A Dissociation in Effects of Risperidone Monotherapy on Functional and Anatomical Connectivity Within the Default Mode Network

The impact of indirect structure on functional connectivity in schizophrenia using a multiplex brain network

It is known that abnormal functional connectivity (FC) in schizophrenia (SZ) is closely related to structural connectivity (SC). We speculate that indirect SC also have an impact on FC in SZ patients. Conventional single-layer network has limitations for studying the relationship between indirect SC and FC. Thus, this study constructed a multiplex network based on structural connectivity and functional connectivity (SC-FC). The SC-FC bandwidth and SC-FC cost are used to analyze the impact of indirect SC on FC. Moreover, this paper proposed mediation ability, mediation cost, mediated strength and mediated cost to quantify the effects of mediator nodes and mediated nodes on indirect SC. The results show that SZ patients exhibit lower SC-FC bandwidth and SC-FC cost compared to healthy controls (HC), which could be caused by the limbic and subcortical network (LSN), default mode network (DMN) and visual network (VN). The mediator and mediated nodes in indirect SC of SZ patients also showed diminished effects. These findings suggest that functional communication ability and cost in SZ patients are influenced by indirect SC. This study provides new perspectives for understanding the relationship between indirect SC and FC, and provides strong evidence for interpreting the physiological mechanisms of SZ patients.

Continuous Dictionary of Nodes Model and Bilinear-Diffusion Representation Learning for Brain Disease Analysis

Brain networks based on functional magnetic resonance imaging (fMRI) provide a crucial perspective for diagnosing brain diseases. Representation learning has recently attracted tremendous attention due to its strong representation capability, which can be naturally applied to brain disease analysis. However, traditional representation learning only considers direct and local node interactions in original brain networks, posing challenges in constructing higher-order brain networks to represent indirect and extensive node interactions. To address this problem, we propose the Continuous Dictionary of Nodes model and Bilinear-Diffusion (CDON-BD) network for brain disease analysis. The CDON model is innovatively used to learn the original brain network, with its encoder weights directly regarded as latent features. To fully integrate latent features, we further utilize Bilinear Pooling to construct higher-order brain networks. The Diffusion Module is designed to capture extensive node interactions in higher-order brain networks. Compared to state-of-the-art methods, CDON-BD demonstrates competitive classification performance on two real datasets. Moreover, the higher-order representations learned by our method reveal brain regions relevant to the diseases, contributing to a better understanding of the pathology of brain diseases.

Alterations in amygdala subregions-Default mode network connectivity after treatment in patients with schizophrenia

Disrupted connectivity in the default mode network (DMN) during resting-state functional MRI (rs-fMRI) is well-documented in schizophrenia (SCZ). The amygdala, a key component in the neurobiology of SCZ, comprises distinct subregions that may exert varying effects on the disorder. This study aimed to investigate variations in functional connectivity (FC) between distinct amygdala subregions and the DMN in SCZ individuals and explore the effects of treatment on these connections. Fifty-six SCZ patients and 51 healthy controls underwent FC analysis and questionnaire surveys during resting state. The amygdala was selected as the region of interest (ROI) and subdivided into four parts. Changes in FC were examined, and correlations between questionnaire scores and brain activity were explored. Pre-treatment, SCZ patients exhibited reduced FC between the amygdala and DMN compared to HCs. After treatment, significant differences persisted in the right medial amygdala, while other regions did not differ significantly from controls. In addition, PANSS scores positively correlated with FC between the Right Medial Amygdala and the left SMFC (r = .347, p = .009), while RBANS5A scores showed a positive correlation with FC between the Left Lateral Amygdala and the right MTG (rho = -.347, p = .009). The rsFC between the amygdala and the DMN plays a crucial role in the treatment mechanisms of SCZ. This could provide a promising predictive indicator for understanding the neural mechanisms behind treatment and symptomatic improvement.

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years.

STUDY DESIGN

The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade.

STUDY RESULTS

Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders.

CONCLUSIONS

We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

Effects of long-term antipsychotic medication on brain instability in first-episode schizophrenia patients: a resting-state fMRI study

Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their prognosis. However, limited attention has been given to the long-term effects of antipsychotic drug therapy on FES patients. In this research, we examined the changes in abnormal brain regions among FES patients undergoing long-term treatment using a dynamic perspective. A total of 98 participants were included in the data analysis, comprising 48 FES patients, 50 healthy controls, 22 patients completed a follow-up period of more than 6 months with qualified data. We processed resting-state fMRI data to calculate coefficient of variation of fractional amplitude of low-frequency fluctuations (CVfALFF), which reflects the brain regional activity stability. Data analysis was performed at baseline and after long-term treatment. We observed that compared with HCs, patients at baseline showed an elevated CVfALFF in the supramarginal gyrus (SMG), parahippocampal gyrus (PHG), caudate, orbital part of inferior frontal gyrus (IOG), insula, and inferior frontal gyrus (IFG). After long-term treatment, the instability in SMG, PHG, caudate, IOG, insula and inferior IFG have ameliorated. Additionally, there was a positive correlation between the decrease in dfALFF in the SMG and the reduction in the SANS total score following long-term treatment. In conclusion, FES patients exhibit unstable regional activity in widespread brain regions at baseline, which can be ameliorated with long-term treatment. Moreover, the extent of amelioration in SMG instability is associated with the amelioration of negative symptoms.

Functional Connectivity Between Auditory and Medial Temporal Lobe Networks in Antipsychotic-Naïve Patients With First-Episode Schizophrenia Predicts the Effects of Dopamine Antagonism on Auditory Verbal Hallucinations

Background

Understanding how antipsychotic medication ameliorates auditory verbal hallucinations (AVHs) through modulation of brain circuitry is pivotal for understanding the pathophysiology of psychosis and for predicting treatment response.

