Functional and anatomical connectivity abnormalities in left inferior frontal gyrus in schizophrenia

Aberrant activity at rest of the associative striatum in schizophrenia: Meta-analyses of the amplitude of low frequency fluctuations

Schizophrenia is a severe psychiatric disorder associated with brain alterations at rest. Amplitude of low-frequency fluctuations (ALFF) and its fractional version (fALFF) have been widely used to investigate alterations in spontaneous brain activity in schizophrenia. However, results are still inconsistent. Furthermore, while these measurements are similar, they showed some differences, and no meta-analysis has been yet performed to compare them in schizophrenia. Thus, we conducted systematic research in five databases and in the grey literature to find articles investigating fALFF and/or ALFF alterations in schizophrenia. Two separate meta-analyses were performed using the SDM-PSI software to identify fALFF and ALFF alterations separately. Then, a conjunction analysis was conducted to determine congruent results between the two approaches. We found that patients with schizophrenia showed altered fALFF activity in the left insula/putamen, the right paracentral lobule and the left middle occipital gyrus compared to healthy individuals. Patients with schizophrenia exhibited ALFF alterations in the bilateral putamen, the bilateral caudate nucleus, the bilateral inferior frontal gyrus, the right precuneus, the right precentral gyrus, the left postcentral gyrus, the right posterior cingulate gyrus, compared to healthy controls. ALFF increased activity in the left putamen was higher in drug-naïve patients and was correlated with positive symptoms. The conjunction analysis revealed a spatial convergence between fALFF and ALFF studies in the left putamen. This left putamen cluster is part of the associative striatum. Its alteration in schizophrenia provides additional support to the influential aberrant salience hypothesis of psychosis.

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.

Altered brain and physiological stress responses in early psychosis

Stress is proposed to be a crucial factor in the onset and presentation of psychosis. The early stage of psychosis provides a window into how stress interacts with the emergence of psychosis. Yet, how people with early psychosis respond to stress remains unclear. The current study examined how stress responses (brain, physiological, self-report) differ in early psychosis. Forty participants (20 early psychosis [EP], 20 healthy controls [HC]) completed a stress task in the scanner that involved viewing stressful and neutral-relaxing images. Physiological responses (cortisol, heart rate) and self-report of stress were also assessed. Region of Interest analyses were conducted with brain regions previously shown to be activated during the stress task (amygdala, hippocampus, striatum, hypothalamus, prefrontal cortex [dorsolateral, ventrolateral, medial orbital]). Linear mixed models were used to test for effects of group (EP, HC) and emotion (stress, neutral-relaxing). HC had higher hippocampus activation to stress versus neutral-relaxing conditions while EP did not show a difference (group x emotion interaction, p = 0.04). There were also significant main effects of group with EP having higher amygdala activation (p = 0.01), ventrolateral prefrontal cortex activation (vlPFC, p = 0.03), self-report of stress (p = 0.01), and heart rate (p < 0.001). Our study found preliminary evidence that people with early psychosis showed heightened response to stressful and non-threatening situations, across multiple levels of stress responses. Our findings suggest a novel perspective on stress alterations in early psychosis and highlight the importance of considering both stressful and non-stressful situations.

Social Cognition and Functional Connectivity in Early and Chronic Schizophrenia

BACKGROUND

Individuals with schizophrenia (SZ) experience impairments in social cognition that contribute to poor functional outcomes. However, mechanisms of social cognitive dysfunction in SZ remain poorly understood, which impedes the design of novel interventions to improve outcomes. In this preregistered project, we examined the representation of social cognition in the brain's functional architecture in early and chronic SZ.

METHODS

The study contains 2 parts: a confirmatory and an exploratory portion. In the confirmatory portion, we identified resting-state connectivity disruptions evident in early and chronic SZ. We performed a connectivity analysis using regions associated with social cognitive dysfunction in early and chronic SZ to test whether aberrant connectivity observed in chronic SZ (n = 47 chronic SZ and n = 52 healthy control participants) was also present in early SZ (n = 71 early SZ and n = 47 healthy control participants). In the exploratory portion, we assessed the out-of-sample generalizability and precision of predictive models of social cognition. We used machine learning to predict social cognition and established generalizability with out-of-sample testing and confound control.

RESULTS

Results revealed decreases between the left inferior frontal gyrus and the intraparietal sulcus in early and chronic SZ, which were significantly associated with social and general cognition and global functioning in chronic SZ and with general cognition and global functioning in early SZ. Predictive modeling revealed the importance of out-of-sample evaluation and confound control.

