Convergence and Divergence of Brain Network Dysfunction in Deficit and Non-deficit Schizophrenia

Diminished functional segregation and resilience are associated with symptomatic severity and cognitive impairments in schizophrenia: a large-scale study

Background

The research findings on the topological properties of functional connectomes (TP-FCs) in patients with schizophrenia (SZPs) exhibit inconsistencies and contradictions, which can be attributed to limitations such as small sample sizes and heterogeneous data processing techniques.

Aims

To address these limitations, we conducted a large-scale study. Uniform data processing flows were employed to investigate the aberrant TP-FCs and the associations between TP-FCs and symptoms or cognitions (A-TP-SCs) in SZPs.

Methods

The large-scale study included six datasets from four sites, involving 497 SZPs and 374 healthy controls (HCs). A uniform process for imaging data preprocessing and functional connectivity matrix configuration was used. ComBat was employed for data harmonisation, and various TPs were calculated. We explored between-group differences in brain functional integration (FI) and functional segregation (FS) measured with TP-FCs, and conducted partial correlation analyses, with adjustments for age, gender and educational level, to identify A-TP-SCs.

Results

Compared with random networks and HCs, SZPs maintained small-worldness and global FI capacity despite their compromised global FS capacity and resilience. A decline in nodal FI and FS capacity was observed in sensory areas, whereas an increase in nodal FI capacity was found in regions associated with cognition and information integration. In addition, associations between TP-FCs and positive symptoms, negative symptoms or cognitive functions including speed of processing, visual learning and the ability to inhibit cognitive interference were identified in SZPs.

Conclusions

The identified A-TP-SCs verified that reductions in FS and resilience indicated pathological impairments in schizophrenia. The A-TP-SCs or TP-FCs, which measured the same attributes of the functional connectomes, exhibited high internal consistency, robustly reinforcing these findings.

Aberrant brain functional connectivity mediates the effects of negative symptoms on cognitive function in schizophrenia: A structural equation model

BACKGROUND

Schizophrenia is a severe psychiatric disorder, characterized by positive symptoms, negative symptoms, and cognitive deficits. Elucidating the mechanism of negative symptom and cognitive deficits could contribute to the treatment and prognosis of schizophrenia. We hypothesized that abnormal functional connectivity would be involved in the indirect effects of negative symptoms on cognitive function.

METHODS

A total of 150 schizophrenia male patients and 108 healthy controls matched for age, education and gender were enrolled in the study. The scores of Brief Negative Symptom Scale were divided into two factors: motivation and pleasure deficits (MAP) and diminished expression (EXP). Subsequently, a series of classic neurocognitive tests were used to evaluate cognitive functions. Resting-state fMRI data was collected from all participants. The Anatomical Automatic Labeling template was employed to establish regions of interest, thereby constructing the functional connectivity network across the entire brain. Eventually, scores of patients' negative symptoms scale, cognitive function, and strengths of abnormal functional connectivity were incorporated into a structural equation model to explore the interactions among variables.

RESULTS

MAP exhibited a distinctly and significantly negative impact on cognitive function. The functional connectivity between the left insula and left precuneus, along with that between the left precuneus and right angular gyrus, collectively served as intermediaries, contributing to the indirect effects of MAP and EXP on cognitive function.

CONCLUSIONS

Our findings demonstrated the moderating role of aberrant brain functional connectivity between negative symptoms and cognitive function, providing clues about the neural correlates of negative symptoms and cognitive deficits in schizophrenia.

Topological Perturbations in the Functional Connectome Support the Deficit/Non-deficit Distinction in Antipsychotic Medication-Naïve First Episode Psychosis Patients

BACKGROUND

Heterogeneity in the etiology, pathophysiology, and clinical features of schizophrenia challenges clinicians and researchers. A helpful approach could be stratifying patients according to the presence or absence of clinical features of the deficit syndrome (DS). DS is characterized by enduring and primary negative symptoms, a clinically less heterogeneous subtype of the illness, and patients with features of DS are thought to present abnormal brain network characteristics, however, this idea has received limited attention. We investigated functional brain network topology in patients displaying deficit features and those who do not.

DESIGN

We applied graph theory analytics to resting-state functional magnetic resonance imaging data of 61 antipsychotic medication-naïve first episode psychosis patients, 18 DS and 43 non-deficit schizophrenia (NDS), and 72 healthy controls (HC). We quantified small-worldness, global and nodal efficiency measures, shortest path length, nodal local efficiency, and synchronization and contrasted them among the 3 groups.

RESULTS

DS presented decreased network integration and segregation compared to HC and NDS. DS showed lower global efficiency, longer global path lengths, and lower global local efficiency. Nodal efficiency was lower and the shortest path length was longer in DS in default mode, ventral attention, dorsal attention, frontoparietal, limbic, somatomotor, and visual networks compared to HC. Compared to NDS, DS showed lower efficiency and longer shortest path length in default mode, limbic, somatomotor, and visual networks.

CONCLUSIONS

Our data supports increasing evidence, based on topological perturbations of the functional connectome, that deficit syndrome may be a distinct form of the illness.

Altered patterns of dynamic functional connectivity of brain networks in deficit and non-deficit schizophrenia

This study aims to investigate the altered patterns of dynamic functional network connectivity (dFNC) between deficit schizophrenia (DS) and non-deficit schizophrenia (NDS), and further explore the associations with cognitive impairments. 70 DS, 91 NDS, and 120 matched healthy controls (HCs) were enrolled. The independent component analysis was used to segment the whole brain. The fMRI brain atlas was used to identify functional networks, and the dynamic functional connectivity (FC) of each network was detected. Correlation analysis was used to explore the associations between altered dFNC and cognitive functions. Four dynamic states were identified. Compared to NDS, DS showed increased FC between sensorimotor network and default mode network in state 1 and decreased FC within auditory network in state 4. Additionally, DS had a longer mean dwell time of state 2 and a shorter one in state 3 compared to NDS. Correlation analysis showed that fraction time and mean dwell time of states were correlated with cognitive impairments in DS. This study demonstrates the distinctive altered patterns of dFNC between DS and NDS patients. The associations with impaired cognition provide specific neuroimaging evidence for the pathogenesis of DS.

