Altered functional connectivity of the cingulate subregions in schizophrenia

Distinct resting-state functional connectivity of the anterior cingulate cortex subregions in first-episode schizophrenia

The anterior cingulate cortex (ACC) is a heterogeneous region of the brain's limbic system that regulates cognitive and emotional processing, and is frequently implicated in schizophrenia. This study aims to characterize resting-state functional connectivity (rsFC) profiles of three subregions of ACC in patients with first-episode schizophrenia and healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were collected from 60 first-episode schizophrenia (FES) patients and 60 healthy controls (HC), and the subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC) were selected as seed regions from the newest automated anatomical labeling atlas 3 (AAL3). Seed-based rsFC maps for each ACC subregion were generated and compared between the two groups. The results revealed that compared to the HC group, the FES group showed higher rsFC between the pgACC and bilateral lateral orbitofrontal cortex (lOFC), and lower rsFC between the dACC and right posterior OFC (pOFC), the medial prefrontal gyrus (MPFC), and the precuneus cortex (PCu). These findings point to a selective functional dysconnectivity of pgACC and dACC in schizophrenia and provide more accurate information about the functional role of the ACC in this disorder.

Astrocyte-secreted neurocan controls inhibitory synapse formation and function

Astrocytes strongly promote the formation and maturation of synapses by secreted proteins. Several astrocyte-secreted synaptogenic proteins controlling excitatory synapse development were identified; however, those that induce inhibitory synaptogenesis remain elusive. Here, we identify neurocan as an astrocyte-secreted inhibitory synaptogenic protein. After secretion from astrocytes, neurocan is cleaved into N- and C-terminal fragments. We found that these fragments have distinct localizations in the extracellular matrix. The neurocan C-terminal fragment localizes to synapses and controls cortical inhibitory synapse formation and function. Neurocan knockout mice lacking the whole protein or only its C-terminal synaptogenic domain have reduced inhibitory synapse numbers and function. Through super-resolution microscopy, in vivo proximity labeling by secreted TurboID, and astrocyte-specific rescue approaches, we discovered that the synaptogenic domain of neurocan localizes to somatostatin-positive inhibitory synapses and strongly regulates their formation. Together, our results unveil a mechanism through which astrocytes control circuit-specific inhibitory synapse development in the mammalian brain.

Explainable fuzzy clustering framework reveals divergent default mode network connectivity dynamics in schizophrenia

Introduction

Dynamic functional network connectivity (dFNC) analysis of resting state functional magnetic resonance imaging data has yielded insights into many neurological and neuropsychiatric disorders. A common dFNC analysis approach uses hard clustering methods like k-means clustering to assign samples to states that summarize network dynamics. However, hard clustering methods obscure network dynamics by assuming (1) that all samples within a cluster are equally like their assigned centroids and (2) that samples closer to one another in the data space than to their centroids are well-represented by their centroids. In addition, it can be hard to compare subjects, as in some cases an individual may not manifest a state strongly enough to enter a hard cluster. Approaches that allow a dimensional approach to connectivity patterns (e.g., fuzzy clustering) can mitigate these issues. In this study, we present an explainable fuzzy clustering framework by combining fuzzy c-means clustering with several explainability metrics and novel summary features.

Methods

We apply our framework for schizophrenia (SZ) default mode network analysis. Namely, we extract dFNC from individuals with SZ and controls, identify 5 dFNC states, and characterize the dFNC features most crucial to those states with a new perturbation-based clustering explainability approach. We then extract several features typically used in hard clustering and further present a variety of unique features specially designed for use with fuzzy clustering to quantify state dynamics. We examine differences in those features between individuals with SZ and controls and further search for relationships between those features and SZ symptom severity.

Results

Importantly, we find that individuals with SZ spend more time in states of moderate anticorrelation between the anterior and posterior cingulate cortices and strong anticorrelation between the precuneus and anterior cingulate cortex. We further find that individuals with SZ tend to transition more rapidly than controls between low-magnitude and high-magnitude dFNC states.

Conclusion

We present a novel dFNC analysis framework and use it to identify effects of SZ upon network dynamics. Given the ease of implementing our framework and its enhanced insight into network dynamics, it has great potential for use in future dFNC studies.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

Objective

To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.

Methods

We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.

Results

Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.

Conclusion

This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Molecular features driving cellular complexity of human brain evolution

Human-specific genomic changes contribute to the unique functionalities of the human brain1-5. The cellular heterogeneity of the human brain6,7 and the complex regulation of gene expression highlight the need to characterize human-specific molecular features at cellular resolution. Here we analysed single-nucleus RNA-sequencing and single-nucleus assay for transposase-accessible chromatin with sequencing datasets for human, chimpanzee and rhesus macaque brain tissue from posterior cingulate cortex. We show a human-specific increase of oligodendrocyte progenitor cells and a decrease of mature oligodendrocytes across cortical tissues. Human-specific regulatory changes were accelerated in oligodendrocyte progenitor cells, and we highlight key biological pathways that may be associated with the proportional changes. We also identify human-specific regulatory changes in neuronal subtypes, which reveal human-specific upregulation of FOXP2 in only two of the neuronal subtypes. We additionally identify hundreds of new human accelerated genomic regions associated with human-specific chromatin accessibility changes. Our data also reveal that FOS::JUN and FOX motifs are enriched in the human-specifically accessible chromatin regions of excitatory neuronal subtypes. Together, our results reveal several new mechanisms underlying the evolutionary innovation of human brain at cell-type resolution.

