsychotic medications. ECT may ameliorate the positive psychotic symptoms of patients suffering from schizophrenia by preferentially targeting limbic brain areas such as the parahippocampal gyrus/hippocampus., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Despite hundreds of structural MRI studies documenting smaller brain volumes on average in schizophrenia compared to controls, little attention has been paid to group differences in the variability of brain volumes. Examination of variability may help interpret mean group differences in brain volumes and aid in better understanding the heterogeneity of schizophrenia. Variability in 246 MRI studies was meta-analyzed for 13 structures that have shown medium to large mean effect sizes (Cohen's d≥0.4): intracranial volume, total brain volume, lateral ventricles, third ventricle, total gray matter, frontal gray matter, prefrontal gray matter, temporal gray matter, superior temporal gyrus gray matter, planum temporale, hippocampus, fusiform gyrus, insula; and a control structure, caudate nucleus. No significant differences in variability in cortical/subcortical volumes were detected in schizophrenia relative to controls. In contrast, increased variability was found in schizophrenia compared to controls for intracranial and especially lateral and third ventricle volumes. These findings highlight the need for more attention to ventricles and detailed analyses of brain volume distributions to better elucidate the pathophysiology of schizophrenia., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Pathophysiological and atrophic changes in the cerebellum have been well-documented in schizophrenia. Reduction of gray matter (GM) in the cerebellum was confirmed across cognitive and motor cerebellar modules in schizophrenia. Such abnormalities in the cerebellum could potentially have widespread effects on both sensorimotor and cognitive symptoms. In this study, we investigated how reduction change in the cerebellum affects the static and the dynamic functional connectivity (FC) between the cerebellum and cortical/subcortical networks in schizophrenia. Reduction of GM in the cerebellum was confirmed across the cognitive and motor cerebellar modules in schizophrenic subjects. Results from this study demonstrates that the extent of reduction of GM within cerebellum correlated with increased static FCs between the cerebellum and the cortical/subcortical networks, including frontoparietal network (FPN), and thalamus in patients with schizophrenia. Decreased GM in the cerebellum was also associated with a declined dynamic FC between the cerebellum and the FPN in schizophrenic subjects. The severity of patients' positive symptom was related to these structural-functional coupling score of cerebellum. These findings identified potential cerebellar driven functional changes associated with positive symptom deficits. A post hoc analysis exploring the effect of changed FC within cerebellum, confirmed that a significant positive relationship, between dynamic FCs of cerebellum-thalamus and intracerebellum existed in patients, but not in controls. The reduction of GM within the cerebellum might be associated with modulation of cerebellum-thalamus, and contributes to the dysfunctional cerebellar-cortical communication in schizophrenia. Our results provide a new insight into the role of cerebellum in understanding the pathophysiological of schizophrenia., (© 2018 Wiley Periodicals, Inc.)

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.