Altered white matter functional pathways in Alzheimer's disease

Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.

Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia

Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.

Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia

Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.

ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia

We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.

A neuromarker for deficit syndrome in schizophrenia from a combination of structural and functional magnetic resonance imaging

AIM

Deficit schizophrenia (DS), defined by primary and enduring negative symptoms, has been proposed as a promising homogeneous subtype of schizophrenia. It has been demonstrated that unimodal neuroimaging characteristics of DS were different from non-deficit schizophrenia (NDS), however, whether multimodal-based neuroimaging features could identify deficit syndrome remains to be determined.

METHODS

Functional and structural multimodal magnetic resonance imaging of DS, NDS and healthy controls were scanned. Voxel-based features of gray matter volume, fractional amplitude of low-frequency fluctuations, and regional homogeneity were extracted. The support vector machine classification models were constructed using these features separately and jointly. The most discriminative features were defined as the first 10% of features with the greatest weights. Moreover, relevance vector regression was applied to explore the predictive values of these top-weighted features in predicting negative symptoms.

RESULTS

The multimodal classifier achieved a higher accuracy (75.48%) compared with the single modal model in distinguishing DS from NDS. The most predictive brain regions were mainly located in the default mode and visual networks, exhibiting differences between functional and structural features. Further, the identified discriminative features significantly predicted scores of diminished expressivity factor in DS but not NDS.

CONCLUSIONS

The present study demonstrated that local properties of brain regions extracted from multimodal imaging data could distinguish DS from NDS with a machine learning-based approach and confirmed the relationship between distinctive features and the negative symptoms subdomain. These findings may improve the identification of potential neuroimaging signatures and improve the clinical assessment of the deficit syndrome.

Disrupted white matter structural networks in individuals with alcohol dependence

Previous diffusion tensor imaging (DTI) studies have demonstrated widespread white matter microstructure damage in individuals with alcoholism. However, very little is known about the alterations in the topological architecture of white matter structural networks in alcohol dependence (AD). This study included 67 AD patients and 69 controls. The graph theoretical analysis method was applied to examine the topological organization of the white matter structural networks, and network-based statistics (NBS) were employed to detect structural connectivity alterations. Compared to controls, AD patients exhibited abnormal global network properties characterized by increased small-worldness, normalized clustering coefficient, clustering coefficient, and shortest path length; and decreased global efficiency and local efficiency. Further analyses revealed decreased nodal efficiency and degree centrality in AD patients mainly located in the default mode network (DMN), including the precuneus, anterior cingulate and paracingulate gyrus, median cingulate and paracingulate gyrus, posterior cingulate gyrus, and medial part of the superior frontal gyrus. Furthermore, based on NBS approaches, patients displayed weaker subnetwork connectivity mainly located in the region of the DMN. Additionally, altered network metrics were correlated with intelligence quotient (IQ) scores and global assessment function (GAF) scores. Our results may reveal the disruption of whole-brain white matter structural networks in AD individuals, which may contribute to our comprehension of the underlying pathophysiological mechanisms of alcohol addiction at the level of white matter structural networks.

[Changes of brain network in patients with insomnia following radiotherapy for cervical cancer and their correlation with IT-TMS treatment efficacy: a graph-theory analysis]

OBJECTIVE

To analyze the changes of brain small-world and node function network properties in patients with insomnia following radiotherapy for cervical cancer based on graph theory analysis and explore the correlation between functional networks and the clinical efficacy of individual-target transcranial magnetic stimulation (IT-TMS) for treatment of insomnia.

METHODS

The resting state functional magnetic resonance imaging (rs-fMRI) data were collected from 30 patients with insomnia following radiotherapy for cervical cancer and 30 matched healthy individuals. All the patients received accelerated intelligent neuromodulation TMS therapy. Using graph theory analysis and GRETNA software, the functional connectivity matrices were constructed and the attribute features were extracted. The scores on the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) of the participants were collected before and after IT-TMS, and the correlation between improvement in insomnia and the functional network was investigated.

RESULTS

The two groups matched for age, gender, and education level (P>0.05) showed significant differences in PSQI, ISI, SAS and SDS scores (P<0.05). Both groups showed attributes of the small-world network. Compared with the healthy individuals, the patients showed significantly decreased σ, EI, Cp and Lp (P<0.05) and increased Eg (P<0.05) at baseline, which, along with insomnia symptoms, were all improved after IT-TMS treatment. The patients showed reduced functional connections of the node network at follow-up compared with the baseline, and the low functional connectivity between the right insula and left superior frontal gyrus was correlated with the improvement of ISI scores.

CONCLUSION

The patients with insomnia following radiotherapy for cervical cancer have impaired information integration ability of the brain network, IT-TMS can significantly improve insomnia symptoms by reducing the hyperconnectivity between the default mode network and the salience network.

The motivation and pleasure deficits but not expressivity affects social functioning through cognitive function in male patients with schizophrenia: A structural equation model

OBJECTIVE

This study aims to compare cognitive function and social functioning in male schizophrenia patients with deficit syndrome (DS) and non-DS, and to explore the associations among two different dimensions of negative symptoms (motivation and pleasure (MAP) and expressivity (EXP) deficits), cognitive function and social functioning base on a Structural Equation Model (SEM).

METHODS

The current study enrolled 161 male schizophrenia patients and 120 age- and education- matched healthy controls. The DS and non-DS group were categorized by the Chinese version of Schedule for the Deficit Syndrome (SDS). The psychotic and negative symptoms were evaluated by the Brief Psychiatric Rating Scale (BPRS) and the Brief Negative Symptoms Scale (BNSS). The Social functioning was measured by Scale of Social function in Psychosis Inpatients (SSPI). A battery of classical neurocognitive tests was used for assessing cognition including sustained vigilance/attention, cognitive flexibility, ideation fluency and visuospatial memory.

RESULTS

Our study indicated that DS patients performed worser in cognitive function and social functioning than non-DS patients. The SEM model demonstrated that MAP significantly affected social functioning through direct influence and mediation of cognitive function. However, our results found that EXP had little influence on cognitive function and social function.