Brain subnetworks most sensitive to alterations of functional connectivity in Schizophrenia: a data-driven approach

Functional connectivity (FC) of the brain changes in various brain disorders. Its complexity, however, makes it difficult to obtain a systematic understanding of these alterations, especially when they are found individually and through hypothesis-based methods. It would be easier if the variety of brain connectivity alterations is extracted through data-driven approaches and expressed as variation modules (subnetworks). In the present study, we modified a blind approach to determine inter-group brain variations at the network level and applied it specifically to schizophrenia (SZ) disorder. The analysis is based on the application of independent component analysis (ICA) over the subject's dimension of the FC matrices, obtained from resting-state functional magnetic resonance imaging (rs-fMRI). The dataset included 27 SZ people and 27 completely matched healthy controls (HC). This hypothesis-free approach led to the finding of three brain subnetworks significantly discriminating SZ from HC. The area associated with these subnetworks mostly covers regions in visual, ventral attention, and somatomotor areas, which are in line with previous studies. Moreover, from the graph perspective, significant differences were observed between SZ and HC for these subnetworks, while there was no significant difference when the same parameters (path length, network strength, global/local efficiency, and clustering coefficient) across the same limited data were calculated for the whole brain network. The increased sensitivity of those subnetworks to SZ-induced alterations of connectivity suggested whether an individual scoring method based on their connectivity values can be applied to classify subjects. A simple scoring classifier was then suggested based on two of these subnetworks and resulted in acceptable sensitivity and specificity with an area under the ROC curve of 77.5%. The third subnetwork was found to be a less specific building block (module) for describing SZ alterations. It projected a wider range of inter-individual variations and, therefore, had a lower chance to be considered as a SZ biomarker. These findings confirmed that investigating brain variations from a modular viewpoint can help to find subnetworks that are more sensitive to SZ-induced alterations. Altogether, our study results illustrated the developed method's ability to systematically find brain alterations caused by SZ disorder from a network perspective.

Astrocyte-Secreted Neurocan Controls Inhibitory Synapse Formation and Function

Astrocytes strongly promote the formation and maturation of synapses by secreted proteins. To date, several astrocyte-secreted synaptogenic proteins controlling different stages of excitatory synapse development have been identified. However, the identities of astrocytic signals that induce inhibitory synapse formation remain elusive. Here, through a combination of in vitro and in vivo experiments, we identified Neurocan as an astrocyte-secreted inhibitory synaptogenic protein. Neurocan is a chondroitin sulfate proteoglycan that is best known as a protein localized to the perineuronal nets. However, Neurocan is cleaved into two after secretion from astrocytes. We found that the resulting N- and C-terminal fragments have distinct localizations in the extracellular matrix. While the N-terminal fragment remains associated with perineuronal nets, the Neurocan C-terminal fragment localizes to synapses and specifically controls cortical inhibitory synapse formation and function. Neurocan knockout mice lacking the whole protein or only its C-terminal synaptogenic region have reduced inhibitory synapse numbers and function. Through super-resolution microscopy and in vivo proximity labeling by secreted TurboID, we discovered that the synaptogenic domain of Neurocan localizes to somatostatin-positive inhibitory synapses and strongly regulates their formation. Together, our results unveil a mechanism through which astrocytes control circuit-specific inhibitory synapse development in the mammalian brain.

Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder

Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the "limbic," the "associative," and the "motor" subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Treatment Effect of Long-Term Antipsychotics on Default-Mode Network Dysfunction in Drug-Naïve Patients With First-Episode Schizophrenia: A Longitudinal Study

Background: The maintenance of antipsychotic treatment is an efficient way to prevent the relapse of schizophrenia (SCZ). Previous studies have identified beneficial effects of antipsychotics on brain structural and functional abnormalities during mostly the acute phase in SCZ, but seldom is known about the effects of long-term antipsychotics on the brain. The present study focused on the long-term antipsychotic effect on the default mode network (DMN) dysfunction in SCZ.

Methods: A longitudinal study of the functional connectivity (FC) of 11 DMN subdivisions was conducted in 86 drug-naive first-episode patients with SCZ at the baseline and after a long-term atypical antipsychotic treatment (more than 6 months) based on the resting-state functional magnetic resonance image. In total, 52 patients completed the follow-up of clinical and neuroimaging investigations.

Results: At the baseline, relative to healthy controls, altered connectivities within the DMN and between the DMN and the external attention system (EAS) were observed in patients. After treatment, along with significant relief of symptoms, most FC alterations between the DMN and the EAS at the baseline were improved after treatment, although the rehabilitation of FC within the DMN was only observed at the link between the posterior cingulate cortex and precuneus. Greater reductions in negative and positive symptoms were both related to the changes of DMN-EAS FC in patients.

Conclusion: Our findings provide evidence that maintenance antipsychotics on SCZ is beneficial for the improvement of DMN-EAS competitive imbalance, which may partly contribute to the efficient relapse prevention of this severe mental disorder.

Increased ventral striatal functional connectivity in patients with schizophrenia during reward anticipation

Background

Growing evidence points towards dysfunction of the ventral striatum as a neural substrate of motivational impairments in schizophrenia. Ventral striatal activity during reward anticipation is generally reduced in patients with schizophrenia and specifically correlates with apathy. However, little is known about the cortico-striatal functional connectivity in patients with schizophrenia during reward anticipation and its relation to negative symptoms.

Objectives

The aim of this study was to identify categorical group differences in ventral striatal functional connectivity during reward anticipation between patients with schizophrenia and healthy controls, and dimensional associations between cortico-striatal functional connectivity and negative symptom severity.

Method

A total of 40 patients with schizophrenia (10 females) and 33 healthy controls (8 females) were included from two previously published studies. All participants performed a variant of the Monetary Incentive Delay Task while undergoing event-related fMRI. Functional connectivity was assessed using psychophysical interactions (PPI) with the left and right ventral striatum as seeds and the contrast [High Reward Anticipation – No Reward Anticipation]. Negative symptoms were assessed using the Brief Negative Symptom Scale.