CONCLUSIONS

This work provides insights into the functional architecture in early and chronic SZ and suggests that inferior frontal gyrus-intraparietal sulcus connectivity could be a prognostic biomarker of social impairments and a target for future interventions (e.g., neuromodulation) focused on improved social functioning.

Machine Learning in Electroconvulsive Therapy: A Systematic Review

ABSTRACT

Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine learning approaches due to the large data sets with data captured through electroencephalography (EEG) and other objective measures. A systematic review of 6 databases led to the full-text examination of 26 articles using machine learning approaches in examining data predicting response to ECT treatment. The identified articles used a wide variety of data types covering structural and functional imaging data (n = 15), clinical data (n = 5), a combination of clinical and imaging data (n = 2), EEG (n = 3), and social media posts (n = 1). The clinical indications in which response prediction was assessed were depression (n = 21) and psychosis (n = 4). Changes in multiple anatomical regions in the brain were identified as holding a predictive value for response to ECT. These primarily centered on the limbic system and associated networks. Clinical features predicting good response to ECT in depression included shorter duration, lower severity, higher medication dose, psychotic features, low cortisol levels, and positive family history. It has also been possible to predict the likelihood of relapse of readmission with psychosis after ECT treatment, including a better response if higher transfer entropy was calculated from EEG signals. A transdisciplinary approach with an international consortium collecting a wide range of retrospective and prospective data may help to refine and extend these outcomes and translate them into clinical practice.

Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

Resting-state functional connectivity correlates of antipsychotic treatment in unmedicated schizophrenia

BACKGROUND

Antipsychotics may modulate the resting state functional connectivity(rsFC) to improve clinical symptoms in schizophrenia(Sz). Existing literature has potential confounders like past medication effects and evaluating preselected regions/networks. We aimed to evaluate connectivity pattern changes with antipsychotics in unmedicated Sz using Multivariate pattern analysis(MVPA), a data-driven technique for whole-brain connectome analysis.

METHODS

Forty-seven unmedicated patients with Sz(DSM-IV-TR) underwent clinical evaluation and neuroimaging at baseline and after 3-months of antipsychotic treatment. Resting-state functional MRI was analysed using group-MVPA to derive 5-components. The brain region with significant connectivity pattern changes with antipsychotics was identified, and post-hoc seed-to-voxel analysis was performed to identify connectivity changes and their association with symptom changes.

RESULTS

Connectome-MVPA analysis revealed the connectivity pattern of a cluster localised to left anterior cingulate and paracingulate gyri (ACC/PCG) (peak coordinates:x = -04,y = +30,z = +26;k = 12;cluster-p_FWE=0.002) to differ significantly after antipsychotics. Specifically, its connections with clusters of precuneus/posterior cingulate cortex(PCC) and left inferior temporal gyrus(ITG) correlated with improvement in positive and negative symptoms scores, respectively.

CONCLUSION

ACC/PCG, a hub of the default mode network, seems to mediate the antipsychotic effects in unmedicated Sz. Evaluating causality models with data from randomised controlled design using the MVPA approach would further enhance our understanding of therapeutic connectomics in Sz.

Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study

Although many studies on brain-age prediction in patients with schizophrenia have been reported recently, none has predicted brain age based on different neuroimaging modalities and different brain regions in these patients. Here, we constructed brain-age prediction models with multimodal MRI and examined the deviations of aging trajectories in different brain regions of participants with schizophrenia recruited from multiple centers. The data of 230 healthy controls (HCs) were used for model training. Next, we investigated the differences in brain age gaps between participants with schizophrenia and HCs from two independent cohorts. A Gaussian process regression algorithm with fivefold cross-validation was used to train 90, 90, and 48 models for gray matter (GM), functional connectivity (FC), and fractional anisotropy (FA) maps in the training dataset, respectively. The brain age gaps in different brain regions for all participants were calculated, and the differences in brain age gaps between the two groups were examined. Our results showed that most GM regions in participants with schizophrenia in both cohorts exhibited accelerated aging, particularly in the frontal lobe, temporal lobe, and insula. The parts of the white matter tracts, including the cerebrum and cerebellum, indicated deviations in aging trajectories in participants with schizophrenia. However, no accelerated brain aging was noted in the FC maps. The accelerated aging in 22 GM regions and 10 white matter tracts in schizophrenia potentially exacerbates with disease progression. In individuals with schizophrenia, different brain regions demonstrate dynamic deviations of brain aging trajectories. Our findings provided more insights into schizophrenia neuropathology.