The progress of schizophrenia at various stages is an intriguing question, which has been explored to some degree using single-modality brain imaging data, e.g. gray matter (GM) or functional connectivity (FC). However it remains unclear how those changes from different modalities are correlated with each other and if the sensitivity to duration of illness and disease stages across modalities is different. In this work, we jointly analyzed FC, GM volume and single nucleotide polymorphisms (SNPs) data of 159 individuals including healthy controls (HC), drug-naïve first-episode schizophrenia (FESZ) and chronic schizophrenia patients (CSZ), aiming to evaluate the links among SNP, FC and GM patterns, and their sensitivity to duration of illness and disease stages in schizophrenia. Our results suggested: 1) both GM and FC highlighted impairments in hippocampal, temporal gyrus and cerebellum in schizophrenia, which were significantly correlated with genes like SATB2, GABBR2, PDE4B, CACNA1C etc. 2) GM and FC presented gradually decrease trend (HC > FESZ>CSZ), while SNP indicated a non-gradual variation trend with un-significant group difference observed between FESZ and CSZ; 3) Group difference between HC and FESZ of FC was more remarkable than GM, and FC presented a stronger negative correlation with duration of illness than GM (p = 0.0006). Collectively, these results highlight the benefit of leveraging multimodal data and provide additional clues regarding the impact of mental illness at various disease stages., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Impaired verbal communication is a prominent feature in patients with schizophrenia. Verbal communication difficulties adversely affect psychosocial outcomes and worsen schizophrenia's clinical manifestation. In the present study, we aimed to investigate associations among gray matter (GM) volumes in language processing areas (LPAs), verbal ability, and positive symptoms in first-episode patients (FEPs) with schizophrenia spectrum psychosis., Methods: We enrolled 94 FEPs and 52 healthy controls (HCs) and subjected them to structural magnetic resonance imaging. The GM volumes of the bilateral pars opercularis (POp), pars triangularis (PTr), planum temporale (PT), Heschl's gyrus (HG), insula, and fusiform gyrus (FG), were estimated and compared between the FEPs and HCs. Verbal intelligence levels and positive symptom severity were examined for correlations with the left LPA volumes., Results: The GM volumes of the left POp, HG, and FG were significantly smaller in the FEPs than in the HCs, while the right regions showed no significant between-group difference. A multiple linear regression model revealed that larger left PT volume was associated with better verbal intelligence in FEPs. In exploratory correlation analysis, several LPAs showed significant correlations with the severity of positive symptoms in FEPs. The left FG volume had a strong inverse correlation with the severity of auditory verbal hallucinations, while the left PT volume was inversely associated with the severity of positive formal thought disorder and delusions. Moreover, the volume of the left insula was positively associated with the severity of bizarre behavior., Conclusions: The present study suggests that GM abnormalities in the LPAs, which can be detected during the early stage of illness, may underlie impaired verbal communication and positive symptoms in patients with schizophrenia spectrum psychosis., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Although cerebellar involvement across a wide range of cognitive and neuropsychiatric phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia (SZ) have primarily focused on supratentorial structures. Hence, the across-sample reproducibility, regional distribution, associations with cerebrocortical morphology and effect sizes of cerebellar relative to cerebral morphological differences in SZ are unknown. We addressed these questions in 983 patients with SZ spectrum disorders and 1349 healthy controls (HCs) from 14 international samples, using state-of-the-art image analysis pipelines optimized for both the cerebellum and the cerebrum. Results showed that total cerebellar grey matter volume was robustly reduced in SZ relative to HCs (Cohens's d=-0.35), with the strongest effects in cerebellar regions showing functional connectivity with frontoparietal cortices (d=-0.40). Effect sizes for cerebellar volumes were similar to the most consistently reported cerebral structural changes in SZ (e.g., hippocampus volume and frontotemporal cortical thickness), and were highly consistent across samples. Within groups, we further observed positive correlations between cerebellar volume and cerebral cortical thickness in frontotemporal regions (i.e., overlapping with areas that also showed reductions in SZ). This cerebellocerebral structural covariance was strongest in SZ, suggesting common underlying disease processes jointly affecting the cerebellum and the cerebrum. Finally, cerebellar volume reduction in SZ was highly consistent across the included age span (16-66 years) and present already in the youngest patients, a finding that is more consistent with neurodevelopmental than neurodegenerative etiology. Taken together, these novel findings establish the cerebellum as a key node in the distributed brain networks underlying SZ.

Lack of insight is a core feature of non-affective psychosis and has been associated with poorer outcomes. Brain abnormalities underlying lack of insight have been suggested, mostly in the frontal lobe, although previous research showed mixed results. We used a voxel-based morphometry (VBM) analysis in 108 first-episode non-affective psychosis patients to investigate the pattern of brain structural abnormalities related to lack of insight. In addition, 77 healthy volunteers were compared with the patients classified as having poor and good insight. The shortened version of the Scale to Assess Unawareness of Mental Disorder was used to evaluate insight. Patients with poor insight (n = 68) compared with patients with good insight (n = 40) showed a single significant cluster (kc = 5834; PcFWE = 0.001) of reduced grey matter volume (GMV) in the right occipital lobe extending to its lateral and medial surfaces, the cuneus, and the middle temporal gyrus. In addition, GMV at this cluster showed a negative correlation with the score of the SUMD (r = -0.305; p = 0.001). When comparing patients with poor insight with healthy subjects overall reductions of GMV were found, mainly in frontal and occipital lobes. Hence, poor insight in non-affective psychosis seems to be associated with specific brain abnormalities in the right occipital and temporal cortical regions. Dysfunction in any combination of these areas may contribute to lack of insight in non-affective psychosis. Specifically, the 'right' hemisphere dysfunction underlying impaired insight in our sample is consistent with previously reported similarities between lack of insight in psychosis and anosognosia in neurological disorders., Competing Interests: The authors have declared that no competing interests exist.