Results

Compared to controls, patients with schizophrenia showed increased functional connectivity between the left ventral striatum and the left precuneus and right parahippocampal gyrus, two hubs of the default mode network (cluster-level threshold: FWE, p < .05). In addition, we found a negative association between apathy scores on the BNSS and increased functional connectivity between the left ventral striatum and the left ventral anterior insula / putamen and the left inferior frontal gyrus / dorsal anterior insula (cluster-level threshold: FWE, p < .05).

Conclusions

Our results indicate that the patterns of increased functional connectivity between the ventral striatum and the dorsal default mode network during reward anticipation could act as a compensatory mechanism to regulate the activity of the ventral striatum. Our results also showed that functional connectivity patterns from the ventral striatum, much like its local activity, is specifically related to apathy, and not diminished expression.

Cortical thickness across the cingulate gyrus in schizophrenia and its association to illness duration and memory performance

Schizophrenia has been associated with structural brain abnormalities and cognitive deficits that partly change during the course of illness. In the present study, cortical thickness in five subregions of the cingulate gyrus was assessed in 44 patients with schizophrenia-spectrum disorder and 47 control persons and related to illness duration and memory capacities. In the patients group, cortical thickness was increased in the posterior part of the cingulate gyrus and related to illness duration whereas cortical thickness was decreased in anterior parts unrelated to illness duration. In contrast, cortical thickness was related to episodic and working memory performance only in the anterior but not posterior parts of the cingulate gyrus. Our finding of a posterior cingulate increase may point to either increased parietal communication that is accompanied by augmented neural plasticity or to effects of altered neurodegenerative processes in schizophrenia.

Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation

BACKGROUND

Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls.

METHODS

We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.

RESULTS

Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus.

CONCLUSION

Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].

DNA Methylation Basis in the Effect of White Matter Integrity Deficits on Cognitive Impairments and Psychopathological Symptoms in Drug-Naive First-Episode Schizophrenia

Background: Mounting evidence from diffusion tensor imaging (DTI) and epigenetic studies, respectively, confirmed the abnormal alterations of brain white matter integrity and DNA methylation (DNAm) in schizophrenia. However, few studies have been carried out in the same sample to simultaneously explore the WM pathology relating to clinical behaviors, as well as the DNA methylation basis underlying the WM deficits. Methods: We performed DTI scans in 42 treatment-naïve first-episode schizophrenia patients and 38 healthy controls. Voxel-based method of fractional anisotropy (FA) derived from DTI was used to assess WM integrity. Participants' peripheral blood genomic DNAm status, quantified by using Infinium® Human Methylation 450K BeadChip, was examined in parallel with DTI scanning. Participants completed Digit Span test and Trail Making test, as well as Positive and Negative Syndrome Scale measurement. We acquired genes that are differentially expressed in the brain regions with abnormal FA values according to the Allen anatomically comprehensive atlas, obtained DNAm levels of the corresponding genes, and then performed Z-test to compare the differential epigenetic-imaging associations (DEIAs) between the two groups. Results: Significant decreases of FA values in the patient group were in the right middle temporal lobe WM, right cuneus WM, right anterior cingulate WM, and right inferior parietal lobe WM, while the significant increases were in the bilateral middle cingulate WM (Ps < 0.01, GRF correction). Abnormal FA values were correlated with patients' clinical symptoms and cognitive impairments. In the DEIAs, patients showed abnormal couple patterns between altered FA and DNAm components, for which the enriched biological processes and pathways could be largely grouped into three biological procedures: the neurocognition, immune, and nervous system. Conclusion: Schizophrenia may not cause widespread neuropathological changes, but subtle alterations affecting local cingulum WM, which may play a critical role in positive symptoms and cognitive impairments. This imaging-epigenetics study revealed for the first time that DNAm of genes enriched in neuronal, immunologic, and cognitive processes may serve as the basis in the effect of WM deficits on clinical behaviors in schizophrenia.

Functional connectivity of the anterior cingulate cortex with pain-related regions in children with post-traumatic headache

Introduction:

Post-traumatic headaches (PTH) are common following mild traumatic brain injury (mTBI). There is evidence of altered central pain processing in adult PTH; however, little is known about how children with PTH process pain. The anterior cingulate cortex (ACC) plays a critical role in descending central pain modulation. In this study, we explored whether the functional connectivity (FC) of the ACC is altered in children with PTH.

Methods:

In this case-control study, we investigated resting-state FC of 5 ACC seeds (caudal, dorsal, rostral, perigenual, and subgenual) in children with PTH ( n = 73) and without PTH ( n = 29) following mTBI, and healthy controls ( n = 27). Post-concussion symptoms were assessed using the Post-Concussion Symptom Inventory and the Child Health Questionnaire. Resting-state functional Magnetic Resonance Imaging (fMRI) data were used to generate maps of ACC FC. Group-level comparisons were performed within a target mask comprised of pain-related regions using FSL Randomise.

Results:

We found decreased FC between the right perigenual ACC and the left cerebellum, and increased FC between the right subgenual ACC and the left dorsolateral prefrontal cortex in children with PTH compared to healthy controls. The ACC FC in children without PTH following mTBI did not differ from the group with PTH or healthy controls. FC between rostral and perigenual ACC seeds and the cerebellum was increased in children with PTH with pre-injury headaches compared to those with PTH without pre-injury headaches. There was a positive relationship between PTH severity and rostral ACC FC with the bilateral thalamus, right hippocampus and periaqueductal gray.