CONCLUSION

Our findings provided evidence supporting that DS may represent as a subtype of schizophrenia, and the MAP factor play a pivotal role to influence the cognitive and social functioning in schizophrenia patients.

Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume

Objective

Schizophrenia can be divided into deficient schizophrenia (DS) and non-deficient schizophrenia (NDS) according to the presence of primary and persistent negative symptoms. So far, there are few studies that have explored the differences in functional connectivity (FC) between the different subtypes based on the region of interest (ROI) from GMV (Gray matter volume), especially since the characteristics of brain networks are still unknown. This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. Then, the relationships between the alterations and the clinical symptoms were analyzed. In addition, the thalamic functional connection imbalance in the two groups was further explored.

Methods

A total of 16 DS, 31 NDS, and 38 health controls (HC) underwent resting-state fMRI scans, patient group will further be evaluated by clinical scales including the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Scale for the Assessment of Positive Symptoms (SAPS). Based on GMV image data, a support vector machine (SVM) is used to classify DS and NDS. Brain regions with high weight in the classification were used as seed points in whole-brain FC analysis and thalamic FC imbalance analysis. Finally, partial correlation analysis explored the relationships between altered FC and clinical scale in the two subtypes.

Results

The relatively high classification accuracy is obtained based on the SVM. Compared to HC, the FC increased between the right inferior parietal lobule (IPL.R) bilateral thalamus, and lingual gyrus, and between the right inferior temporal gyrus (ITG.R) and the Salience Network (SN) in NDS. The FC between the right thalamus (THA.R) and Visual network (VN), between ITG.R and right superior occipital gyrus in the DS group was higher than that in HC. Furthermore, compared with NDS, the FC between the ITG.R and the left superior and middle frontal gyrus decreased in the DS group. The thalamic FC imbalance, which is characterized by frontotemporal-THA.R hypoconnectivity and sensory motor network (SMN)-THA.R hyperconnectivity was found in both subtypes. The FC value of THA.R and SMN was negatively correlated with the SANS score in the DS group but positively correlated with the SAPS score in the NDS group.

Conclusion

Using an SVM classification method and based on an ROI from GMV, we highlighted the difference in functional connectivity between DS and NDS from the local to the brain network, which provides new information for exploring the neural physiopathology of the two subtypes of schizophrenic.

The whole-brain connectome landscape in patients with schizophrenia: a systematic review and meta-analysis of graph theoretical characteristics

The alterations of connectome in schizophrenia have been reported, but the results remain inconsistent. We conducted a systematic review and random-effects meta-analysis on structural or functional connectome MRI studies comparing global graph theoretical characteristics between schizophrenia and healthy controls. Meta-regression and subgroup analyses were performed to examine confounding effects. Based on the included 48 studies, Structural connectome in schizophrenia showed a significant decrease in segregation (lower clustering coefficient and local efficiency, Hedge's g= -0.352 and -0.864, respectively) and integration (higher characteristic path length and lower global efficiency, Hedge's g= 0.532 and -0.577 respectively). The functional connectome showed no difference between groups except γ. Moderator analysis indicated that clinical and methodological factors exerted a potential effect on the graph theoretical characteristics. Our analysis revealed a weaker small-worldization trend in structural connectome of schizophrenia. For the relatively unchanged functional connectome, more homogenous and high-quality studies are warranted to elucidate whether the change was blurred by heterogeneity or the presentation of pathophysiological reconfiguration.

The genetic influence of the DRD3 rs6280 polymorphism (Ser9Gly) on functional connectivity and gray matter volume of the hippocampus in patients with first-episode, drug-naïve schizophrenia

The D3 dopamine receptor (DRD3) plays a major role in cognitive function and is a candidate gene for schizophrenia. DRD3 is widely distributed in the hippocampus, but whether there are potential associations between the rs6280 genotype, the hippocampus, and cognitive function in first-episode, drug-naïve (FES) patients and healthy controls (HCs) is still poorly understood. First, using functional and structural magnetic resonance imaging data, we calculated the gray matter volume (GMV) and functional connectivity (FC) of the hippocampus. Then, we examined the possible interaction effect of the DRD3 genotype and the disease on the FC and GMV of the hippocampus in 52 FES patients and 51 HCs. Finally, the correlation between the FC and GMV in the hippocampus, influenced by rs6280, and the cognitive performance of subjects was analyzed. A significant interaction effect of diagnostic group by genotype of rs6280 on the GMV of the left hippocampus was found, with lower GMV in FES patients that were C carriers compared with TT homozygotes; the opposite pattern was found in the genetic subgroups of HCs. In the FES group, C carriers performed significantly worse on reasoning and problem-solving tests than TT homozygotes. The left hippocampal GMV positively correlated with reasoning and problem-solving performance in TT homozygotes, but this correlation disappeared in FES patients that were C carriers and in genetic subgroups of HCs. Together, these results suggest that FES patients that are C carriers of rs6280 have lower GMV in the hippocampus, resulting in greater cognitive impairment.

The Role of Two Factors of Negative Symptoms and Cognition on Social Functioning in Male Patients with Schizophrenia: A Mediator Model

OBJECTIVE

This study aims to compare the cognitive function and social functioning in male patients with deficit syndrome (DS) and non-DS, and to explore whether cognitive function serves as a mediator in the relationship between the two factors of negative symptoms (motivation and pleasure (MAP) and expressivity (EXP) deficits, and social functioning in schizophrenia patients.

METHODS

One hundred and fifty-six male patients with schizophrenia and 109 age- and education-matched normal controls were enrolled in the current study. The Chinese version of a Schedule for Deficit Syndrome (SDS) was used for DS and non-DS categorization. The Brief Psychiatric Rating Scale (BPRS) and the Brief Negative Symptoms Scale (BNSS) were used to assess psychotic and negative symptoms in patients. The Social-Adaptive Functioning Evaluation (SAFE) was adopted to evaluate patients' social functioning, and a battery of classical neurocognitive tests was used to assess cognition, including sustained vigilance/attention, cognitive flexibility, ideation fluency, and visuospatial memory.