Methods

This case-control study included examinations at baseline and at follow-up after 6 weeks. Initially, antipsychotic-naïve patients with first-episode schizophrenia who were experiencing AVHs were recruited together with healthy control participants. Antipsychotic treatment with the relatively selective D2 receptor antagonist amisulpride was administered as monotherapy. Functional connectivity measured by resting-state functional magnetic resonance imaging between networks of interest was used to study the effects of D2 blockade on brain circuitry and predict clinical treatment response. Hallucinations were rated with the Positive and Negative Syndrome Scale.

Results

Thirty-two patients experiencing AVHs and 34 healthy control participants were scanned at baseline. Twenty-two patients and 34 healthy control participants were rescanned at follow-up. Connectivity between the auditory network and the medial temporal lobe network was increased in patients at baseline (p = .002) and normalized within 6 weeks of D2 blockade (p = .018). At baseline, the connectivity between these networks was positively correlated with ratings of hallucinations (t = 2.67, p = .013). Moreover, baseline connectivity between the auditory network and the medial temporal lobe network predicted reduction in hallucinations (t = 2.34, p = .032).

Conclusions

Functional connectivity between the auditory network and the medial temporal lobe predicted response to initial antipsychotic treatment. These findings demonstrate that connectivity between networks involved in auditory processing, internal monitoring, and memory is associated with the clinical effect of dopamine antagonism.

fMRI connectivity as a biomarker of antipsychotic treatment response: A systematic review

BACKGROUND

Antipsychotic drugs are the first-choice therapy for psychotic episodes, but antipsychotic treatment response (AP-R) is unpredictable and only becomes clear after weeks of therapy. A biomarker for AP-R is currently unavailable. We reviewed the evidence for the hypothesis that functional magnetic resonance imaging functional connectivity (fMRI-FC) is a predictor of AP-R or could serve as a biomarker for AP-R in psychosis.

METHOD

A systematic review of longitudinal fMRI studies examining the predictive performance and relationship between FC and AP-R was performed following PRISMA guidelines. Technical and clinical aspects were critically assessed for the retrieved studies. We addressed three questions: Q1) is baseline fMRI-FC related to subsequent AP-R; Q2) is AP-R related to a change in fMRI-FC; and Q3) can baseline fMRI-FC predict subsequent AP-R?

RESULTS

In total, 28 articles were included. Most studies were of good quality. fMRI-FC analysis pipelines included seed-based-, independent component- / canonical correlation analysis, network-based statistics, and graph-theoretical approaches. We found high heterogeneity in methodological approaches and results. For Q1 (N = 17) and Q2 (N = 18), the most consistent evidence was found for FC between the striatum and ventral attention network as a potential biomarker of AP-R. For Q3 (N = 9) accuracy's varied form 50 till 93%, and prediction models were based on FC between various brain regions.

CONCLUSION

The current fMRI-FC literature on AP-R is hampered by heterogeneity of methodological approaches. Methodological uniformity and further improvement of the reliability and validity of fMRI connectivity analysis is needed before fMRI-FC analysis can have a place in clinical applications of antipsychotic treatment.

A review of multi-modal magnetic resonance imaging studies on perimenopausal brain: a hint towards neural heterogeneity

The population ageing process worldwide is leading to an increasing number of women in the perimenopausal phase. Many of the perimenopausal symptoms, such as headache, depression, insomnia, and cognitive decline, are neurological in nature. Therefore, the study of the perimenopausal brain is of great importance. In addition, relevant studies can also provide an imaging basis for multiple therapies to treat perimenopausal symptoms. Because of its non-invasive nature, magnetic resonance imaging (MRI) has now been widely applied to the study of perimenopausal brains, revealing alterations in the brain associated with symptoms during the menopause transition. In this review, we collected papers and works of literature on the perimenopausal brain using MRI techniques in the Web of Science database. We firstly described the general principles and analysis methods of different MRI modalities briefly and then reviewed the structural, functional, perfusion, and metabolic compounds changes in the brain of perimenopausal women respectively, and described the latest advances in probing the perimenopausal brain using MRI, resulting in summary diagrams and figures. Based on the summary of existing works of the literature, this review further provided a perspective on multi-modal MRI studies in the perimenopausal brain, suggesting that population-based, multi-center, and longitudinal studies will be beneficial to the comprehensive understanding of changes in the perimenopausal brain. In addition, we found a hint towards neural heterogeneity in the perimenopausal brain, which should be addressed by future MRI studies to provide more help for the precise diagnosis and personalized treatment of perimenopausal symptoms. KEY POINTS: • Perimenopause is not only a physiological transition but also a period of neurological transition. • Multi-modal MRI studies have revealed that perimenopause is accompanied by alterations in the brain, which is implicated in many perimenopausal symptoms. • The diversity in the multi-modal MRI findings may give a hint to neural heterogeneity in the perimenopausal brain.

Structure-function coupling in white matter uncovers the abnormal brain connectivity in Schizophrenia

Schizophrenia is characterized by dysconnectivity syndrome. Evidence of widespread impairment of structural and functional integration has been demonstrated in schizophrenia. Although white matter (WM) microstructural abnormalities have been commonly reported in schizophrenia, the dysfunction of WM as well as the relationship between structure and function in WM remains uncertain. In this study, we proposed a novel structure-function coupling measurement to reflect neuronal information transfer, which combined spatial-temporal correlations of functional signals with diffusion tensor orientations in the WM circuit from functional and diffusion magnetic resonance images (MRI). By analyzing MRI data from 75 individuals with schizophrenia (SZ) and 89 healthy volunteers (HV), the associations between structure and function in WM regions in schizophrenia were examined. Randomized validation of the measurement was performed in the HV group to confirm the capacity of the neural signal transferring along the WM tracts, referring to quantifying the association between structure and function. Compared to HV, SZ showed a widespread decrease in the structure-function coupling within WM regions, involving the corticospinal tract and the superior longitudinal fasciculus. Additionally, the structure-function coupling in the WM tracts was found to be significantly correlated with psychotic symptoms and illness duration in schizophrenia, suggesting that abnormal signal transfer of neuronal fiber pathways could be a potential mechanism of the neuropathology of schizophrenia. This work supports the dysconnectivity hypothesis of schizophrenia from the aspect of circuit function, and highlights the critical role of WM networks in the pathophysiology of schizophrenia.