Conclusions:

Central pain processing is altered in children with PTH. Pre-existing headaches help to drive this process.

Trial registration:

The PlayGame Trial was registered in ClinicalTrials.gov database ( ClinicalTrials.gov Identifier: NCT01874847).

Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized. Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects. Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity. Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Advanced Signal Processing Methods for Characterization of Schizophrenia

OBJECTIVE

Schizophrenia is a severe mental disorder associated with nerobiological deficits. Auditory oddball P300 have been found to be one of the most consistent markers of schizophrenia. The goal of this study is to find quantitative features that can objectively distinguish patients with schizophrenia (SCZs) from healthy controls (HCs) based on their recorded auditory odd-ball P300 electroencephalogram (EEG) data.

METHODS

Using EEG dataset, we develop a machine learning (ML) algorithm to distinguish 57 SCZs from 66 HCs. The proposed ML algorithm has three steps. In the first step, a brain source localization (BSL) procedure using the linearly constrained minimum variance (LCMV) beamforming approach is employed on EEG signals to extract source waveforms from 30 specified brain regions. In the second step, a method for estimating effective connectivity, referred to as symbolic transfer entropy (STE), is applied to the source waveforms. In the third step the ML algorithm is applied to the STE connectivity matrix to determine whether a set of features can be found that successfully discriminate SCZ from HC.

RESULTS

The findings revealed that the SCZs have significantly higher effective connectivity compared to HCs and the selected STE features could achieve an accuracy of 92.68%, with a sensitivity of 92.98% and specificity of 92.42%.

CONCLUSION

The findings imply that the extracted features are from the regions that are mainly affected by SCZ and can be used to distinguish SCZs from HCs.

SIGNIFICANCE

The proposed ML algorithm may prove to be a promising tool for the clinical diagnosis of schizophrenia.

Altered Functional Connectivity of the Nucleus Accumbens Network Between Deficit and Non-deficit Schizophrenia

Deficit schizophrenia (DS), which is marked by stable negative symptoms, is regarded as a homogeneous subgroup of schizophrenia. While DS patients have structurally altered nucleus accumbens (NAcc) compared to non-deficit schizophrenia (NDS) patients and healthy individuals, the investigation of NAcc functional connectivity (FC) with negative symptoms and neurocognition could provide insights into the pathophysiology of schizophrenia. 58 DS, 93 NDS, and 113 healthy controls (HCs) underwent resting-state functional magnetic resonance (rsfMRI). The right and left NAcc were respectively used as seed points to construct the functional NAcc network in whole-brain FC analysis. ANCOVA compared the differences in NAcc network FC and partial correlation analysis explored the relationships between altered FC of NAcc, negative symptoms and neurocognition. Compared to HCs, both DS and NDS patients showed decreased FC between the left NAcc (LNAcc) and bilateral middle cingulate gyrus, and between the right NAcc (RNAcc) and right middle frontal gyrus (RMFG), as well as increased FC between bilateral NAcc and bilateral lingual gyrus. Moreover, the FC between the LNAcc and bilateral calcarine gyrus (CAL) was lower in the DS group compared to NDS patients. Correlation analysis indicated that FC value of LNAcc-CAL was negatively correlated to negative symptoms. Furthermore, aberrant FC values within the NAcc network were correlated with severity of clinical symptoms and neurocognitive impairments in DS and NDS patients. This study demonstrated abnormal patterns of FC in the NAcc network between DS and NDS. The presence of altered LNAcc-CAL FC might be involved in the pathogenesis of negative symptoms in schizophrenia.

Organized Resting-state Functional Dysconnectivity of the Prefrontal Cortex in Patients with Schizophrenia

Schizophrenia has prominent functional dysconnectivity, especially in the prefrontal cortex (PFC). However, it is unclear whether in the same group of patients with schizophrenia, PFC functional dysconnectivity appears in an organized manner or is stochastically located in different subregions. By investigating the resting-state functional connectivity (rsFC) of each PFC subregion from the Brainnetome atlas in 40 schizophrenia patients and 40 healthy subjects, we found 24 altered connections in schizophrenia, and the connections were divided into four categories by a clustering analysis: increased connections within the PFC, increased connections between the inferior PFC and the thalamus/striatum, reduced connections between the PFC and the motor control areas, and reduced connections between the orbital PFC and the emotional perception regions. In addition, the four categories of rsFC showed distinct cognitive engagement patterns. Our findings suggest that PFC subregions have specific functional dysconnectivity patterns in schizophrenia and may reflect heterogeneous symptoms and cognitive deficits in schizophrenia.

Altered brain function and clinical features in patients with first-episode, drug naïve major depressive disorder: A resting-state fMRI study

Major depressive disorder (MDD) is characterized by heterogeneous clinical performance and neurocognitive impairment. It is important to explore the correlation between global functioning and regional homogeneity (ReHo)/amplitude of low-frequency fluctuation (ALFF) values in MDD patients. 67 first-episode, drug naïve MDD patients and 69 healthy subjects were enrolled in the study. The MATRICS Consensus Cognitive Battery (MCCB) and the Functioning Assessment Short Test (FAST) were used to assess functional impairment in patients. Brain activity was assessed using ReHo and ALFF measurements. The relationship between the clinical features and altered brain function was evaluated using correlation analysis. There were significant differences in the ReHo and ALFF values between MDD patients and healthy subjects. The reduction in ReHo in the left calcarine/lingual gyrus/cuneus was negatively correlated with occupational functioning and the total FAST scores. The reduction in ALFF in the right calcarine/lingual gyrus was positively correlated with the verbal learning aspects of the MCCB. These findings suggest that the altered brain function in the default mode network (DMN) may be related to functional impairments in patients with first-episode, drug naïve major depressive disorder.