RESULTS

We found that male patients with DS performed worse in all four cognitive domains and social functioning compared to non-DS patients. Both total negative symptoms and its two factors were significantly associated with all four domains of cognition and social functioning in male patients. Interestingly, our results indicate that only cognitive flexibility mediates the relationship between negative symptoms and social functioning in schizophrenia patients, but there were no differences between EXP and MAP negative factors in this model.

CONCLUSION

Our findings suggest that DS patients may represent a unique clinical subgroup of schizophrenia, and the integrated interventions targeting both negative symptoms and cognition, especially cognitive flexibility, may optimally improve functional outcomes in schizophrenia patients.

Decreased integration of default-mode network during a working memory task in schizophrenia with severe attention deficits

Background

Working memory (WM) and attention deficits are both important features of schizophrenia. WM is closely related to attention, for it acted as an important characteristic in activating and manipulating WM. However, the knowledge of neural mechanisms underlying the relationship between WM and attention deficits in schizophrenia is poorly investigated.

Methods

Graph theory was used to examine the network topology at the whole-brain and large-scale network levels among 125 schizophrenia patients with different severity of attention deficits (65 mild attention deficits; 46 moderate attention deficits; and 14 severe attention deficits) and 53 healthy controls (HCs) during an N-back WM task. These analyses were repeated in the same participants during the resting state.

Results

In the WM task, there were omnibus differences in small-worldness and normalized clustering coefficient at a whole-brain level and normalized characterized path length of the default-mode network (DMN) among all groups. Post hoc analysis further indicated that all patient groups showed increased small-worldness and normalized clustering coefficient of the whole brain compared with HCs, and schizophrenia with severe attention deficits showed increased normalized characterized path length of the DMN compared with schizophrenia with mild attention deficits and HCs. However, these observations were not persisted under the resting state. Further correlation analyses indicated that the increased normalized characterized path length of the DMN was correlated with more severe attentional deficits and poorer accuracy of the WM task.

Conclusion

Our research demonstrated that, compared with the schizophrenia patients with less attention deficits, disrupted integration of the DMN may more particularly underlie the WM deficits in schizophrenia patients with severe attention deficits.

Unraveling schizophrenia replicable functional connectivity disruption patterns across sites

Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal-based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site-effect correction methods in removing the site-related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site-related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo-connectivity within sensory areas (Net1), hypo-connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper-connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet-specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out-of-sample public data set (Z = -1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet-specific composite FC measures might be replicable neuroimaging markers for schizophrenia.

Abnormal functional connectivity of the striatum in first-episode drug-naive early-onset Schizophrenia

Abnormal brain network connectivity is strongly implicated in the pathogenesis of schizophrenia. The striatum, consisting of the caudate and putamen, is the major treatment target for antipsychotics, the primary treatments for schizophrenia; however, there are few studies on the functional connectivity (FC) of striatum in drug-naive early-onset schizophrenia (EOS) patients. We examined the FC values of the caudate nucleus and putamen with whole brain by resting-state functional magnetic resonance imaging (RS-fMRI) and the associations with indices of clinical severity. Patients demonstrated abnormal FC between subregions of the putamen and both the visual network (left middle occipital gyrus) and default mode network (bilateral anterior cingulate, left superior frontal, and right middle frontal gyri). Furthermore, FC between dorsorostral putamen and left superior frontal gyrus correlated with both positive symptom subscore and total score on the Positive and Negative Syndrome Scale (PANSS). These findings demonstrate abnormal FC between the striatum and other brain areas even in the early stages of schizophrenia, supporting neurodevelopmental disruption in disease etiology and expression.

Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia

BACKGROUND

Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function.

METHODS

Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks.

RESULTS

At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions.

CONCLUSIONS

These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.

Improved Functional Organization in Patients With Primary Insomnia After Individually-Targeted Transcranial Magnetic Stimulation

Primary insomnia (PI) is among the most prevalent sleep-related disorders and has a far-reaching impact on daytime functioning. Repetitive transcranial magnetic stimulation (rTMS) has drawn attention because of its effectiveness and safety. The purpose of the current study was to detect changes in the topological organization of whole-brain functional networks and to determine their associations with the clinical treatment effects of rTMS. Resting-state functional magnetic resonance imaging (rsfMRI) data from 32 patients with PI were collected and compared with findings from 32 age- and gender-matched healthy controls (HCs). The patients were treated with Stanford accelerated intelligent neuromodulation therapy, which is a recently validated neuroscience-informed accelerated intermittent theta-burst stimulation protocol. Graph theoretical analysis was used to construct functional connectivity matrices and to extract the attribute features of small-world networks in insomnia. Scores on the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and the associations between these clinical characteristics and functional metrics, were the primary outcomes. At baseline, the patients with PI showed inefficient small-world property and aberrant functional segregation and functional integration compared with the HCs. These properties showed renormalization after individualized rTMS treatment. Furthermore, low functional connectivity between the right insula and left medial frontal gyrus correlated with improvement in ISI scores. We highlight functional network dysfunctions in PI patients and provide evidence into the pathophysiological mechanisms involved and the possible mode of action of rTMS.

Aberrant large-scale brain modules in deficit and non-deficit schizophrenia

OBJECTIVE

Schizophrenia is a heterogenous psychiatric disease, and deficit schizophrenia (DS) is a clinical subgroup with primary and enduring negative symptoms. Although previous neuroimaging studies have identified functional connectome alterations in schizophrenia, the modular organizations in DS and nondeficit schizophrenia (NDS) remain poorly understood. Therefore, this study aimed to investigate the modular-level alterations in DS patients compared with the NDS and healthy control (HC) groups.

METHODS

A previously collected dataset was re-analyzed, in which 74 chronic male schizophrenia patients (33 DS and 41 NDS) and 40 HC underwent resting-state functional magnetic resonance imaging with eyes closed in a Siemens 3 T scanner (scanning duration = 8 min). Modular- (intramodule and intermodule connectivity) and nodal- [normalized within-module degree (Z_i) and participation coefficient (PC_i)] level graph theory properties were computed and compared among the three groups. Receiver operating characteristic curve (ROC) analyses were performed to examine the classification ability of these measures, and partial correlations were conducted between network measures and symptom severity. Validation analyses on head motion, network sparsity, and parcellation scheme were also performed.