Clinical anatomy of the precuneus and pathogenesis of the schizophrenia

Recent evidence has shown that the precuneus plays a role in the pathogenesis of schizophrenia. The precuneus is a structure of the parietal lobe's medial and posterior cortex, representing a central hub involved in multimodal integration processes. Although neglected for several years, the precuneus is highly complex and crucial for multimodal integration. It has extensive connections with different cerebral areas and is an interface between external stimuli and internal representations. In human evolution, the precuneus has increased in size and complexity, allowing the development of higher cognitive functions, such as visual-spatial ability, mental imagery, episodic memory, and other tasks involved in emotional processing and mentalization. This paper reviews the functions of the precuneus and discusses them concerning the psychopathological aspects of schizophrenia. The different neuronal circuits, such as the default mode network (DMN), in which the precuneus is involved and its alterations in the structure (grey matter) and the disconnection of pathways (white matter) are described.

Comparison of brain network between schizophrenia and bipolar disorder: A multimodal MRI analysis of comparative studies

OBJECTIVE

Cognitive impairment is a shared symptom of Schizophrenia (SCZ) and bipolar disorder (BP), but the underlying neural mechanisms for both remain unclear. We aimed to identify abnormalities in the structural and functional brain network of patients with SCZ and BP.

METHODS

The study included 69 patients with SCZ, 40 with BP, and 63 healthy controls (HC). After neurocognitive function assessment, resting-state functional magnetic resonance imaging and diffusion tensor imaging were acquired respectively. We compared the network of structural connectivity (SC) and functional connectivity (FC) among the three groups and performed graph theoretical analyses. The SC-FC coupling was calculated, and the correlations between the cognitive function scores and network properties were ascertained.

RESULTS

The BP group showed significantly higher indicators in subnetworks and graph theory analysis than SCZ and HC. Several brain regions, such as the inferior parietal lobe, exhibited differences among all pairwise comparisons and showed significant correlations with cognitive scores in both SCZ and BP. SC-FC coupling did not significantly differ between the three groups but showed close associations with clinical performance. Interestingly, the direction of correlations between the network properties and cognition tends to present the opposite between SCZ and BP, especially regarding the working memory, attention, and language sections.

CONCLUSIONS

The FC and SC network of the SCZ group appeared more inefficient and disconnected than BP. The network demonstrated to be closely but differently associated with cognitive function at both local and global levels, indicating the potentially separated pathologies of cognition deficits in SCZ and BP.

Striatum-related spontaneous coactivation patterns predict treatment response on positive symptoms of drug-naive first-episode schizophrenia with risperidone monotherapy

Background

Evidence from functional magnetic resonance imaging (fMRI) studies of schizophrenia suggests that interindividual variation in the stationary striatal functional circuit may be correlated with antipsychotic treatment response. However, little is known about the role of the dynamic striatum-related network in predicting patients’ clinical improvement. The spontaneous coactivation pattern (CAP) technique has recently been found to be important for elucidating the non-stationary nature of functional brain networks.

Methods

Forty-two drug-naive first-episode schizophrenia patients underwent fMRI and T1W imaging before and after 8 weeks of risperidone monotherapy. The striatum was divided into 3 subregions, including the putamen, pallidum, and caudate. Spontaneous CAPs and CAP states were utilized to measure the dynamic characteristics of brain networks. We used DPARSF and Dynamic Brain Connectome software to analyze each subregion-related CAP and CAP state for each group and then compared the between-group differences in the neural network biomarkers. We used Pearson’s correlation analysis to determine the associations between the neuroimaging measurements with between-group differences and the improvement in patients’ psychopathological symptoms.

Results

In the putamen-related CAPs, patients showed significantly increased intensity in the bilateral thalamus, bilateral supplementary motor areas, bilateral medial, and paracingulate gyrus, left paracentral lobule, left medial superior frontal gyrus, and left anterior cingulate gyrus compared with healthy controls. After treatment, thalamic signals in the putamen-related CAP 1 showed a significant increase, while the signals of the medial and paracingulate gyrus in the putamen-related CAP 3 revealed a significant decrease. The increase in thalamic signal intensity in the putamen-related CAP 1 was significantly and positively correlated with the percentage reduction in PANSS_P.

Conclusion

This study is the first to combine striatal CAPs and fMRI to explore treatment response-related biomarkers in the early phase of schizophrenia. Our findings suggest that dynamic changes in CAP states in the putamen-thalamus circuit may be potential biomarkers for predicting patients’ variation in the short-term treatment response of positive symptoms.

Virtual histology of morphometric similarity network after risperidone monotherapy and imaging-epigenetic biomarkers for treatment response in first-episode schizophrenia

BACKGROUND

Antipsychotic treatment has been conceived to alter brain connectivity, but it is unclear how the changes of network phenotypes relate to the underlying transcriptomics. Given DNA methylation (DNAm) may alter transcriptional levels, we further integrated an imaging-transcriptomic-epigenetic analysis to explore multi-omics treatment response biomarkers.