Autonomic modulation networks in schizophrenia: The relationship between heart rate variability and functional and structural connectivity in the brain

Heart rate variability (HRV), a measurement of autonomic nervous system (ANS) activity, has been found reduced in schizophrenia. The anterior cingulate cortex (ACC), which is important in regulating the ANS, is structurally and functionally affected in schizophrenia. We investigate the relationship between HRV and functional and structural connectivity of the ACC in patients with schizophrenia and healthy controls. Ten patients with a diagnosis of schizophrenia and ten healthy controls were recruited. Heart rate was monitored in a naturalistic out-of-clinic setting. Magnetic resonance imaging (MRI) was performed, including resting-state functional MRI and diffusion tensor imaging. Patients with schizophrenia had significantly lower HRV compared to controls. A positive correlation between ACC connectivity with the bilateral cerebellum and HRV was found in the patients. HRV was also positively correlated with amplitude of low frequency fluctuations (ALFF) in the cerebellum, and with axial diffusivity in the middle cerebellar peduncle, in the patients. There was a significant negative relationship between antipsychotic medication dosage, HRV and all neuroimaging measures related to HRV. We conclude that ACC connectivity seems to be affected in schizophrenia, both structurally and functionally, and that the ACC-cerebellum connectivity, as well as cerebellar function, is associated with ANS regulation in patients with schizophrenia.

Effects of risperidone monotherapy on the default-mode network in antipsychotic-naïve first-episode schizophrenia: Posteromedial cortex heterogeneity and relationship with the symptom improvements

The default mode network (DMN) has been consistently detected abnormally in schizophrenia. However, the effects of antipsychotics on this network are still under debate, and inconsistent findings may be due to the functional heterogeneity within the DMN, especially in the component regions of the posteromedial cortex (PMC). Here, we conducted a longitudinal research on the resting-state functional connectivity of the PMC subdivisions on 33 treatment-naive first-episode patients with schizophrenia at baseline and after 8 weeks of risperidone treatment through resting-state functional magnetic resonance imaging. At baseline, the patients demonstrated decreased connectivity of the three PMC seeds with several brain regions (target regions) compared with healthy controls. We then tested the effect of antipsychotic treatment on the functional connectivity between the three seeds and the target regions. We found that, one of the three seeds encompassed in PMC, namely, posterior cingulate cortex (PCC), was observed to have increased functional connectivity with the bilateral thalamus and the left lingual gyrus (LG). On the contrary, the functional connectivity between the target regions and the two remaining seeds, namely, the retrosplenial cortex and precuneus, was unaffected by risperidone treatment. Correlation analysis revealed a positive correlation between longitudinal change of PCC-LG connectivity and symptom improvement. These findings indicated the heterogeneity of the PMC in response to antipsychotic treatment and suggested the role of PCC as a treatment biomarker for schizophrenia.

Anterior Hippocampal-Cortical Functional Connectivity Distinguishes Antipsychotic Naïve First-Episode Psychosis Patients From Controls and May Predict Response to Second-Generation Antipsychotic Treatment

BACKGROUND

Converging evidence implicates the anterior hippocampus in the proximal pathophysiology of schizophrenia. Although resting state functional connectivity (FC) holds promise for characterizing anterior hippocampal circuit abnormalities and their relationship to treatment response, this technique has not yet been used in first-episode psychosis (FEP) patients in a manner that distinguishes the anterior from posterior hippocampus.

METHODS

We used masked-hippocampal-group-independent component analysis with dual regression to contrast subregional hippocampal-whole brain FC between healthy controls (HCs) and antipsychotic naïve FEP patients (N = 61, 36 female). In a subsample of FEP patients (N = 27, 15 female), we repeated this analysis following 8 weeks of second-generation antipsychotic treatment and explored whether baseline FC predicted treatment response using random forest.

RESULTS

Relative to HC, untreated FEP subjects displayed reproducibly lower FC between the left anteromedial hippocampus and cortical regions including the anterior cingulate and insular cortex (P < .05, corrected). Anteromedial hippocampal FC increased in FEP patients following treatment (P < .005), and no longer differed from HC. Random forest analysis showed baseline anteromedial hippocampal FC with four brain regions, namely the insular-opercular cortex, superior frontal gyrus, precentral gyrus, and postcentral gyrus predicted treatment response (area under the curve = 0.95).

CONCLUSIONS

Antipsychotic naïve FEP is associated with lower FC between the anterior hippocampus and cortical regions previously implicated in schizophrenia. Preliminary analysis suggests that random forest models based on hippocampal FC may predict treatment response in FEP patients, and hence could be a useful biomarker for treatment development.

Diagnosing schizophrenia with network analysis and a machine learning method

OBJECTIVE

Schizophrenia is a chronic and debilitating neuropsychiatric disorder. It has been suggested that impaired brain connectivity underlies the pathophysiology of schizophrenia. Network analysis has thus recently emerged in the field of schizophrenia research.

METHODS

We investigated 48 schizophrenia patients and 24 healthy controls using network analysis and a machine learning method. A number of global and nodal network properties were estimated from graphs that were reconstructed using probabilistic brain tractography. These network properties were then compared between groups and used for machine learning to classify schizophrenia patients and healthy controls.

RESULTS

In classifying schizophrenia patients and healthy controls via network properties, the support vector machine, random forest, naïve Bayes, and gradient boosting machine learning models showed an encouraging level of performance. The overall connectivity was revealed as the most significant contributing feature to this classification among the global network properties. Among the nodal network properties, although the relative importance of each region of interest was not identical, there were still some patterns.