Structural and Functional Brain Changes in Acute Takotsubo Syndrome

BACKGROUND

Takotsubo syndrome mimics an acute myocardial infarction, typically in the aftermath of mental or physical stress.

OBJECTIVES

The mechanism by which emotional processing in the context of stress leads to significant cardiac injury is poorly understood, so a full exploration of brain structure and function in takotsubo syndrome patients merits investigation.

METHODS

Twenty-five acute (<5 days) takotsubo patients and 25 control subjects were recruited into this observational cross-sectional study. Surface-based morphometry was carried out on magnetic resonance imaging (MRI) brain scans to extract cortical morphology based on volume, thickness, and surface area with the use of Freesurfer. Cortical morphology general linear models were corrected for age, sex, photoperiod, and total brain volume. Resting-state functional MRI and diffusion tensor tractography images were preprocessed and analyzed with the use of the Functional Magnetic Resonance Imaging of the Brain Diffusion Toolbox and Functional Connectivity Toolbox.

RESULTS

There was significantly smaller total white matter and subcortical gray matter volumes in takotsubo (P < 0.001), with smaller total brain surface area but increased total cortical thickness (both P < 0.001). Individual gray matter regions (hippocampus and others) were significantly smaller in takotsubo (P < 0.001); only thalamus and insula were larger (P < 0.001). There was significant hyperfunctional and hypofunctional connectivity in multiple areas, including thalamus-amygdala-insula and basal ganglia (P < 0.05). All structural tractography connections were increased in takotsubo (P < 0.05).

CONCLUSIONS

The authors showed smaller gray and white matter volumes driven by smaller cortical surface area, but increased cortical thickness and structural tractography connections with bidirectional changes in functional connectivity linked to emotion, language, reasoning, perception, and autonomic control. These are interventional targets in takotsubo patients' rehabilitation.

The Static and dynamic functional connectivity characteristics of the left temporoparietal junction region in schizophrenia patients with auditory verbal hallucinations during low-frequency rTMS treatment

BACKGROUND

Auditory verbal hallucinations (AVH) are a core symptom of schizophrenia. Low-frequency (e.g., 1 Hz) repetitive transcranial magnetic stimulation (rTMS) targeting language processing regions (e.g., left TPJ) has been evident as a potential treatment for AVH. However, the underlying neural mechanisms of the rTMS treatment effect remain unclear. The present study aimed to investigate the effects of 1 Hz rTMS on functional connectivity (FC) of the temporoparietal junction area (TPJ) seed with the whole brain in schizophrenia patients with AVH.

METHODS

Using a single-blind placebo-controlled randomized clinical trial, 55 patients with AVH were randomly divided into active treatment group (n = 30) or placebo group (n = 25). The active treatment group receive 15-day 1 Hz rTMS stimulation to the left TPJ, whereas the placebo group received sham rTMS stimulation to the same site. Resting-state fMRI scans and clinical measures were acquired for all patients before and after treatment. The seed-based (left TPJ) static and DFC was used to assess the connectivity characteristics during rTMS treatment in patients with AVH.

RESULTS

Overall, symptom improvement following 1 Hz rTMS treatment was found in the active treatment group, whereas no change occurred in the placebo group. Moreover, decreased static FC (SFC) of the left TPJ with the right temporal lobes, as well as increased SFC with the prefrontal cortex and subcortical structure were observed in active rTMS group. Increased dynamic FC (DFC) of the left TPJ with frontoparietal areas was also found in the active rTMS group. However, seed-based SFC and DFC were reduced to a great extent in the placebo group. In addition, these changed FC (SFC) strengths in the active rTMS group were associated with reduced severity of clinical outcomes (e.g., positive symptoms).

CONCLUSION

The application of 1 Hz rTMS over the left TPJ may affect connectivity characteristics of the targeted region and contribute to clinical improvement, which shed light on the therapeutic effect of rTMS on schizophrenia with AVH.

Estimating effective connectivity in Alzheimer's disease progression: A dynamic causal modeling study

Introduction

Alzheimer's disease (AD) affects the whole brain from the cellular level to the entire brain network structure. The causal relationship among brain regions concerning the different AD stages is not yet investigated. This study used Dynamic Causal Modeling (DCM) method to assess effective connectivity (EC) and investigate the changes that accompany AD progression.