METHODS

Forty-two treatment-naive first-episode schizophrenia patients were scanned by TI weighted (T1W) imaging and DTI before and after 8-week risperidone monotherapy, and their peripheral blood genomic DNAm values were examined in parallel with MRI scanning. Morphometric similarity network (MSN) quantified with DTI and T1W data were used as a marker of treatment-related alterations in interareal cortical connectivity. We utilized partial least squares (PLS) to examine spatial associations between treatment-related MSN variations and cortical transcriptomic data obtained from the Allen Human Brain Atlas.

RESULTS

Longitudinal MSN alterations were related to treatment response on cognitive function and general psychopathology symptoms, while DNAm values of 59 PLS1 genes were on negative and positive symptoms. Virtual-histology transcriptomic analysis linked the MSN alterations with the neurobiological, cellular and metabolic pathways or processes, and assigned MSN-related genes to multiple cell types, specifying neurons and glial cells as contributing most to the transcriptomic associations of longitudinal changes in MSN.

CONCLUSIONS

We firstly reveal how brain-wide transcriptional levels and cell classes capture molecularly validated cortical connectivity alterations after antipsychotic treatment. Our findings represent a vital step towards the exploration of treatment response biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.

Longitudinal multi-omics alterations response to 8-week risperidone monotherapy: Evidence linking cortical thickness, transcriptomics and epigenetics

Background

Antipsychotic treatment-related alterations of cortical thickness (CT) and clinical symptoms have been previously corroborated, but less is known about whether the changes are driven by gene expression and epigenetic modifications.

Methods

Utilizing a prospective design, we recruited 42 treatment-naive first-episode schizophrenia patients (FESP) and 38 healthy controls. Patients were scanned by TI weighted imaging before and after 8-week risperidone monotherapy. CT estimation was automatically performed with the FreeSurfer software package. Participants' peripheral blood genomic DNA methylation (DNAm) status, quantified by using Infinium^® Human Methylation 450K BeadChip, was examined in parallel with T1 scanning. In total, CT measures from 118 subjects and genomic DNAm status from 114 subjects were finally collected. Partial least squares (PLS) regression was used to detect the spatial associations between longitudinal CT variations after treatment and cortical transcriptomic data acquired from the Allen Human Brain Atlas. Canonical correlation analysis (CCA) was then performed to identify multivariate associations between DNAm of PLS1 genes and patients' clinical improvement.

Results

We detected the significant PLS1 component (2,098 genes) related to longitudinal alterations of CT, and the PLS1 genes were significantly enriched in neurobiological processes, and dopaminergic- and cancer-related pathways. Combining Laplacian score and CCA analysis, we further linked DNAm of 33 representative genes from the 2,098 PLS1 genes with patients' reduction rate of clinical symptoms.

Conclusions

This study firstly revealed that changes of CT and clinical behaviors after treatment may be transcriptionally and epigenetically underlied. We define a "three-step" roadmap which represents a vital step toward the exploration of treatment- and treatment response-related biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.

Antipsychotics-Induced Changes in Synaptic Architecture and Functional Connectivity: Translational Implications for Treatment Response and Resistance

Schizophrenia is a severe mental illness characterized by alterations in processes that regulate both synaptic plasticity and functional connectivity between brain regions. Antipsychotics are the cornerstone of schizophrenia pharmacological treatment and, beyond occupying dopamine D2 receptors, can affect multiple molecular targets, pre- and postsynaptic sites, as well as intracellular effectors. Multiple lines of evidence point to the involvement of antipsychotics in sculpting synaptic architecture and remodeling the neuronal functional unit. Furthermore, there is an increasing awareness that antipsychotics with different receptor profiles could yield different interregional patterns of co-activation. In the present systematic review, we explored the fundamental changes that occur under antipsychotics' administration, the molecular underpinning, and the consequences in both acute and chronic paradigms. In addition, we investigated the relationship between synaptic plasticity and functional connectivity and systematized evidence on different topographical patterns of activation induced by typical and atypical antipsychotics.

Altered higher-order coupling between brain structure and function with embedded vector representations of connectomes in schizophrenia

It has been shown that the functional dependency of the brain exists in both direct and indirect regional relationships. Therefore, it is necessary to map higher-order coupling in brain structure and function to understand brain dynamic. However, how to quantify connections between not directly regions remains unknown to schizophrenia. The word2vec is a common algorithm through create embeddings of words to solve these problems. We apply the node2vec embedding representation to characterize features on each node, their pairwise relationship can give rise to correspondence relationships between brain regions. Then we adopt pearson correlation to quantify the higher-order coupling between structure and function in normal controls and schizophrenia. In addition, we construct direct and indirect connections to quantify the coupling between their respective functional connections. The results showed that higher-order coupling is significantly higher in schizophrenia. Importantly, the anomalous cause of coupling mainly focus on indirect structural connections. The indirect structural connections play an essential role in functional connectivity–structural connectivity (SC–FC) coupling. The similarity between embedded representations capture more subtle network underlying information, our research provides new perspectives for understanding SC–FC coupling. A strong indication that the structural backbone of the brain has an intimate influence on the resting-state functional.

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.

Predictive Biomarkers for Antipsychotic Treatment Response in Early Phase of Schizophrenia: Multi-Omic Measures Linking Subcortical Covariant Network, Transcriptomic Signatures, and Peripheral Epigenetics

Background

Volumetric alterations of subcortical structures as predictors of antipsychotic treatment response have been previously corroborated, but less is known about whether their morphological covariance relates to treatment outcome and is driven by gene expression and epigenetic modifications.

Methods

Subcortical volumetric covariance was analyzed by using baseline T1-weighted magnetic resonance imaging (MRI) in 38 healthy controls and 38 drug-naïve first-episode schizophrenia patients. Patients were treated with 8-week risperidone monotherapy and divided into responder and non-responder groups according to the Remission in Schizophrenia Working Group (RSWG). We utilized partial least squares (PLS) regression to examine the spatial associations between gene expression of subcortical structures from a publicly available transcriptomic dataset and between-group variances of structural covariance. The peripheral DNA methylation (DNAm) status of a gene of interest (GOI), overlapping between genes detected in the PLS and 108 schizophrenia candidate gene loci previously reported, was examined in parallel with MRI scanning.