Structural and functional deficits associated with schizophrenia are observed prior to the onset of psychosis and differ according to the stage of illness. However, most previous studies concentrated on a limited period during the illness, and it remains uncertain how these abnormalities develop throughout the entire disease course. In the current study, we investigated the gray matter (GM) and regional neural activity alterations in subjects at 4 different stages of schizophrenia. The subjects comprised 53 genetic high risk (HR) individuals, 26 ultra-high risk (UHR) individuals, 58 patients with first-episode schizophrenia (FES), 41 patients with chronic schizophrenia (ChSz) and 39 healthy controls (HC), all of whom underwent structural and resting-state functional MRI scanning. Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) values were compared voxelwise among the five groups using voxel-based morphometry (VBM) and the software REST. Correlations among structural, functional abnormalities and PANSS scores in the FES group were evaluated by partial correlation analysis and multiple stepwise regression. Pronounced GMV decline was observed in the bilateral occipital lobe, left orbital frontal cortex, bilateral superior parietal lobule (SPL), right middle temporal gyrus (MTG), gyrus rectus and medial superior frontal gyrus (SFG) in the FES group and in the bilateral occipital lobe in the HR group. The FES patients also showed increased ALFF in the caudate and decreased ReHo in the bilateral inferior parietal lobule (IPL) and precuneus. The ChSz patients displayed increased ALFF in the right hippocampus. The GMV of the right MTG and SPL and the ReHo of the precuneus were negatively correlated with the general psychopathology scale, while the GMV of the right MTG was negatively correlated with the total score on the Positive and Negative Syndrome Scale (PANSS). The GMV of the right occipital cortex and SPL were associated with the ALFF of the caudate, the GMV of the right SPL was associated with the ReHo of the bilateral IPL and precuneus. GM deficits and regional dysfunction are evident prior to the onset of psychotic symptoms and are more prominent during the onset of illness than during any other phase. The right MTG and SPL, the striatum and the DMN may play important roles in the pathological changes underlying schizophrenia., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Acquisition of multimodal brain imaging data for the same subject has become more common leading to a growing interest in determining the intermodal relationships between imaging modalities to further elucidate the pathophysiology of schizophrenia. Multimodal data have previously been individually analyzed and subsequently integrated; however, these analysis techniques lack the ability to examine true modality inter-relationships. The utilization of a multiset canonical correlation and joint independent component analysis (mCCA + jICA) model for data fusion allows shared or distinct abnormalities between modalities to be examined. In this study, first-episode schizophrenia patients (n SZ =19) and matched controls (n HC =21) completed a resting-state functional magnetic resonance imaging (fMRI) scan at 7 T. Grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and amplitude of low frequency fluctuation (ALFF) maps were used as features in a mCCA + jICA model. Results of the mCCA + jICA model indicated three joint group-discriminating components (GM-CSF, WM-ALFF, GM-ALFF) and two modality-unique group-discriminating components (GM, WM). The joint component findings are highlighted by GM basal ganglia, somatosensory, parietal lobe, and thalamus abnormalities associated with ventricular CSF volume; WM occipital and frontal lobe abnormalities associated with temporal lobe function; and GM frontal, temporal, parietal, and occipital lobe abnormalities associated with caudate function. These results support and extend major findings throughout the literature using independent single modality analyses. The multimodal fusion of 7 T data in this study provides a more comprehensive illustration of the relationships between underlying neuronal abnormalities associated with schizophrenia than examination of imaging data independently., (© 2018 Wiley Periodicals, Inc.)