RESULTS

Both schizophrenia subgroups showed decreased intramodule connectivity in salience network (SN), somatosensory-motor network (SMN), and visual network (VN), and increased intermodule connectivity in SMN-default mode network (DMN) and SMN-frontoparietal network (FPN). Compared with NDS patients, DS patients showed weaker intramodule connectivity in SN and stronger intermodule connectivity in SMN-FPN and SMN-VN. At the nodal level, the schizophrenia-related alterations were distributed in SN, SMN, VN, and DMN, and 7 DS-specific nodal alterations were identified. Intramodule connectivity of SN, intermodule connectivity of SMN-VN, and Z_i of left precuneus successfully distinguished the three groups. Partial correlational analyses revealed that these measures were related to negative symptoms, general psychiatric symptoms, and neurocognitive function.

CONCLUSION

Our findings suggest that functional connectomes, especially SN, SMN, and VN, may capture the distinct and common disruptions of DS and NDS. These findings may help to understand the neuropathology of negative symptoms of schizophrenia and inform targets for treating different schizophrenia subtypes.

Functional reconfiguration of cerebellum-cerebral neural loop in schizophrenia following electroconvulsive therapy

Recent evidence highlights the role of the cerebellum-cerebral loop in the pathophysiology of schizophrenia (SZ). Electroconvulsive therapy (ECT) is clinically applied to augment the effect of antipsychotic drugs. The study aims to address whether the cerebellum-cerebral loop is involved in the mechanisms of ECT's augmentation effect. Forty-two SZ patients and 23 healthy controls (HC) were recruited and scanned using resting-state functional MRI (rs-fMRI). Twenty-one patients received modified ECT plus antipsychotics (MSZ group), and 21 patients took antipsychotics only (DSZ group). All patients were re-scanned four weeks later. Brain functional network was constructed according to the graph theory. The sub-network exhibited longitudinal changes after ECT or medications were constructed. For the MSZ group, a sub-network involving default-mode network and cerebellum showed significant longitudinal changes. For the DSZ group, a different sub-network involving the thalamus, frontal and occipital cortex was found to be altered in the follow-up scan. In addition, the changing FC of the left cerebellar crus2 region was correlated with the changing scores of the psychotic symptoms only in the MSZ group but not in the DSZ group. In conclusion, the cerebral-cerebellum loop is possibly involved in the antipsychotic mechanisms of ECT for schizophrenia.

Serum BDNF levels, glycolipid metabolism in deficit schizophrenia: A case-control study

BACKGROUND

Few studies have compared serum BDNF and glycolipid profiles in patients with deficit schizophrenia (DS) and non-deficit schizophrenia (NDS). We aimed to compare BDNF and glycolipid profiles between DS and NDS patients and healthy controls, and to investigate the relationship between BDNF, glycolipid profiles in DS and NDS patients.

METHODS

A total of 591 patients with chronic schizophrenia (SZ) and 238 healthy controls participated in this study. According to Proxy for the Deficit Syndrome Scale, SZ patients were divided into DS (n = 158) and NDS (n = 273) patients. Psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Serum BDNF levels were measured using enzyme-linked immunosorbent assay (ELISA).

RESULTS

BDNF levels were significantly lower in SZ patients than those in healthy controls (7.81 ± 2.98 ng/ml vs. 11.96 ± 2.29 ng/ml, P < 0.01). Furthermore, BDNF levels were lower in DS group than those in NDS group (P = 0.007, OR = 0.846, 95% CI = 0.750-0.955). Lower triglyceride levels were also an independent predictor for DS patients (P = 0.007, OR = 0.846, 95% CI = 0.750-0.955). Serum BDNF levels were negatively associated with the severity of deficit syndrome in SZ patients (β = -1.151, t = -2.559, P = 0.011). In DS group, triglycerides were associated with PANSS negative subscore (β = -0.262, t = -2.994, P = 0.003) and depressive factor subscore (β = 0.282, t = 2.146, P = 0.035).

CONCLUSION

Serum BDNF and triglycerides may be informative biomarkers of DS in SZ patients. The differences in glycolipid metabolism patterns between DS and NDS patients indicate that deficit syndrome is an independent endophenotype of SZ patients.

Aberrant functional brain network dynamics in patients with functional constipation

The aberrant static functional connectivity of brain network has been widely investigated in patients with functional constipation (FCon). However, the dynamics of brain functional connectivity in FCon patients remained unknown. This study aimed to detect the brain dynamics of functional connectivity states and network topological organizations of FCon patients and investigate the correlations of the aberrant brain dynamics with symptom severity. Eighty-three FCon patients and 80 healthy subjects (HS) were included in data analysis. The spatial group independent component analysis, sliding-window approach, k-means clustering, and graph-theoretic analysis were applied to investigate the dynamic temporal properties and coupling patterns of functional connectivity states, as well as the time-variation of network topological organizations in FCon patients. Four reoccurring functional connectivity states were identified in k-means clustering analysis. Compared to HS, FCon patients manifested the lower occurrence rate and mean dwell time in the state with a complex connection between default mode network and cognitive control network, as well as the aberrant anterior insula-cortical coupling patterns in this state, which were significantly correlated with the symptom severity. The graph-theoretic analysis demonstrated that FCon patients had higher sample entropy at the nodal efficiency of anterior insula than HS. The current findings provided dynamic perspectives for understanding the brain connectome of FCon and laid the foundation for the potential treatment of FCon based on brain connectomics.