Results

In the psychotic symptom dimension, non-responders had a higher baseline structural covariance in the putamen-hippocampus-pallidum-accumbens pathway compared with responders. For disorganized symptoms, significant differences in baseline structural covariant connections were found in the putamen-hippocampus-pallidum-thalamus circuit between the two subgroups. The imaging variances related to psychotic symptom response were spatially related to the expression of genes enriched in neurobiological processes and dopaminergic pathways. The DNAm of GOI demonstrated significant associations with patients' improvement of psychotic symptoms.

Conclusion

Baseline subcortical structural covariance and peripheral DNAm may relate to antipsychotic treatment response. Phenotypic variations in subcortical connectome related to psychotic symptom response may be transcriptomically and epigenetically underlaid. This study defines a roadmap for future studies investigating multimodal imaging epigenetic biomarkers for treatment response in schizophrenia.

Beneficial Effect of High-Frequency Repetitive Transcranial Magnetic Stimulation for the Verbal Memory and Default Mode Network in Healthy Older Adults

Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) is a non-invasive effective treatment for cognitive disorder, but its underlying mechanism of action remains unknown. The aim of this study was to explore the effect of a 2-week high-frequency (HF) active or sham 10 Hz rTMS on verbal memory in 40 healthy older adults. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to measure functional connectivity (FC) within the default mode network (DMN). Verbal memory performance was evaluated using an auditory verbal learning test (AVLT). Additionally, we evaluated the relationship between memory improvement and FC changes within the DMN. The results revealed that HF-rTMS can enhance immediate recall and delayed recall of verbal memory and increased the FC of the bilateral precuneus (PCUN) within the DMN. The positive correlations between the immediate recall memory and the FC of the left PCUN after a 2-week intervention of HF-rTMS were detected. In conclusion, HF-rTMS may have the potential to improve verbal memory performance in older adults, which relation to FC changes in the DMN. The current findings are useful for increasing the understanding of the mechanisms of HF-rTMS, as well as guiding HF-rTMS treatment of cognitive disorders.

Neurometabolic and functional changes of default-mode network relate to clinical recovery in first-episode psychosis patients: A longitudinal 1H-MRS and fMRI study

BACKGROUND

Antipsychotic treatment has improved the disrupted functional connectivity (FC) and neurometabolites levels of the default mode network (DMN) in schizophrenia patients, but a direct relationship between FC change, neurometabolic level alteration, and symptom improvement has not been built. This study examined the association between the alterations in DMN FC, the changes of neurometabolites levels in the medial prefrontal cortex (MPFC), and the improvementsinpsychopathology in a longitudinal study of drug-naïve first-episode psychosis (FEP) patients.

METHODS

Thirty-two drug-naïve FEP patients and 30 matched healthy controls underwent repeated assessments with the Positive and Negative Syndrome Scale (PANSS) and 3T proton magnetic resonance spectroscopy as well as resting-state functional magnetic resonance imaging. The levels of γ-aminobutyric acid, glutamate, N-acetyl-aspartate in MPFC, and the FC of DMN were measured. After 8-week antipsychotic treatment, 24 patients were re-examined.

RESULTS

After treatment, the changes in γ-aminobutyric acid were correlated with the alterations of FC between the MPFC and DMN, while the changes in N-acetyl-aspartate were associated with the alterations of FC between the posterior cingulate cortex/precuneus and DMN. The FC changes of both regions were correlated with patients PANSS positive score reductions. The structural equation modeling analyses revealed that the changes of DMN FC mediated the relationship between the changes of neurometabolites and the symptom improvements of the patients.

CONCLUSIONS

The derived neurometabolic-functional changes underlying the clinical recovery provide insights into the prognosis of FEP patients. It is noteworthy that this is an exploratory study, and future work with larger sample size is needed to validate our findings.

Altered Default Mode Network Is Associated With Cognitive Impairment in CADASIL as Revealed by Multimodal Neuoimaging

Background and Purpose: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy caused by mutations in the NOTCH3 gene is a hereditary cerebral small vessel disease, manifesting with stroke, cognitive impairment, and mood disturbances. Functional or structural changes in the default mode network (DMN), which plays important role in cognitive and mental maintenance, have been found in several neurological and mental diseases. However, it remains unclear whether DMN is altered in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Methods: Multimodal imaging methods, including MRI and positron emission tomography (PET), were applied to evaluate the functional, structural, and metabolic characteristics of DMN in 25 patients with CADASIL and 42 healthy controls. Results: Compared with controls, patients with CADASIL had decreased nodal efficiency and degree centrality of the dorsal medial pre-frontal cortex and hippocampal formation within DMN. Structural MRI and diffusion tensor imaging (DTI) showed decreased gray matter volume and fiber tracks presented in the bilateral hippocampal formation. Meanwhile, PET imaging showed decreased metabolism within the whole DMN in CADASIL. Furthermore, correlation analyses showed that these nodal characteristics, gray matter volume, and metabolic signals of DMN were related to cognitive scores in CADASIL. Conclusions: Our results suggested that altered network characteristics of DMN might play important roles in cognitive deficits of CADASIL.

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.