Background: Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia., Methods: We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses., Results: We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus., Limitations: The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects., Conclusion: The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

The current study aimed to explore age-variant trait differences of cortical gray matter volume (GMV) in a unique sample of first-episode and treatment-naïve patients with schizophrenia. A total of 158 subjects, including 26 adolescent-onset patients and 49 adult-onset patients as well as 83 age- and gender-matched controls were scanned using a 3T MRI scanner. Voxel-based morphometry (VBM) following Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra (DARTEL) was used to explore group differences between patients and controls in regional GMV. We found that patients with schizophrenia had decreased GMV in the left parietal postcentral region that extended to the left frontal regions, the right middle temporal gyrus, the occipital lobe and the right cerebellum posterior pyramis. Further analysis showed a distinct pattern of gray matter alterations in adolescent-onset patients compared with both healthy controls and adult-onset patients. Relative to healthy controls, adolescent-onset patients showed GMV alterations in the left parietal postcentral gyrus, parahippocampal gyrus and right cerebellum posterior pyramis, while GMV deficits in adult-onset patients were focused on the cingulo-fronto-temporal module and right occipital regions. Our study identified differential cortical gray matter deficits between adolescent- and adulthood-onset patients with schizophrenia, which suggests that the cortical abnormalities in schizophrenia are likely adjusted by the developmental community structure of the human brain.

An interaction between external stressors and intrinsic vulnerability is one of the longest standing pathoaetiological explanations for schizophrenia. However, novel lines of evidence from genetics, preclinical studies, epidemiology and imaging have shed new light on the mechanisms that may underlie this, implicating microglia as a key potential mediator. Microglia are the primary immune cells of the central nervous system. They have a central role in the inflammatory response, and are also involved in synaptic pruning and neuronal remodeling. In addition to immune and traumatic stimuli, microglial activation occurs in response to psychosocial stress. Activation of microglia perinatally may make them vulnerable to subsequent overactivation by stressors experienced in later life. Recent advances in genetics have shown that variations in the complement system are associated with schizophrenia, and this system has been shown to regulate microglial synaptic pruning. This suggests a mechanism via which genetic and environmental influences may act synergistically and lead to pathological microglial activation. Microglial overactivation may lead to excessive synaptic pruning and loss of cortical gray matter. Microglial mediated damage to stress-sensitive regions such as the prefrontal cortex and hippocampus may lead directly to cognitive and negative symptoms, and account for a number of the structural brain changes associated with the disorder. Loss of cortical control may also lead to disinhibition of subcortical dopamine-thereby leading to positive psychotic symptoms. We review the preclinical and in vivo evidence for this model and consider the implications this has for treatment, and future directions.

Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide single-nucleotide polymorphism (SNP) and neuroimaging data from 1750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (false discovery rate=10%). In particular, intracranial volume and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross-disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder., Competing Interests: Authors declare no conflicts of interest.

Neuroimaging research into the brain structure of schizophrenia patients has shown consistent reductions in grey matter volume relative to healthy controls. Examining structural differences in individuals with high levels of schizotypy may help elucidate the course of disorder progression, and provide further support for the schizotypy-schizophrenia continuum. Thus far, the few studies investigating grey matter differences in schizotypy have produced inconsistent results. In the current study, we used a multivariate partial least squares (PLS) approach to clarify the relationship between psychometric schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experiences) and grey matter volume in 49 healthy adults. We found a negative association between all schizotypy dimensions and grey matter volume in the frontal and temporal lobes, as well as the insula. We also found a positive association between all schizotypy dimensions and grey matter volume in the parietal and temporal lobes, and in subcortical regions. Further correlational analyses revealed that positive and disorganised schizotypy were strongly associated with key regions (left superior temporal gyrus and insula) most consistently reported to be affected in schizophrenia and schizotypy. We also compared PLS with the typically used General Linear Model (GLM) and demonstrate that PLS can be reliably used as an extension to voxel-based morphometry (VBM) data. This may be particularly valuable for schizotypy research due to PLS' ability to detect small, but reliable effects. Together, the findings indicate that healthy schizotypal individuals exhibit structural changes in regions associated with schizophrenia. This adds to the evidence of an overlap of phenotypic expression between schizotypy and schizophrenia, and may help establish biological endophenotypes for the disorder., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

13 male patients with schizophrenia and 18 age-matched healthy men underwent structural magnetic reso- nance imaging and completed the Stroop task which included the switching condition. As compared to con- trols, the patients showed slowing of color naming in the neutral condition and a reduction ofgray matter vol- ume and thickness in the frontal and temporal areas. In healthy subjects, the time of color naming was neg- atively correlated with gray matter volume in the left cuneus. In the schizophrenia group, there was a positive correlation between the time of color naming and cortical thickness in the middle and inferior frontal gyri of the right hemisphere. These results indicate a change in structural-functional relationships at the early stages of schizophrenia.