Methods

We included the resting-state fMRI data of 34 AD patients, 31 late mild cognitive impairment (LMCI) patients, 34 early MCI (EMCI) patients, and 31 cognitive normal (CN) subjects selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The parametric Empirical Bayes (PEB) method was used to infer the effective connectivities and the corresponding probabilities. A linear regression analysis was carried out to test if the connection strengths could predict subjects' cognitive scores.

Results

The results showed that the connections reduced from full connection in the CN group to no connection in the AD group. Statistical analysis showed the connectivity strengths were lower for later-stage patients. Linear regression analysis showed that the connection strengths were partially predictive of the cognitive scores.

Discussion

Our results demonstrated the dwindling connectivity accompanying AD progression on causal relationships among brain regions and indicated the potential of EC as a loyal biomarker in AD progression.

Hemispheric lateralization of semantic processing before and after aripiprazole treatment in first-episode psychosis or ultra-high risk state

Whether aberrant language-related lateralization can be improved after antipsychotic treatment in drug-free patients with first-episode psychosis or ultra-high risk state is little known. We aimed to investigate the improvement in lateralization of semantic processing after antipsychotic treatment and associated clinical and cognitive changes. Twenty-one drug-free patients with first-episode psychosis or ultra-high risk state underwent functional magnetic resonance imaging with a semantic task, neuropsychological testing, and clinical assessments with the Positive and Negative Syndrome Scale before and after 6 weeks of aripiprazole treatment. A lateralization index of the region of interest, i.e., inferior frontal gyrus, was calculated and correlated with the behavioral indices of the semantic task, Positive and Negative Syndrome Scale scores, and language-related neuropsychological test scores. After treatment, the lateralization index of the inferior frontal gyrus was significantly increased, which was related to reduced activation of the right inferior frontal gyrus. The increase in the lateralization index was significantly associated with the increase in verbal fluency score. A higher baseline accuracy of the semantic task was associated with a higher post-treatment lateralization index of the inferior frontal gyrus and greater improvement of the total score and positive subscore of the Positive and Negative Syndrome Scale. Our findings indicated aripiprazole treatment significantly increased semantic processing-related lateralization in the inferior frontal gyrus in drug-free patients with first-episode psychosis or ultra-high risk state. A higher baseline accuracy might predict a higher post-treatment lateralization index and greater symptom improvement.

Exploring Brain Structural and Functional Biomarkers in Schizophrenia via Brain-Network-Constrained Multi-View SCCA

Recent studies have proved that dynamic regional measures extracted from the resting-state functional magnetic resonance imaging, such as the dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), could provide a great insight into brain dynamic characteristics of the schizophrenia. However, the unimodal feature is limited for delineating the complex patterns of brain deficits. Thus, functional and structural imaging data are usually analyzed together for uncovering the neural mechanism of schizophrenia. Investigation of neural function-structure coupling enables to find the potential biomarkers and further helps to understand the biological basis of schizophrenia. Here, a brain-network-constrained multi-view sparse canonical correlation analysis (BN-MSCCA) was proposed to explore the intrinsic associations between brain structure and dynamic brain function. Specifically, the d-fALFF was first acquired based on the sliding window method, whereas the gray matter map was computed based on voxel-based morphometry analysis. Then, the region-of-interest (ROI)-based features were extracted and further selected by performing the multi-view sparse canonical correlation analysis jointly with the diagnosis information. Moreover, the brain-network-based structural constraint was introduced to prompt the detected biomarkers more interpretable. The experiments were conducted on 191 patients with schizophrenia and 191 matched healthy controls. Results showed that the BN-MSCCA could identify the critical ROIs with more sparse canonical weight patterns, which are corresponding to the specific brain networks. These are biologically meaningful findings and could be treated as the potential biomarkers. The proposed method also obtained a higher canonical correlation coefficient for the testing data, which is more consistent with the results on training data, demonstrating its promising capability for the association identification. To demonstrate the effectiveness of the potential clinical applications, the detected biomarkers were further analyzed on a schizophrenia-control classification task and a correlation analysis task. The experimental results showed that our method had a superior performance with a 5-8% increment in accuracy and 6-10% improvement in area under the curve. Furthermore, two of the top-ranked biomarkers were significantly negatively correlated with the positive symptom score of Positive and Negative Syndrome Scale (PANSS). Overall, the proposed method could find the association between brain structure and dynamic brain function, and also help to identify the biological meaningful biomarkers of schizophrenia. The findings enable our further understanding of this disease.