Abnormal Network Properties and Fiber Connections of DMN across Major Mental Disorders: A Probability Tracing and Graph Theory Study

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Aberrant default mode connectivity in adolescents with early-onset psychosis: A resting state fMRI study

Abnormal default mode network (DMN) connectivity has been found in schizophrenia and other psychotic disorders. However, there are limited studies on early onset psychosis (EOP), and their results show lack of agreement. Here, we investigated within-network DMN connectivity in EOP compared to healthy controls (HC), and its relationship to clinical characteristics. A sample of 68 adolescent patients with EOP (mean age 16.53 ± 1.12 [SD] years, females 66%) and 95 HC (mean age 16.24 ± 1.50 [SD], females 60%) from two Scandinavian cohorts underwent resting state functional magnetic resonance imaging (rsfMRI). A group independent component analysis (ICA) was performed to identify the DMN across all participants. Dual regression was used to estimate spatial maps reflecting each participant's DMN network, which were compared between EOP and HC using voxel-wise general linear models and permutation-based analyses. Subgroup analyses were performed within the patient group, to explore associations between diagnostic subcategories and current use of psychotropic medication in relation to connectivity strength. The analysis revealed significantly reduced DMN connectivity in EOP compared to HC in the posterior cingulate cortex, precuneus, fusiform cortex, putamen, pallidum, amygdala, and insula. The subgroup analysis in the EOP group showed strongest deviations for affective psychosis, followed by other psychotic disorders and schizophrenia. There was no association between DMN connectivity strength and the current use of psychotropic medication. In conclusion, the findings demonstrate weaker DMN connectivity in adolescent patients with EOP compared to healthy peers, and differential effects across diagnostic subcategories, which may inform our understanding of underlying disease mechanisms in EOP.

Multilevel growth curve analyses of behavioral activation for anhedonia (BATA) and mindfulness-based cognitive therapy effects on anhedonia and resting-state functional connectivity: Interim results of a randomized trial✰

BACKGROUND

The neural mechanisms associated with anhedonia treatment response are poorly understood. Additionally, no study has investigated changes in resting-state functional connectivity (rsFC) accompanying psychosocial treatment for anhedonia.

METHODS

We evaluated a novel psychotherapy, Behavioral Activation Therapy for Anhedonia (BATA, n = 38) relative to Mindfulness-Based Cognitive Therapy (MBCT, n = 35) in a medication-free, transdiagnostic, anhedonic sample in a parallel randomized controlled trial. Participants completed up to 15 sessions of therapy and up to four 7T MRI scans before, during, and after treatment (n = 185 scans). Growth curve models estimated change over time in anhedonia and in rsFC using average region-of-interest (ROI)-to-ROI connectivity within the default mode network (DMN), frontoparietal network (FPN), salience network, and reward network. Changes in rsFC from pre- to post-treatment were further evaluated using whole-network seed-to-voxel and ROI-to-ROI edgewise analyses.

RESULTS

Growth curve models showed significant reductions in anhedonia symptoms and in average rsFC within the DMN and FPN over time, across BATA and MBCT. There were no differences in anhedonia reductions between treatments. Within-person, changes in average rsFC were unrelated to changes in anhedonia. Between-person, higher than average FPN rsFC was related to less anhedonia across timepoints. Seed-to-voxel and edgewise rsFC analyses corroborated reductions within the DMN and between the DMN and FPN over time, across the sample.

CONCLUSIONS

Reductions in rsFC within the DMN, FPN, and between these networks co-occurred with anhedonia improvement across two psychosocial treatments for anhedonia. Future anhedonia clinical trials with a waitlist control group should disambiguate treatment versus time-related effects on rsFC.

Divergent Alterations of Structural-Functional Connectivity Couplings in First-episode and Chronic Schizophrenia Patients

Emerging evidence suggests that the coupling relating the structural connectivity (SC) of the brain to its functional connectivity (FC) exhibits remarkable changes during development, normal aging, and diseases. Although altered structural-functional connectivity couplings (SC-FC couplings) have been previously reported in schizophrenia patients, the alterations in SC-FC couplings of different illness stages of schizophrenia (SZ) remain largely unknown. In this study, we collected structural and resting-state functional MRI data from 73 normal controls (NCs), 61 first-episode (FeSZ) and 78 chronic (CSZ) schizophrenia patients. Positive and negative syndrome scale (PANSS) scores were assessed for all patients. Structural and functional brain networks were constructed using gray matter volume (GMV) and resting-state magnetic resonance imaging (rs-fMRI) time series measurements. At the connectivity level, the CSZ patients showed significantly increased SC-FC coupling strength compared with the FeSZ patients. At the node strength level, significant decreased SC-FC coupling strength was observed in the FeSZ patients compared to that of the NCs, and the coupling strength was positively correlated with negative PANSS scores. These results demonstrated divergent alterations of SC-FC couplings in FeSZ and CSZ patients. Our findings provide new insight into the neuropathological mechanisms underlying the developmental course of SZ.

The Effects of Antipsychotic Treatment on the Brain of Patients With First-Episode Schizophrenia: A Selective Review of Longitudinal MRI Studies

A large number of neuroimaging studies have detected brain abnormalities in first-episode schizophrenia both before and after treatment, but it remains unclear how these abnormalities reflect the effects of antipsychotic treatment on the brain. To summarize the findings in this regard and provide potential directions for future work, we reviewed longitudinal structural and functional imaging studies in patients with first-episode schizophrenia before and after antipsychotic treatment. A total of 36 neuroimaging studies was included, involving 21 structural imaging studies and 15 functional imaging studies. Both anatomical and functional brain changes in patients after treatment were consistently observed in the frontal and temporal lobes, basal ganglia, limbic system and several key components within the default mode network (DMN). Alterations in these regions were affected by factors such as antipsychotic type, course of treatment, and duration of untreated psychosis (DUP). Over all we showed that: (a) The striatum and DMN were core target regions of treatment in schizophrenia, and their changes were related to different antipsychotics; (b) The gray matter of frontal and temporal lobes tended to reduce after long-term treatment; and (c) Longer DUP was accompanied with faster hippocampal atrophy after initial treatment, which was also associated with poorer outcome. These findings are in accordance with previous notions but should be interpreted with caution. Future studies are needed to clarify the effects of different antipsychotics in multiple conditions and to identify imaging or other biomarkers that may predict antipsychotic treatment response. With such progress, it may help choose effective pharmacological interventional strategies for individuals experiencing recent-onset schizophrenia.

Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia

Schizophrenia (SCZ) is a highly heterogeneous disorder with remarkable intersubject variability in clinical presentations. Previous neuroimaging studies in SCZ have primarily focused on identifying group-averaged differences in the brain connectome between patients and healthy controls (HCs), largely neglecting the intersubject differences among patients. We acquired whole-brain resting-state functional MRI data from 121 SCZ patients and 183 HCs and examined the intersubject variability of the functional connectome (IVFC) in SCZ patients and HCs. Between-group differences were determined using permutation analysis. Then, we evaluated the relationship between IVFC and clinical variables in SCZ. Finally, we used datasets of patients with bipolar disorder (BD) and major depressive disorder (MDD) to assess the specificity of IVFC alteration in SCZ. The whole-brain IVFC pattern in the SCZ group was generally similar to that in HCs. Compared with the HC group, the SCZ group exhibited higher IVFC in the bilateral sensorimotor, visual, auditory, and subcortical regions. Moreover, altered IVFC was negatively correlated with age of onset, illness duration, and Brief Psychiatric Rating Scale scores and positively correlated with clinical heterogeneity. Although the SCZ shared altered IVFC in the visual cortex with BD and MDD, the alterations of IVFC in the sensorimotor, auditory, and subcortical cortices were specific to SCZ. The alterations of whole-brain IVFC in SCZ have potential implications for the understanding of the high clinical heterogeneity of SCZ and the future individualized clinical diagnosis and treatment of this disease.

Characteristics of White Matter Structural Networks in Chronic Schizophrenia Treated With Clozapine or Risperidone and Those Never Treated

BACKGROUND

Despite its benefits, a major concern regarding antipsychotic treatment is its possible impact on the brain's structure and function. This study sought to explore the characteristics of white matter structural networks in chronic never-treated schizophrenia and those treated with clozapine or risperidone, and its potential association with cognitive function.

METHODS

Diffusion tensor imaging was performed on a unique sample of 34 schizophrenia patients treated with antipsychotic monotherapy for over 5 years (17 treated with clozapine and 17 treated with risperidone), 17 never-treated schizophrenia patients with illness duration over 5 years, and 27 healthy control participants. Graph theory and network-based statistic approaches were employed.

RESULTS

We observed a disrupted organization of white matter structural networks as well as decreased nodal and connectivity characteristics across the schizophrenia groups, mainly involving thalamus, prefrontal, and occipital regions. Alterations in nodal and connectivity characteristics were relatively milder in risperidone-treated patients than clozapine-treated patients and never-treated patients. Altered global network measures were significantly associated with cognitive performance levels. Structural connectivity as reflected by network-based statistic mediated the difference in cognitive performance levels between clozapine-treated and risperidone-treated patients.

LIMITATIONS

These results are constrained by the lack of random assignment to different types of antipsychotic treatment.

CONCLUSION

These findings provide insight into the white matter structural network deficits in patients with chronic schizophrenia, either being treated or untreated, and suggest white matter structural networks supporting cognitive function may benefit from antipsychotic treatment, especially in those treated with risperidone.

Adjunct ketamine treatment of depression in treatment-resistant schizophrenia patients is unsatisfactory in pilot and secondary follow-up studies

OBJECTIVE

To investigate the effects of adjunct ketamine treatment on chronic treatment-resistant schizophrenia patients with treatment-resistant depressive symptoms (CTRS-TRD patients), including alterations in brain function.

METHODS

Intravenous ketamine (0.5 mg/kg body weight) was administered to CTRS-TRD patients over a 1-hr period on days 1, 4, 7, 10, 13, 16, 19, 22, and 25 of our initial pilot study. This treatment method was subsequently repeated 58 days after the start of the pilot study for a secondary follow-up study. Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), and regional homogeneity (ReHo) results were used to assess treatment effects and alterations in brain function throughout the entire duration of our studies.

RESULTS

Between day 7 and day 14 of the first treatment, CDSS scores were reduced by 63.8% and PANSS scores were reduced by 30.04%. In addition, ReHo values increased in the frontal, temporal, and parietal lobes. However, by day 21, depressive symptoms relapsed. During the second treatment period, CDSS and PANSS scores exhibited no significant differences compared to baseline between day 58 and day 86. On day 65, ReHo values were higher in the temporal, frontal, and parietal lobes. However, on day 79, the increase in ReHo values completely disappeared.

CONCLUSIONS

Depressive symptoms in CTRS-TRD patients were alleviated with adjunct ketamine treatment for only 1 week during the first treatment period. Moreover, after 1 month, the antidepressant effects of ketamine on CTRS-TRD patients completely disappeared. Correspondingly, ReHo alterations induced by ketamine in the CTRS-TRD patients were not maintained for more than 3 weeks. These pilot findings indicate that adjunct ketamine treatment is not satisfactory for CTRS-TRD patients.

Effect of Risperidone Monotherapy on Dynamic Functional Connectivity of Insular Subdivisions in Treatment-Naive, First-Episode Schizophrenia

OBJECTIVE

The insula consists of functionally diverse subdivisions, and each division plays different roles in schizophrenia neuropathology. The current study aimed to investigate the abnormal patterns of dynamic functional connectivity (dFC) of insular subdivisions in schizophrenia and the effect of antipsychotics on these connections.