The objective of this longitudinal magnetic resonance (MR) imaging study was to examine the effects of endurance training on hippocampal and grey matter volumes in schizophrenia patients and healthy controls. 20 chronic schizophrenia patients and 21 age- and gender-matched healthy controls underwent 3months of endurance training (30min, 3 times per week). 19 additionally recruited schizophrenia patients played table soccer ("foosball" in the USA) over the same period. MR imaging with 3D-volumetric T1-weighted sequences was performed on a 3T MR scanner at baseline, after 6weeks and after the 3-month intervention and 3 additional training-free months. In addition to voxel-based morphometry (VBM), we performed manual and automatic delineation of the hippocampus and its substructures. Endurance capacity and psychopathological symptoms were measured as secondary endpoints. No significant increases in the volumes of the hippocampus or hippocampal substructures were observed in schizophrenia patients or healthy controls. However, VBM analyses displayed an increased volume of the left superior, middle and inferior anterior temporal gyri compared to baseline in schizophrenia patients after the endurance training, whereas patients playing table soccer showed increased volumes in the motor and anterior cingulate cortices. After the additional training-free period, the differences were no longer present. While endurance capacity improved in exercising patients and healthy controls, psychopathological symptoms did not significantly change. The subtle changes in the left temporal cortex indicate an impact of exercise on brain volumes in schizophrenia. Subsequent studies in larger cohorts are warranted to address the question of response variability of endurance training., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Cortical gray matter loss in schizophrenia remains a great therapeutic difficulty. Each psychotic episode causes irreversible cortical gray matter loss, that causes the patients to never regain their previous state of functioning. Microglial cells are part of the innate immune system and their functions, among others, include phagocytosis and release of neurotrophic factors. They have a key impact on developmental and plasticity-induced removal of neuronal precursors, live-but-stressed neurons and synapses, while also stimulating synaptic growth and development. We hypothesize that microglia are the culprit for the cortical gray matter loss in schizophrenia through abnormal synaptic pruning, phagocytosis of stressed neurons and lacking neurotrophic factor release. Furthermore, we propose a research that could validate the hypotheses using serum samples of first-episode early-onset patients. By measuring the serum levels of milk fat globule-EGF factor 8 (MFG-E8), subcomponent in the classical pathway of complement activation (C1q), brain-derived neurotrophic factor (BDNF), interleukin-6 (IL-6) and interleukin-10 (IL-10), we could gain an insight into the state of microglial activation during various stages of the disease. If this hypothesis is valid, new targeted drugs could be developed in order to reduce the deterioration of cortical gray matter, thereby possibly improving negative symptoms and cognitive deficits., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Schizophrenia (SZ) and bipolar disorder (BD) share clinical features, genetic risk factors and neuroimaging abnormalities. There is evidence of disrupted connectivity in resting state networks in patients with SZ and BD and their unaffected relatives. Resting state networks are known to undergo reorganization during youth coinciding with the period of increased incidence for both disorders. We therefore focused on characterizing resting state network connectivity in youth at familial risk for SZ or BD to identify alterations arising during this period. We measured resting-state functional connectivity in a sample of 106 youth, aged 7-19 years, comprising offspring of patients with SZ (N = 27), offspring of patients with BD (N = 39) and offspring of community control parents (N = 40). We used Independent Component Analysis to assess functional connectivity within the default mode, executive control, salience and basal ganglia networks and define their relationship to grey matter volume, clinical and cognitive measures. There was no difference in connectivity within any of the networks examined between offspring of patients with BD and offspring of community controls. In contrast, offspring of patients with SZ showed reduced connectivity within the left basal ganglia network compared to control offspring, and they showed a positive correlation between connectivity in this network and grey matter volume in the left caudate. Our findings suggest that dysconnectivity in the basal ganglia network is a robust correlate of familial risk for SZ and can be detected during childhood and adolescence.