Abnormal nodal and global network organization in resting state functional MRI from subjects with the 22q11 deletion syndrome

The 22q11 deletion syndrome is a genetic disorder associated with a high risk of developing psychosis, and is therefore considered a neurodevelopmental model for studying the pathogenesis of schizophrenia. Studies have shown that localized abnormal functional brain connectivity is present in 22q11 deletion syndrome like in schizophrenia. However, it is less clear whether these abnormal cortical interactions lead to global or regional network disorganization as seen in schizophrenia. We analyzed from a graph-theory perspective fMRI data from 40 22q11 deletion syndrome patients and 67 healthy controls, and reconstructed functional networks from 105 brain regions. Between-group differences were examined by evaluating edge-wise strength and graph theoretical metrics of local (weighted degree, nodal efficiency, nodal local efficiency) and global topological properties (modularity, local and global efficiency). Connectivity strength was globally reduced in patients, driven by a large network comprising 147 reduced connections. The 22q11 deletion syndrome network presented with abnormal local topological properties, with decreased local efficiency and reductions in weighted degree particularly in hub nodes. We found evidence for abnormal integration but intact segregation of the 22q11 deletion syndrome network. Results suggest that 22q11 deletion syndrome patients present with similar aberrant local network organization as seen in schizophrenia, and this network configuration might represent a vulnerability factor to psychosis.

Aberrant triple-network connectivity patterns discriminate biotypes of first-episode medication-naive schizophrenia in two large independent cohorts

Schizophrenia is a complex disorder associated with aberrant brain functional connectivity. This study aims to demonstrate the relation of heterogeneous symptomatology in this disorder to distinct brain connectivity patterns within the triple-network model. The study sample comprised 300 first-episode antipsychotic-naive patients with schizophrenia (FES) and 301 healthy controls (HCs). At baseline, resting-state functional magnetic resonance imaging data were captured for each participant, and concomitant neurocognitive functions were evaluated outside the scanner. Clinical information of 49 FES in the discovery dataset were reevaluated at a 6-week follow-up. Differential features between FES and HCs were selected from triple-network connectivity profiles. Cutting-edge unsupervised machine learning algorithms were used to define patient subtypes. Clinical and cognitive variables were compared between patient subgroups. Two FES subgroups with differing triple-network connectivity profiles were identified in the discovery dataset and confirmed in an independent hold-out cohort. One patient subgroup appearing to have more severe clinical symptoms was distinguished by salience network (SN)-centered hypoconnectivity, which was associated with greater impairments in sustained attention. The other subgroup exhibited hyperconnectivity and manifested greater deficits in cognitive flexibility. The SN-centered hypoconnectivity subgroup had more persistent negative symptoms at the 6-week follow-up than the hyperconnectivity subgroup. The present study illustrates that clinically relevant cognitive subtypes of schizophrenia may be associated with distinct differences in connectivity in the triple-network model. This categorization may foster further analysis of the effects of therapy on these network connectivity patterns, which may help to guide therapeutic choices to effectively reach personalized treatment goals.

Topological Organization Alterations of Whole-Brain Functional Networks in Patients with Childhood Absence Epilepsy: Associations with Treatment Effects

PURPOSE

The purpose of the current study is to detect changes of topological organization of whole-brain functional networks and their relationship with the clinical treatment effects of antiepileptic drugs (AEDs) for patients with childhood absence epilepsy (CAE) using resting-state functional MRI (RS-fMRI). Patients and Methods. RS-fMRI data from 30 CAE patients were collected and compared with findings from 30 age- and gender-matched healthy controls (HCs). The patients were treated with first-line AEDs for 46.03 months before undergoing a second RS-fMRI scan.

RESULTS

CAE children at baseline showed a reduced clustering coefficient (Cp) and local efficiency (El) than the HC group, implying the reduction of functional segregation. CAE children at baseline also showed smaller characteristic path length (Lp) and higher global efficiency (Eg) compared with the HC group, implying the impairment of functional segregation. However, those metrics showed no significant differences between CAE children at follow-up and the HC group which indicated a clear renormalization of topological organization after AED treatments. CAE at follow-up also showed significantly decreased connectivity between several network regions, with which the thalamus is mainly involved. Furthermore, the reduced connectivity change between the left superior parietal gyrus and the left thalamus is positively correlated with the symptom improvements after AED treatment.

CONCLUSION

We highlighted the convergence and divergence of brain functional network dysfunctions in CAE patients and provided crucial insights into pathophysiological mechanisms and the AED effects.

Classifying Vulnerability to Sleep Deprivation Using Resting-State Functional MRI Graph Theory Metrics

Sleep deprivation (SD) has become very common in contemporary society, where people work around the clock. SD-induced cognitive deficits show large inter-individual differences and are trait-like with known neural correlates. However, few studies have used neuroimaging to predict vulnerability to SD. Here, resting state functional magnetic resonance imaging (fMRI) data and psychomotor vigilance task (PVT) data were collected from 60 healthy subjects after resting wakefulness and after one night of SD. The number of PVT lapses was then used to classify participants on the basis of whether they were vulnerable or resilient to SD. We explored the viability of graph-theory-based degree centrality to accurately classify vulnerability to SD. Compared with during resting wakefulness, widespread changes in degree centrality (DC) were found after SD, indicating significant reorganization of sleep homeostasis with respect to activity in resting state brain network architecture. Support vector machine (SVM) analysis using leave-one-out cross-validation achieved a correct classification rate of 84.75% [sensitivity 82.76%, specificity 86.67%, and area under the receiver operating characteristic curve (AUC) 0.94] for differentiating vulnerable subjects from resilient subjects. Brain areas that contributed most to the classification model were mainly located within the sensorimotor network, default mode network, and thalamus. Furthermore, we found a significantly negative correlation between changes in PVT lapses and DC in the thalamus after SD. These findings suggest that resting-state network measures combined with a machine learning algorithm could have broad potential applications in screening vulnerability to SD.

Social brain network correlates with real-life social network in individuals with schizophrenia and social anhedonia

Social behaviour requires the brain to efficiently integrate multiple social processes, but it is not clear what neural substrates underlie general social behaviour. While psychosis patients and individuals with subclinical symptoms are characterized by social dysfunction, the neural mechanisms underlying social dysfunctions in schizophrenia spectrum disorders remains unclear. We first constructed a general social brain network (SBN) using resting-state functional connectivity (FC) with regions of interest based on the automatic meta-analysis results from NeuroSynth. We then examined the general SBN and its relationship with social network (SN) characteristics in 30 individuals with schizophrenia (SCZ) and 33 individuals with social anhedonia (SA). We found that patients with SCZ exhibited deficits in their SN, while SA individuals did not. SCZ patients showed decreased segregation and functional connectivity in their SBN, while SA individuals showed a reversed pattern with increased segregation and functional connectivity of their SBN. Sparse canonical correlation analysis showed that both SCZ patients and SA individuals exhibited reduced correlation between SBN and SN characteristics compared with their corresponding healthy control groups. These preliminary findings suggest that both SCZ and SA participants exhibit abnormality in segregation and functional connectivity within the general SBN and reduced correlation with SN characteristics. These findings could guide the development of non-pharmacological interventions for social dysfunction in SCZ spectrum disorders.