METHODS

Longitudinal study of the dFC of insular subdivisions was conducted in 42 treatment-naive first-episode patients with schizophrenia at baseline and after 8 weeks of risperidone treatment based on resting-state functional magnetic resonance image (fMRI).

RESULTS

At baseline, patients showed decreased dFC variance (less variable) between the insular subdivisions and the precuneus, supplementary motor area and temporal cortex, as well as increased dFC variance (more variable) between the insular subdivisions and parietal cortex, compared with healthy controls. After treatment, the dFC variance of the abnormal connections were normalized, which was accompanied by a significant improvement in positive symptoms.

CONCLUSIONS

Our findings highlighted the abnormal patterns of fluctuating connectivity of insular subdivision circuits in schizophrenia and suggested that these abnormalities may be modified after antipsychotic treatment.

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.

Mapping Theme Trends and Knowledge Structure of Magnetic Resonance Imaging Studies of Schizophrenia: A Bibliometric Analysis From 2004 to 2018

BACKGROUND

Recently, magnetic resonance imaging (MRI) technology has been widely used to quantitatively analyze brain structure, morphology, and functional activities, as well as to clarify the neuropathological and neurobiological mechanisms of schizophrenia. However, although there have been many relevant results and conclusions, there has been no systematic assessment of this field.

AIM

To analyze important areas of research utilizing MRI in studies of schizophrenia and explore major trends and the knowledge structure using bibliometric analysis.

METHODS

Literature related to MRI studies of schizophrenia published in PubMed between January 1, 2004 and December 31, 2018 were retrieved in 5-year increments. The extracted major Medical Subject Headings (MeSH) terms/MeSH subheadings were analyzed quantitatively. Bi-clu-stering analysis, social network analysis (SNA), and strategic diagrams were employed to analyze the word matrix and co-occurrence matrix of high-frequency MeSH terms.

RESULTS

For the periods of 2004 to 2008, 2009 to 2013, and 2014 to 2018, the number of relevant retrieved publications were 916, 1,344, and 1,512 respectively, showing an overall growth trend. 26, 34, and 36 high-frequency major MeSH terms/MeSH subheadings were extracted in each period, respectively. In line with strategic diagrams, the main undeveloped theme clusters in 2004-2008 were effects of antipsychotics on brain structure and their curative efficacy. These themes were replaced in 2009-2013 by physiopathology mechanisms of schizophrenia, etiology of cognitive disorder, research on default mode network and schizophrenic psychology, and were partially replaced in 2014-2018 by studies of differences in the neurobiological basis for schizophrenia and other mental disorders. Based on SNA, nerve net/physiopathology and psychotic disorder/pathology were considered the emerging hotspots of research in 2009-2013 and 2014-2018.

CONCLUSIONS

MRI studies on schizophrenia were relatively diverse, but the theme clusters derived from each period may reflect the publication trends to some extent. Bibliometric research over a 15-year period may be helpful in depicting the overall scope of research interest and may generate novel ideas for researchers initiating new projects.

Treatment of auditory verbal hallucinations with atypical antipsychotics in healthy individuals: an artificially controlled post-treatment report

OBJECTIVE

This study was performed to investigate the effects and associated global functional connectivity density (gFCD) alterations associated with the use of atypical antipsychotics in healthy individuals with auditory verbal hallucinations (Hi-AVHs) using gFCD mapping techniques.

METHODS

A magnetic resonance imaging database of 38 Hi-AVHs with chronic or severe AVH symptoms was generated. The Hi-AVHs were administered an atypical antipsychotic (risperidone) for 24 weeks and monitored for a treatment response. All patients underwent functional magnetic resonance imaging pre- and post-treatment.

RESULTS

gFCD alterations were found in the auditory-memory-language and visual circuit regions pre- and post-treatment. However, gFCD alterations differed between patients with strong and weak treatment responses.

CONCLUSION

This is the first report to show that atypical antipsychotics can improve the symptoms of AVHs and that the treatment effects are associated with gFCD alterations in the auditory-memory-language circuit. These findings provide a foundation for future exploration of new treatment strategies for Hi-AVHs.

Subtle white matter alterations in schizophrenia identified with a new measure of fiber density

Altered cerebral connectivity is one of the core pathophysiological mechanism underlying the development and progression of information-processing deficits in schizophrenia. To date, most diffusion tensor imaging (DTI) studies used fractional anisotropy (FA) to investigate disrupted white matter connections. However, a quantitative interpretation of FA changes is often impeded by the inherent limitations of the underlying tensor model. A more fine-grained measure of white matter alterations could be achieved by measuring fiber density (FD) - a novel non-tensor-derived diffusion marker. This study investigates, for the first time, FD alterations in schizophrenia patients. FD and FA maps were derived from diffusion data of 25 healthy controls (HC) and 21 patients with schizophrenia (SZ). Using tract-based spatial statistics (TBSS), group differences in FD and FA were investigated across the entire white matter. Furthermore, we performed a region of interest (ROI) analysis of frontal fasciculi to detect potential correlations between FD and positive symptoms. As a result, whole brain TBSS analysis revealed reduced FD in SZ patients compared to HC in several white matter tracts including the left and right thalamic radiation (TR), superior longitudinal fasciculus (SLF), corpus callosum (CC), and corticospinal tract (CST). In contrast, there were no significant FA differences between groups. Further, FD values in the TR were negatively correlated with the severity of positive symptoms and medication dose in SZ patients. In summary, a novel diffusion-weighted data analysis approach enabled us to identify widespread FD changes in SZ patients with most prominent white matter alterations in the frontal and subcortical regions. Our findings suggest that the new FD measure may be more sensitive to subtle changes in the white matter microstructure compared to FA, particularly in the given population. Therefore, investigating FD may be a promising approach to detect subtle changes in the white matter microstructure of altered connectivity in schizophrenia.