CONCLUSION

In conclusion, the possibility exists to classify schizophrenia patients and healthy controls using network properties, and we have found that there is a provisional pattern of involved brain regions among patients with schizophrenia.

Network functional connectivity analysis in individuals at ultrahigh risk for psychosis and patients with schizophrenia

Schizophrenia is a severe mental disorder, and the onset of which is preceded by a stage of ultrahigh risk (UHR) for developing psychosis. Therefore, analyzing individuals with UHR is essential for identifying predictive biomarkers for the onset of schizophrenia. The current study aimed to identify such biomarkers based on a voxelwise whole-brain functional degree centrality (FDC) analysis. Conjunction analysis showed that, compared with healthy controls, both UHR subjects and patients with schizophrenia showed significantly increased FDC at the medial prefrontal cortex (MPFC) and significantly decreased FDC at the right fusiform gyrus (FG). The subsequent partial correlation analysis showed significant correlations between the disorganization symptoms and FDCs at the MPFC and the right FG for both UHR subjects and patients with schizophrenia. These findings suggest that FDC within the MPFC and the right FG could be candidate biomarkers for the onset of schizophrenia.

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity

Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.

N-Acetyl-Cysteine Supplementation Improves Functional Connectivity Within the Cingulate Cortex in Early Psychosis: A Pilot Study

BACKGROUND

There is increasing evidence that redox dysregulation, which can lead to oxidative stress and eventually to impairment of oligodendrocytes and parvalbumin interneurons, may underlie brain connectivity alterations in schizophrenia. Accordingly, we previously reported that levels of brain antioxidant glutathione in the medial prefrontal cortex were positively correlated with increased functional connectivity along the cingulum bundle in healthy controls but not in early psychosis patients. In a recent randomized controlled trial, we observed that 6-month supplementation with a glutathione precursor, N-acetyl-cysteine, increased brain glutathione levels and improved symptomatic expression and processing speed.

METHODS

We investigated the effect of N-acetyl-cysteine supplementation on the functional connectivity between regions of the cingulate cortex, which have been linked to positive symptoms and processing speed decline. In this pilot study, we compared structural connectivity and resting-state functional connectivity between early psychosis patients treated with 6-month N-acetyl-cysteine (n = 9) or placebo (n = 11) supplementation with sex- and age-matched healthy control subjects (n = 74).

RESULTS

We observed that 6-month N-acetyl-cysteine supplementation increases functional connectivity along the cingulum and more precisely between the caudal anterior part and the isthmus of the cingulate cortex. These functional changes can be partially explained by an increase of centrality of these regions in the functional brain network.

CONCLUSIONS

N-acetyl-cysteine supplementation has a positive effect on functional connectivity within the cingulate cortex in early psychosis patients. To our knowledge, this is the first study suggesting that increased brain glutathione levels via N-acetyl-cysteine supplementation may improve brain functional connectivity.

Common and distinct changes of default mode and salience network in schizophrenia and major depression

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study

Multimodal, imaging-genomics techniques offer a platform for understanding genetic influences on brain abnormalities in psychiatric disorders. Such approaches utilize the information available from both imaging and genomics data and identify their association. Particularly for complex disorders such as schizophrenia, the relationship between imaging and genomic features may be better understood by incorporating additional information provided by advanced multimodal modeling. In this study, we propose a novel framework to combine features corresponding to functional magnetic resonance imaging (functional) and single nucleotide polymorphism (SNP) data from 61 schizophrenia (SZ) patients and 87 healthy controls (HC). In particular, the features for the functional and genetic modalities include dynamic (i.e., time-varying) functional network connectivity (dFNC) features and the SNP data, respectively. The dFNC features are estimated from component time-courses, obtained using group independent component analysis (ICA), by computing sliding-window functional network connectivity, and then estimating subject specific states from this dFNC data using a k-means clustering approach. For each subject, both the functional (dFNC states) and SNP data are selected as features for a parallel ICA (pICA) based imaging-genomic framework. This analysis identified a significant association between a SNP component (defined by large clusters of functionally related SNPs statistically correlated with phenotype components) and time-varying or dFNC component (defined by clusters of related connectivity links among distant brain regions distributed across discrete dynamic states, and statistically correlated with genomic components) in schizophrenia. Importantly, the polygenetic risk score (PRS) for SZ (computed as a linearly weighted sum of the genotype profiles with weights derived from the odds ratios of the psychiatric genomics consortium (PGC)) was negatively correlated with the significant dFNC component, which were mostly present within a state that exhibited a lower occupancy rate in individuals with SZ compared with HC, hence identifying a potential dFNC imaging biomarker for schizophrenia. Taken together, the current findings provide preliminary evidence for a link between dFNC measures and genetic risk, suggesting the application of dFNC patterns as biomarkers in imaging genetic association study.

Motor dysfunction as research domain across bipolar, obsessive-compulsive and neurodevelopmental disorders

Although genuine motor abnormalities (GMA) are frequently found in schizophrenia, they are also considered as an intrinsic feature of bipolar, obsessive-compulsive, and neurodevelopmental disorders with early onset such as autism, ADHD, and Tourette syndrome. Such transnosological observations strongly suggest a common neural pathophysiology. This systematic review highlights the evidence on GMA and their neuroanatomical substrates in bipolar, obsessive-compulsive, and neurodevelopmental disorders. The data lends support for a common pattern contributing to GMA expression in these diseases that seems to be related to cerebello-thalamo-cortical, fronto-parietal, and cortico-subcortical motor circuit dysfunction. The identified studies provide first evidence for a motor network dysfunction as a correlate of early neurodevelopmental deviance prior to clinical symptom expression. There are also first hints for a developmental risk factor model of these mental disorders. An in-depth analysis of motor networks and related patho-(physiological) mechanisms will not only help promoting Research Domain Criteria (RDoC) Motor System construct, but also facilitate the development of novel psychopharmacological models, as well as the identification of neurobiologically plausible target sites for non-invasive brain stimulation.

Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity

Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).

Brain Structures Associated with Internet Addiction Tendency in Adolescent Online Game Players

With the development of the Internet, an increasing number of adolescents play online game excessively, which leads to adverse effects on individuals and society. Previous studies have demonstrated altered gray-matter volume (GMV) in individuals with Internet gaming disorder (IGD), but the relationship between the tendency to IGD and the GMV across whole brain is still unclear in adolescents. In the present study, anatomical imaging with high resolution was performed on 67 male adolescents who played online game; and Young's Internet addiction test (IAT) was conducted to test the tendency to IGD. FMRIB Software Library (FSL) was used to calculate the voxel-based correlations between the GMV and the IAT score after controlling for the age and years of education. The GMVs of the bilateral postcentral gyri (postCG), the bilateral precentral gyri (preCG), the right precuneus, the left posterior midcingulate cortex (pMCC), the left inferior parietal lobe (IPL), and the right middle frontal gyrus (MFG) were negatively correlated with the IAT score. The correlation still existed between the IAT score and the GMVs of the bilateral postCG, the left preCG, the left pMCC, and the right MFG after controlling for the total time of playing online game. When the participants were divided into two groups according to the IAT score, the GMVs of these IAT-related brain regions were lower in high IAT score subgroup (IAT score >50) than in low IAT score subgroup (IAT score ≤50). Our results suggested that the GMVs of brain regions involved in sensorimotor process and cognitive control were associated with the IGD tendency. These findings may lead to new targets for preventing and treating the IGD.

Cortical Gray Matter Loss, Augmented Vulnerability to Speech-on-Speech Masking, and Delusion in People With Schizophrenia

People with schizophrenia exhibit impairments in target-speech recognition (TSR) against multiple-talker-induced informational speech masking. Up to date, the underlying neural mechanisms and its relationships with psychotic symptoms remain largely unknown. This study aimed to investigate whether the schizophrenia-associated TSR impairment contribute to certain psychotic symptoms by sharing underlying alternations in cortical gray-matter volume (GMV) with the psychotic symptoms. Participants with schizophrenia (N = 34) and their matched healthy controls (N = 29) were tested for TSR against a two-talker-speech masker. Psychotic symptoms of participants with schizophrenia were evaluated using the Positive and Negative Syndrome Scale. The regional GMV across various cortical regions was assessed using the voxel-based morphometry. The results of partial-correlation and mediation analyses showed that in participants with schizophrenia, the TSR was negatively correlated with the delusion severity, but positively with the GMV in the bilateral superior/middle temporal cortex, bilateral insular, left medial orbital frontal gyrus, left Rolandic operculum, left mid-cingulate cortex, left posterior fusiform, and left cerebellum. Moreover, the association between GMV and delusion was based on the mediating role played by the TSR performance. Thus, in people with schizophrenia, both delusions and the augmented vulnerability of TSR to informational masking are associated with each other and share the underlying cortical GMV reduction, suggesting that the origin of delusion in schizophrenia may be related to disorganized or limited informational processing (e.g., the incapability of adequately filtering information from multiple sources at the perceptual level). The TSR impairment can be a potential marker for predicting delusion severity.

Effect of rs1344706 in the ZNF804A gene on the brain network

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = − 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia.

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This study was the first to report the effect of ZNF804A rs1344706 on the property of the whole-brain network.

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We found a significant interaction of rs1344706 genotype × diagnosis on the functional connectivity of the PCU.

Altered Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Schizophrenia

BACKGROUND

Respective changes in resting-state cerebral blood flow (CBF) and functional connectivity in schizophrenia have been reported. However, their coupling alterations in schizophrenia remain largely unknown.

METHODS

89 schizophrenia patients and 90 sex- and age-matched healthy controls underwent resting-state functional MRI to calculate functional connectivity strength (FCS) and arterial spin labeling imaging to compute CBF. The CBF-FCS coupling of the whole gray matter and the CBF/FCS ratio (the amount of blood supply per unit of connectivity strength) of each voxel were compared between the 2 groups.

RESULTS

Whole gray matter CBF-FCS coupling was decreased in schizophrenia patients relative to healthy controls. In schizophrenia patients, the decreased CBF/FCS ratio was predominantly located in cognitive- and emotional-related brain regions, including the dorsolateral prefrontal cortex, insula, hippocampus and thalamus, whereas an increased CBF/FCS ratio was mainly identified in the sensorimotor regions, including the putamen, and sensorimotor, mid-cingulate and visual cortices.

CONCLUSION

These findings suggest that the neurovascular decoupling in the brain may be a possible neuropathological mechanism of schizophrenia.

Selective functional disconnection of the orbitofrontal subregions in schizophrenia

BACKGROUND

As a disconnection syndrome, schizophrenia has shown impaired resting-state functional connectivity (rsFC) in the orbitofrontal cortex (OFC); however, the OFC is a rather heterogeneous region and the rsFC changes in the OFC subregions remain unknown.

METHOD

A total of 98 schizophrenia patients and 102 healthy controls underwent resting-state functional MRI using a sensitivity-encoded spiral-in imaging sequence (SENSE-SPIRAL) to reduce susceptibility-induced signal loss and distortion. The OFC subregions were defined according to a previous parcellation study that divided the OFC into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. The rsFC was compared using two-way repeated-measures ANOVA.