Aberrant cerebellar neural activity and cerebro-cerebellar functional connectivity involving executive dysfunction in schizophrenia with primary negative symptoms

Deficit schizophrenia (DS) is a distinct subtype of schizophrenia characterized by primary and enduring negative symptoms. More severe executive dysfunctions were observed in DS patients, however, the associated neuroimaging characteristics, especially cerebellar functional anomalies in DS, remain largely unknown. We employed resting-state functional and structural MRI data of 106 male participants, including data from 29 DS patients, 39 non-deficit schizophrenia (NDS) patients and 38 healthy controls (HCs). Z-standardized fractional amplitude of low-frequency fluctuation (zfALFF) values were calculated in order to examine spontaneous regional brain activity. Cerebro-cerebellar functional connectivity and changes in the volume of gray matter in the cerebellum were also examined. Relative to the HCs, both DS and NDS patients exhibited decreased zfALFF in the bilateral cerebellar lobules VIII and IX. The zfALFF in the left Crus II was lower in DS patients compared to NDS patients. No significant difference was observed in the volume of cerebellar gray matter among the three groups. Compared with NDS patients, cerebro-cerebellar functional connectivity analysis revealed increased connectivity in the left orbital medial frontal cortex and right putamen regions in DS patients. Reduced zfALFF in the left Crus II in the DS group was significantly positively correlated with Stroop Color and Word scores, while negatively correlated with Trail-Making Test part B scores. The increased functional connectivity in the right putamen in DS patients was significantly positively correlated with Animal Naming Test and semantic Verbal Fluency Test scores. These results highlight cerebellar functional abnormality in DS patients and provide insight into the pathophysiological mechanism of executive dysfunction.

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.

Levodopa Changes Functional Connectivity Patterns in Subregions of the Primary Motor Cortex in Patients With Parkinson's Disease

Background

The primary motor cortex (M1) is a critical node in Parkinson’s disease (PD)-related motor circuitry; however, the functional roles of its subregions are poorly understood. In this study, we investigated changes in the functional connectivity patterns of M1 subregions and their relationships to improved clinical symptoms following levodopa administration.

Methods

Thirty-six PD patients and 37 healthy controls (HCs) were enrolled. A formal levodopa challenge test was conducted in the PD group, and the Unified Parkinson’s Disease Rating Scale motor section (UPDRS-III) was assessed before (off state) and 1 h after administration of levodopa (on state). The PD group underwent resting-state functional magnetic resonance imaging in both off and on states, whereas the HC group was scanned once. We used the Human Brainnetome Atlas template to subdivide M1 into twelve regions of interest (ROIs). Functional connectivity (FC) was compared between PD on and off states [paired t-test, voxel-level p < 0.001, cluster-level p < 0.05, Gaussian random field (GRF) correction] and between patients and HC (two-sample t-test voxel-level p < 0.001, cluster-level p < 0.05). Correlations between ΔFC (differences in FC between PD off and on states) and clinical symptom improvements were examined.

Results

There was decreased FC between the right caudal dorsolateral area 6 and the anterior cingulate gyrus (ACC), the right upper limb region and the left medial dorsal thalamus (mdTHA), as well as increased FC between the left tongue and larynx region and the left medial frontal gyrus. ΔFC between the right caudal dorsolateral area 6 and ACC was positively correlated with improvements in UPDRS-III total scores as well as the rigidity (item 22) and bradykinesia (items 23–26 and 31) subscores. ΔFC between the right upper limb region and left thalamus was positively correlated with improvements in the left upper limb tremor (items 20c and 21b) and postural tremor (item 21b) subscores.

Conclusions

Our results reveal novel information regarding the underlying mechanisms in the motor circuits in the M1 and a promising way to explore the internal function of the M1 in PD patients. Notably, M1 is a potential therapeutic target in PD, and the exploration of its subregions provides a basis and a source of new insights for clinical intervention and precise drug treatment.

Prevalence, Sociodemographic, and Clinical Correlates of Older Chinese Patients With Deficit Schizophrenia

OBJECTIVE

No study has investigated the frequency and risk factors for deficit schizophrenia (DS) in Chinese Han population. We investigated the prevalence of DS among community-dwelling older Chinese patients with schizophrenia and examined the sociodemographic and clinical correlates of DS in this population.

METHODS

A total of 326 community-dwelling older patients with schizophrenia were recruited in this cross-sectional study. Deficit schizophrenia was confirmed using the Chinese version of the Schedule for the Deficit Syndrome. Data pertaining to sociodemographic and clinical characteristics were collected. Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS).

RESULTS

The prevalence of DS in the study population was 26.7% (31.2% among male patients and 21.6% among female patients with schizophrenia). Patients with DS had significantly higher current smoking rate, hospitalizations, PANSS negative score, PANSS total score, and had earlier age at onset than patients with non-deficit schizophrenia (N-DS). The N-DS patients had higher PANSS positive scores and a greater proportion of married patients. Multiple logistic regression analysis indicated that negative PANSS score (odds ratio [OR] = 1.10, 95% confidence interval [CI] = 1.04-1.16, P < .001), male sex (OR = 1.71, 95% CI = 1.53-1.91, P = .037), age at onset (OR = 0.88, 95% CI = 0.82-0.94, P = .035), and current smoking (OR = 1.37, 95% CI = 1.15-1.63, P = .041) were independently associated with DS.

CONCLUSION

Deficit schizophrenia is relatively common among older community-dwelling Chinese patients with schizophrenia. High negative symptom scores, male sex, early onset, and smoking were independent correlates for DS.