Altered Coupling of Cerebral Blood Flow and Functional Connectivity Strength in First-Episode Schizophrenia Patients With Auditory Verbal Hallucinations

Objective

Auditory verbal hallucinations (AVHs) are a major symptom of schizophrenia and are connected with impairments in auditory and speech-related networks. In schizophrenia with AVHs, alterations in resting-state cerebral blood flow (CBF) and functional connectivity have been described. However, the neurovascular coupling alterations specific to first-episode drug-naïve schizophrenia (FES) patients with AVHs remain unknown.

Methods

Resting-state functional MRI and arterial spin labeling (ASL) was performed on 46 first-episode drug-naïve schizophrenia (FES) patients with AVHs (AVH), 39 FES drug-naïve schizophrenia patients without AVHs (NAVH), and 48 healthy controls (HC). Then we compared the correlation between the CBF and functional connection strength (FCS) of the entire gray matter between the three groups, as well as the CBF/FCS ratio of each voxel. Correlation analyses were performed on significant results between schizophrenia patients and clinical measures scale.

Results

The CBF/FCS ratio was reduced in the cognitive and emotional brain regions in both the AVH and NAVH groups, primarily in the crus I/II, vermis VI/VII, and cerebellum VI. In the AVH group compared with the HC group, the CBF/FCS ratio was higher in auditory perception and language-processing areas, primarily the left superior and middle temporal gyrus (STG/MTG). The CBF/FCS ratio in the left STG and left MTG positively correlates with the score of the Auditory Hallucination Rating Scale in AVH patients.

Conclusion

These findings point to the difference in neurovascular coupling failure between AVH and NAVH patients. The dysfunction of the forward model based on the predictive and computing role of the cerebellum may increase the excitability in the auditory cortex, which may help to understand the neuropathological mechanism of AVHs.

Processing Argument Structure and Syntactic Complexity in People with Schizophrenia Spectrum Disorders

INTRODUCTION

Deficits in language comprehension and production have been repeatedly observed in Schizophrenia Spectrum Disorders (SSD). However, the characterization of the language profile of this population is far from complete, and the relationship between language deficits, impaired thinking and cognitive functions is widely debated.

OBJECTIVE

The aims of the present study were to assess production and comprehension of verbs with different argument structures, as well as production and comprehension of sentences with canonical and non-canonical word order in people with SSD. In addition, the study investigated the relationship between language deficits and cognitive functions.

METHODS

Thirty-four participants with a diagnosis of SSD and a group of healthy control participants (HC) were recruited and evaluated using the Italian version of the Northwestern Assessment of Verbs and Sentences (NAVS, Cho-Reyes & Thompson, 2012; Barbieri et al., 2019).

RESULTS

Results showed that participants with SSD were impaired - compared to HC - on both verb and sentence production, as well as on comprehension of syntactically complex (but not simple) sentences. While verb production was equally affected by verb-argument structure complexity in both SSD and HC, sentence comprehension was disproportionately more affected by syntactic complexity in SSD than in HC. In addition, in the SSD group, verb production deficits were predicted by performance on a measure of visual attention, while sentence production and comprehension deficits were explained by performance on measures of executive functions and working memory, respectively.

DISCUSSION

Our findings support the hypothesis that language deficits in SSD may be one aspect of a more generalized, multi-domain, cognitive impairment, and are consistent with previous findings pointing to reduced inter- and intra-hemispheric connectivity as a possible substrate for such deficits. The study provides a systematic characterization of lexical and syntactic deficits in SSD and demonstrates that psycholinguistically-based assessment tools may be able to capture language deficits in this population.

Altered Brain Criticality in Schizophrenia: New Insights From Magnetoencephalography

Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements toward a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient population. In this study, the resting-state neuromagnetic signals of schizophrenia patients and healthy controls were analyzed in the framework of criticality. When biological systems like the brain are in a state of criticality, they are thought to be functioning at maximum efficiency (e.g., optimal communication and storage of information) and with maximum adaptability to incoming information. Here, we assessed the self-similarity and multifractality of resting-state brain signals recorded with magnetoencephalography in patients with schizophrenia patients and in matched controls. Schizophrenia patients had similar, although attenuated, patterns of self-similarity and multifractality values. Statistical tests showed that patients had higher values of self-similarity than controls in fronto-temporal regions, indicative of more regularity and memory in the signal. In contrast, patients had less multifractality than controls in the parietal and occipital regions, indicative of less diverse singularities and reduced variability in the signal. In addition, supervised machine-learning, based on logistic regression, successfully discriminated the two groups using measures of self-similarity and multifractality as features. Our results provide new insights into the baseline cognitive functioning of schizophrenia patients by identifying key alterations of criticality properties in their resting-state brain data.