Both schizophrenia and antipsychotic treatment are known to modulate brain morphology. However, it is difficult to establish whether observed structural brain abnormalities are due to disease or the effects of treatment. The aim of this study was to investigate the effects of illness and antipsychotic treatment on brain structures in antipsychotic-naïve first-episode schizophrenia based on a longitudinal short-term design. Twenty antipsychotic-naïve subjects with first-episode schizophrenia and twenty-four age- and sex-matched healthy controls underwent 3T MRI scans. Voxel-based morphometry (VBM) was used to examine the brain structural abnormality in patients compared to healthy controls. Nine patients were included in the follow-up examination after 8 weeks of treatment. Tensor-based morphometry (TBM) was used to identify longitudinal brain structural changes. We observed significantly reduced grey matter volume in the right superior temporal gyrus in antipsychotic-naïve patients with schizophrenia compared with healthy controls. After 8 weeks of treatment, patients showed significantly increased grey matter volume primarily in the bilateral prefrontal cortex, insula, right thalamus, left superior occipital cortex and the bilateral cerebellum. In addition, a greater enlargement of the prefrontal cortex is associated with the improvement in negative symptoms, and a more enlarged thalamus is associated with greater improvement in positive symptoms. Our results suggest the following: (1) the abnormality in the right superior temporal gyrus is present in the early stages of schizophrenia, possibly representing the core region related to schizophrenia; and (2) atypical antipsychotics could modulate brain morphology involving the thalamus, cortical grey matter and cerebellum. In addition, examination of the prefrontal cortex and thalamus might facilitate an efficient response to atypical antipsychotics in terms of symptom improvement.

Objective: The purpose of this study was to determine whether microglial activity, measured using translocator-protein positron emission tomography (PET) imaging, is increased in unmedicated persons presenting with subclinical symptoms indicating that they are at ultra high risk of psychosis and to determine whether microglial activity is elevated in schizophrenia after controlling for a translocator-specific genetic polymorphism., Method: The authors used the second-generation radioligand [(11)C]PBR28 and PET to image microglial activity in the brains of participants at ultra high risk for psychosis. Participants were recruited from early intervention centers. The authors also imaged a cohort of patients with schizophrenia and matched healthy subjects for comparison. In total, 50 individuals completed the study. At screening, participants were genotyped to account for the rs6971 polymorphism in the gene encoding the 18Kd translocator protein. The main outcome measure was total gray matter [(11)C]PBR28 binding ratio, representing microglial activity., Results: [(11)C]PBR28 binding ratio in gray matter was elevated in ultra-high-risk participants compared with matched comparison subjects (Cohen's d >1.2) and was positively correlated with symptom severity (r=0.730). Patients with schizophrenia also demonstrated elevated microglial activity relative to matched comparison subjects (Cohen's d >1.7)., Conclusions: Microglial activity is elevated in patients with schizophrenia and in persons with subclinical symptoms who are at ultra high risk of psychosis and is related to at-risk symptom severity. These findings suggest that neuroinflammation is linked to the risk of psychosis and related disorders, as well as the expression of subclinical symptoms.