Topologically state-independent and dependent functional connectivity patterns in current and remitted depression

OBJECTIVE

Identification of state-independent and -dependent neural biomarkers may provide insight into the pathophysiology and effective treatment of major depressive disorder (MDD), therefore we aimed to investigate the state-independent and -dependent topological alterations of MDD.

METHOD

Brain resting-state functional magnetic resonance imaging (fMRI) data were acquired from 59 patients with unmedicated first episode current MDD (cMDD), 48 patients with remitted MDD (rMDD) and 60 demographically matched healthy controls (HCs). Using graph theory, we systematically studied the topological organization of their whole-brain functional networks at the global and nodal level.

RESULTS

At a global level, both patient groups showed decreased normalized clustering coefficient in relative to HCs. On a nodal level, both patient groups showed decreased nodal centrality, predominantly in cortex-mood-regulation brain regions including the dorsolateral prefrontal cortex, posterior parietal cortex and posterior cingulate cortex. By comparison to cMDD patients, rMDD group had a higher nodal centrality in right parahippocampal gyrus.

LIMITATIONS

The present study, an exploratory analysis, may require further confirmation with task-based and experimental studies.

CONCLUSIONS

Deficits in the topological organization of the whole brain and cortex-mood-regulation brain regions in both rMDD and cMDD represent state-independent biomarkers.

Convergent and divergent altered patterns of default mode network in deficit and non-deficit schizophrenia

OBJECTIVE

Previous studies suggested likely mechanisms underlying the dysfunction of the default mode network (DMN) in schizophrenia. However, altered patterns of the intrinsic activity of the DMN in both deficit schizophrenia (DS) and non-deficit schizophrenia (NDS) patients, as well as the neurocognitive relationships among them, remain unknown. This study explores the resting-state characteristics of the DMN activity in both DS and NDS patients, and further investigates correlations with neurocognitive features.

METHODS

Demographic, resting-state functional MRI, and neurocognitive data were collected in 37 DS and 38 NDS patients, as well as in 38 matched healthy control subjects (HCs). Independent component analysis was conducted to investigate the characteristics of DMN activity and to further distinguish between common and specific altered regions. In addition, partial correlation analysis was conducted to examine associations between the activity of altered regions and neurocognitive assessments.

RESULTS

Overlapping altered brain activity was observed in both DS and NDS patients in the left middle frontal gyrus (MFG), the left angular gyrus (ANG), and the calcarine sulcus (CAL) region. Furthermore, compared to HCs, DS patients showed less activity in the right inferior temporal gyrus, the right para-hippocampal gyrus / hippocampus (PHP / HIP), and the left precuneus (PCUN), while they showed increased activity in the posterior cingulate cortex (PCC). Notably, NDS patients showed less activity in the bilateral middle occipital gyrus. Correlation analysis indicated that, in the DS group, both Trail Making Test (TMT)-B and spatial processing scores were positively associated with the activities of the left PCUN and the right PHP / HIP, while the Stroop color scores were negatively associated with PCC activity. In the NDS group, the TMT-B scores were associated with activities of the left MFG and CAL regions, while the scores of the Wechsler adult intelligence scale (Chinese revision) were negatively associated with CAL region activity.

CONCLUSION

The present study demonstrates convergent and divergent altered patterns of the DMN in both DS and NDS patients. Importantly, the specific altered regions of the DMN in DS patients may be associated with extensive deficient neurocognition, indicating novel insights into the pathogenesis of cognitive impairment in schizophrenia.

Enhanced Global-Brain Functional Connectivity in the Left Superior Frontal Gyrus as a Possible Endophenotype for Schizophrenia

The notion of dysconnectivity in schizophrenia has been put forward for many years and results in substantial attempts to explore altered functional connectivity (FC) within different networks with inconsistent results. Clinical, demographical, and methodological heterogeneity may contribute to the inconsistency. Forty-four patients with first-episode, drug-naive schizophrenia, 42 unaffected siblings of schizophrenia patients and 44 healthy controls took part in this study. Global-brain FC (GFC) was employed to analyze the imaging data. Compared with healthy controls, patients with schizophrenia and unaffected siblings shared enhanced GFC in the left superior frontal gyrus (SFG). In addition, patients had increased GFC mainly in the thalamo-cortical network, including the bilateral thalamus, bilateral posterior cingulate cortex (PCC)/precuneus, left superior medial prefrontal cortex (MPFC), right angular gyrus, and right SFG/middle frontal gyrus and decreased GFC in the left ITG/cerebellum Crus I. No other altered GFC values were observed in the siblings group relative to the control group. Further ROC analysis showed that increased GFC in the left SFG could separate the patients or the siblings from the controls with acceptable sensitivities. Our findings suggest that increased GFC in the left SFG may serve as a potential endophenotype for schizophrenia.

Abnormal Alpha Rhythm During Self-Referential Processing in Schizophrenia Patients

Schizophrenia patients exhibited a psychological abnormal appearance when they recognized objects related to themselves. This cognitive process is associated with self-referential processing. In this study, the self-referential memory (SRM) task was performed by 18 schizophrenia patients and 18 healthy controls. In the encoding stage of the SRM task, the behavioral experiment data and electroencephalogram (EEG) data were recorded in three experimental conditions (self-referential condition, other-referential condition, and physical condition). For data analysis, the electrophysiological performance of the time-frequency distribution, phase lag index (PLI) strengths, phase synchronization connectivity, and brain-network properties were assessed in schizophrenia patients compared to healthy controls. We found that schizophrenia patients exhibited abnormal alpha oscillation characteristics at the time of 100-300 ms poststimulus during the self-referential condition, which consisted of diminished time-frequency distributions over the prefrontal, parietal, and occipital regions; lower functional connectivity strengths of the PLI in the parietal and occipital areas; higher global efficiency and the lower characteristic path length; and nodal efficiency of local areas (increased nodal efficiency in temporal regions and decreased nodal efficiency in occipital region) for dynamic network topology properties. Furthermore, the evoked power of the alpha band during the self-referential condition was significantly correlated with the SRM bias score in the patients (r = 0.595, p = 0.009). These results provided electrophysiological evidence and supported the hypothesis that an abnormal alpha rhythm might be the principal factor of dysfunctional self-referential processing in schizophrenia patients.