RESULTS

Whether or not global signal regression, compared with healthy controls, schizophrenia patients consistently exhibited decreased rsFC between the left OFCi and the left middle temporal gyrus and the right middle frontal gyrus (MFG), between the right OFCi and the right MFG and the left inferior frontal gyrus, between the right OFCm and the middle cingulate cortex and the left Rolandic operculum. These rsFC changes still remained significant even after cortical atrophy correction.

CONCLUSIONS

These findings suggest a selective functional disconnection of the OFC subregions in schizophrenia, and provide more precise information about the functional disconnections of the OFC in this disorder.

Nicotinic modulation of salience network connectivity and centrality in schizophrenia

Although functional abnormalities of the salience network are associated with schizophrenia, the acute effects of nicotine on its function and network dynamics during the resting state in patients are poorly understood. In this study, the effects of a 7 mg nicotine patch (vs. placebo) on salience network connectivity were examined in 17 patients with schizophrenia and 19 healthy subjects. We hypothesized abnormal connectivity between the salience network and other major networks (e.g. executive network) in patients under placebo administration and amelioration of this difference after nicotine. We also examined effects of nicotine on betweenness centrality (a measure of the influence of a region on information transfer throughout the brain) and local efficiency (a measure of local information transfer) of the network. A hybrid independent component analysis (ICA)/seed-based connectivity approach was implemented in which the salience network was extracted by ICA and cortical network peaks (anterior cingulate cortex (ACC), left and right insula) were used as seeds for whole-brain seed-to-voxel connectivity analysis. Significant drug X diagnosis interactions were observed between the ACC seed and superior parietal lobule and ventrolateral prefrontal cortex. A significant interaction effect was also observed between the left insula seed and middle cingulate cortex. During placebo conditions, abnormal connectivity predicted negative symptom severity and lower global functioning in patients. A significant drug X diagnosis interaction was also observed for betweenness centrality of the ACC. These results suggest that nicotine may target abnormalities in functional connectivity between salience and executive network areas in schizophrenia as well as affect the ability of the salience network to act as an integrator of global signaling in the disorder.

Combination of volume and perfusion parameters reveals different types of grey matter changes in schizophrenia

Diverse brain structural and functional changes have been reported in schizophrenia. Identifying different types of brain changes may help to understand the neural mechanisms and to develop reliable biomarkers in schizophrenia. We aimed to categorize different grey matter changes in schizophrenia based on grey matter volume (GMV) and cerebral blood flow (CBF). Structural and perfusion magnetic resonance imaging data were acquired in 100 schizophrenia patients and 95 healthy comparison subjects. Voxel-based GMV comparison was used to show structural changes, CBF analysis was used to demonstrate functional changes. We identified three types of grey matter changes in schizophrenia: structural and functional impairments in the anterior cingulate cortex and insular cortex, displaying reduction in both GMV and CBF; structural impairment with preserved function in the frontal and temporal cortices, demonstrating decreased GMV with normal CBF; pure functional abnormality in the anterior cingulate cortex and lateral prefrontal cortex and putamen, showing altered CBF with normal GMV. By combination of GMV and CBF, we identified three types of grey matter changes in schizophrenia. These findings may help to understand the complex manifestations and to develop reliable biomarkers in schizophrenia.

Morphometric analysis of the cerebral expression of ATP-binding cassette transporter protein ABCB1 in chronic schizophrenia: Circumscribed deficits in the habenula

There is increasing evidence that microvascular abnormalities and malfunction of the blood-brain barrier (BBB) significantly contribute to schizophrenia pathophysiology. The ATP-binding cassette transporter ABCB1 is an important molecular component of the intact BBB, which has been implicated in a number of neurodegenerative and psychiatric disorders, including schizophrenia. However, the regional and cellular expression of ABCB1 in schizophrenia is yet unexplored. Therefore, we studied ABCB1 protein expression immunohistochemically in twelve human post-mortem brain regions known to play a role in schizophrenia, in 13 patients with schizophrenia and nine controls. In ten out of twelve brain regions under study, no significant differences were found with regard to the numerical density of ABCB1-expressing capillaries between all patients with schizophrenia and control cases. The left and right habenular complex, however, showed significantly reduced capillary densities in schizophrenia patients. In addition, we found a significantly reduced density of ABCB1-expressing neurons in the left habenula. Reduced ABCB1 expression in habenular capillaries might contribute to increased brain levels of proinflammatory cytokines in patients with schizophrenia, while decreased expression of this protein in a subpopulation of medial habenular neurons (which are probably purinergic) might be related to abnormalities of purines and their receptors found in this disease.

Proteomic analysis of the postsynaptic density implicates synaptic function and energy pathways in bipolar disorder

The postsynaptic density (PSD) contains a complex set of proteins of known relevance to neuropsychiatric disorders such as schizophrenia and bipolar disorder. We enriched for this anatomical structure in the anterior cingulate cortex of 16 bipolar disorder samples and 20 controls from the Stanley Medical Research Institute. Unbiased shotgun proteomics incorporating label-free quantitation was used to identify differentially expressed proteins. Quantitative investigation of the PSD identified 2033 proteins, among which 288 were found to be differentially expressed. Validation of expression changes of DNM1, DTNA, NDUFV2, SEPT11 and SSBP was performed by western blotting. Bioinformatics analysis of the differentially expressed proteins implicated metabolic pathways including mitochondrial function, the tricarboxylic acid cycle, oxidative phosphorylation, protein translation and calcium signaling. The data implicate PSD-associated proteins, and specifically mitochondrial function in bipolar disorder. They relate synaptic function in bipolar disorder and the energy pathways that underpin it. Overall, our findings add to a growing literature linking the PSD and mitochondrial function in psychiatric disorders generally, and suggest that mitochondrial function associated with the PSD is particularly important in bipolar disorder.