Investigating brain tissue T2* relaxation properties in vivo can potentially guide the uncovering of neuropathology in psychiatric illness, which is traditionally examined post mortem. We use an MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique that produces inherently co-registered images allowing quantitative assessment of tissue cellular and hemodynamic properties. Usually described as R2* (=1/T2*) relaxation rate constant, recent developments in GEPCI allow the separation of cellular-specific (R2*C) and hemodynamic (BOLD) contributions to the MRI signal decay. We characterize BOLD effect in terms of tissue concentration of deoxyhemoglobin, i.e. CDEOXY, which reflects brain activity. 17 control (CON), 17 bipolar disorder (BPD), 16 schizophrenia (SCZ), and 12 unaffected schizophrenia sibling (SIB) participants were scanned and post-processed using GEPCI protocols. A MANOVA of 38gray matter regions ROIs showed significant group effects for CDEOXY but not for R2*C. In the three non-control groups, 71-92% of brain regions had increased CDEOXY. Group effects were observed in the superior temporal cortex and the thalamus. Increased superior temporal cortex CDEOXY was found in SCZ (p=0.01), BPD (p=0.01) and SIB (p=0.02), with bilateral effects in SCZ and only left hemisphere effects in BPD and SIB. Thalamic CDEOXY abnormalities were observed in SCZ (p=0.003), BPD (p=0.03) and SIB (p=0.02). Our results suggest that increased activity in certain brain regions is part of the underlying pathophysiology of specific psychiatric disorders. High CDEOXY in the superior temporal cortex suggests abnormal activity with auditory, language and/or social cognitive processing. Larger studies are needed to clarify the clinical significance of relaxometric abnormalities., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Individuals in the early phases of psychotic illness have disturbed metacognitive capacity, which has been linked to a number of poor outcomes. Little is known, however, about the neural systems associated with metacognition in this population. The purpose of this study was to elucidate the neuroanatomical correlates of metacognition. We anticipated that higher levels of metacognition may be dependent upon gray matter density (GMD) of regions within the prefrontal cortex. Examining whole-brain structure in 25 individuals with early phase psychosis, we found positive correlations between increased medial prefrontal cortex and ventral striatum GMD and higher metacognition. These findings represent an important step in understanding the path through which the biological correlates of psychotic illness may culminate into poor metacognition and, ultimately, disrupted functioning. Such a path will serve to validate and promote metacognition as a viable treatment target in early phase psychosis.

Neuroimaging studies have identified patterns of brain abnormalities in various stages of schizophrenia, but whether these abnormalities reflect primary factors associated with the causes of illness or secondary phenomena such as medications has been unclear. Recent work conducted within the prodromal risk paradigm suggests that progressive change in brain structure and function occurs around the time when clinically high-risk individuals transition into full-blown psychosis, effects that cannot be explained by exposure to medications or illness chronicity. This article reviews recent work bearing on the question of the timing of onset and course of brain changes, focusing on structural MRI, diffusion tensor imaging, and resting state connectivity MRI, in association with the onset and course of psychosis. We conclude with a consideration of potential mechanisms underlying progressive tissue changes during the prodromal phase of schizophrenia and implications for prevention.

Background: Genetic variation in the gene encoding ZNF804A, a risk gene for schizophrenia, has been shown to affect brain functional endophenotypes of the disorder, while studies of white matter structure have been inconclusive., Method: We analysed effects of ZNF804A single nucleotide polymorphism rs1344706 on grey and white matter using voxel-based morphometry (VBM) in high-resolution T1-weighted magnetic resonance imaging scans of 62 schizophrenia patients and 54 matched healthy controls., Results: We found a significant (p < 0.05, family-wise error corrected for multiple comparisons) interaction effect of diagnostic group x genotype for local grey matter in the left orbitofrontal and right and left lateral temporal cortices, where patients and controls showed diverging effects of genotype. Analysing the groups separately (at p < 0.001, uncorrected), variation in rs1344706 showed effects on brain structure within the schizophrenia patients in several areas including the left and right inferior temporal, right supramarginal/superior temporal, right and left inferior frontal, left frontopolar, right and left dorsolateral/ventrolateral prefrontal cortices, and the right thalamus, as well as effects within the healthy controls in left lateral temporal, right anterior insula and left orbitofrontal cortical areas. We did not find effects of genotype of regional white matter in either of the two cohorts., Conclusions: Our findings demonstrate effects of ZNF804A genetic variation on brain structure, with diverging regional effects in schizophrenia patients and healthy controls in frontal and temporal brain areas. These effects, however, might be dependent on the impact of other (genetic or non-genetic) disease factors.

Background: Reduced gray matter volume in left superior temporal gyrus (STG) is considered to be associated with auditory P300 amplitude in schizophrenia. Little is known about possible pathological circuits regarding sub-regions of STG that contribute to auditory P300 abnormality in schizophrenia. The current study investigated gray matter volume in STG and functional connectivity of Heschl's gyrus in first-episode schizophrenia (FESZ), as well as their correlations with P300 amplitude., Methods: Nineteen FESZ patients and 19 healthy controls contributed MRI scans. Eighteen patients and 17 controls underwent auditory P300 test within 1 week after MRI scanning. STG structural abnormalities were analyzed using voxel-based morphometry (VBM) analysis. Bilateral Heschl's gyri (HG) were selected as seeds for FC analysis in resting MRI data. Correlations of P300 amplitude with gray matter alterations in STG and HG-based FC were analyzed using Pearson correlation analysis within each group., Results: Compared to healthy controls, FESZ patients showed reduced gray matter in left STG and P300 amplitude. Gray matter volume of left Heschl's gyrus was positively correlated with P300 amplitude in FESZ patients. HG-based FC of resting fMRI was decreased in the inferior frontal gyrus (IFG), medial frontal gyrus (MFG), anterior cingulate cortex (ACC), and left temporal pole, whereas the same metric was increased in the lingual gyrus, precuneus and cerebellar tonsil among FESZ patients. FC between bilateral HG and precuneus was inversely correlated with P300 amplitude among healthy controls, and was absent among FES patients., Conclusions: The findings point towards both decreased volume of Heschl's gyrus and its altered functional pathways may contribute to auditory P300 abnormality in schizophrenia., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background: Alterations in the dopaminergic reward system, predominantly the striatum, constitute core characteristics of schizophrenia., Aims: Functional connectivity of the dorsal striatum during reward-related trial-and-error learning was investigated in 17 people with schizophrenia and 18 healthy volunteers and related to striatal grey matter volume and psychopathology., Method: We used voxel-based morphometry and psychophysiological interaction to examine striatal volume and connectivity., Results: A reduced functional connectivity between left striatum and temporo-occipital areas, precuneus and insula could be detected in the schizophrenia group. The positive correlation between grey matter volume and functional connectivity of the left striatum yielded significant results in a very similar network. Connectivity of the left striatum was negatively correlated with negative symptoms., Conclusions: Present results suggest a disruption in striatal functional connectivity that is closely linked to grey matter morphometry of the striatum. Decreased connectivity between the striatum and psychopathologically relevant networks may explain the emergence of negative symptoms., (Royal College of Psychiatrists.)

One application of imaging genomics is to explore genetic variants associated with brain structure and function, presenting a new means of mapping genetic influences on mental disorders. While there is growing interest in performing genome-wide searches for determinants, it remains challenging to identify genetic factors of small effect size, especially in limited sample sizes. In an attempt to address this issue, we propose to take advantage of a priori knowledge, specifically to extend parallel independent component analysis (pICA) to incorporate a reference (pICA-R), aiming to better reveal relationships between hidden factors of a particular attribute. The new approach was first evaluated on simulated data for its performance under different configurations of effect size and dimensionality. Then pICA-R was applied to a 300-participant (140 schizophrenia (SZ) patients versus 160 healthy controls) dataset consisting of structural magnetic resonance imaging (sMRI) and single nucleotide polymorphism (SNP) data. Guided by a reference SNP set derived from ANK3, a gene implicated by the Psychiatric Genomic Consortium SZ study, pICA-R identified one pair of SNP and sMRI components with a significant loading correlation of 0.27 (p=1.64×10(-6)). The sMRI component showed a significant group difference in loading parameters between patients and controls (p=1.33×10(-15)), indicating SZ-related reduction in gray matter concentration in prefrontal and temporal regions. The linked SNP component also showed a group difference (p=0.04) and was predominantly contributed to by 1030 SNPs. The effect of these top contributing SNPs was verified using association test results of the Psychiatric Genomic Consortium SZ study, where the 1030 SNPs exhibited significant SZ enrichment compared to the whole genome. In addition, pathway analyses indicated the genetic component majorly relating to neurotransmitter and nervous system signaling pathways. Given the simulation and experiment results, pICA-R may prove a promising multivariate approach for use in imaging genomics to discover reliable genetic risk factors under a scenario of relatively high dimensionality and small effect size., (Copyright © 2013 Elsevier Inc. All rights reserved.)