The Processing of Semantic Complexity and Cospeech Gestures in Schizophrenia: A Naturalistic, Multimodal fMRI Study

Schizophrenia is marked by aberrant processing of complex speech and gesture, which may contribute functionally to its impaired social communication. To date, extant neuroscientific studies of schizophrenia have largely investigated dysfunctional speech and gesture in isolation, and no prior research has examined how the two communicative channels may interact in more natural contexts. Here, we tested if patients with schizophrenia show aberrant neural processing of semantically complex story segments, and if speech-associated gestures (co-speech gestures) might modulate this effect. In a functional MRI study, we presented to 34 participants (16 patients and 18 matched-controls) an ecologically-valid retelling of a continuous story, performed via speech and spontaneous gestures. We split the entire story into ten-word segments, and measured the semantic complexity for each segment with idea density, a linguistic measure that is commonly used clinically to evaluate aberrant language dysfunction at the semantic level. Per segment, the presence of numbers of gestures varied (n = 0, 1, +2). Our results suggest that, in comparison to controls, patients showed reduced activation for more complex segments in the bilateral middle frontal and inferior parietal regions. Importantly, this neural aberrance was normalized in segments presented with gestures. Thus, for the first time with a naturalistic multimodal stimulation paradigm, we show that gestures reduced group differences when processing a natural story, probably by facilitating the processing of semantically complex segments of the story in schizophrenia.

Dimensional distribution of cortical abnormality across antipsychotics treatment-resistant and responsive schizophrenia

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Different etiology is assumed in treatment-resistant and responsive schizophrenia.

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Patients with treatment-resistant schizophrenia were classified from controls.

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Patients with non-treatment-resistant schizophrenia were classified from controls.

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Two classifications reached area under the curve as high as 0.69 and 0.85.

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Area under the curve remained as high as 0.69 when two classifiers were swapped.

Background

One-third of patients with schizophrenia are treatment-resistant to non-clozapine antipsychotics (TRS), while the rest respond (NTRS). Examining whether TRS and NTRS represent different pathophysiologies is an important step toward precision medicine.

Methods

Focusing on cortical thickness (CT), we analyzed international multi-site cross-sectional datasets of magnetic resonance imaging comprising 110 patients with schizophrenia (NTRS = 46, TRS = 64) and 52 healthy controls (HCs). We utilized a logistic regression with L1-norm regularization to find brain regions related to either NTRS or TRS. We conducted nested 10-fold cross-validation and computed the accuracy and area under the curve (AUC). Then, we applied the NTRS classifier to patients with TRS, and vice versa.

Results

Patients with NTRS and TRS were classified from HCs with 65% and 78% accuracies and with the AUC of 0.69 and 0.85 (p = 0.014 and < 0.001, corrected), respectively. The left planum temporale (PT) and left anterior insula/inferior frontal gyrus (IFG) contributed to both NTRS and TRS classifiers. The left supramarginal gyrus only contributed to NTRS and right superior temporal sulcus and right lateral orbitofrontal cortex only to the TRS. The NTRS classifiers successfully distinguished those with TRS from HCs with the AUC of 0.78 (p < 0.001), while the TRS classifiers classified those with NTRS from HCs with the AUC of 0.69 (p = 0.015).

Conclusion

Both NTRS and TRS could be distinguished from HCs on the basis of CT. The CT pathological basis of NTRS and TRS has commonalities, and TRS presents unique CT features.

Implications for Early Diagnosis and Treatment in Schizophrenia Due to Correlation between Auditory Perceptual Deficits and Cognitive Impairment

It is indicated that auditory perception deficits are present in schizophrenia and related to formal thought disorder. The purpose of the present study was to investigate the association of auditory deficits with cognitive impairment in schizophrenia. An experimental group of 50 schizophrenia patients completed a battery of auditory processing evaluation and a neuropsychological battery of tests. Correlations between neuropsychological battery scores and auditory processing scores were examined. Cognitive impairment was correlated with auditory processing deficits in schizophrenia patients. All neuropsychological test scores were significantly correlated with at least one auditory processing test score. Our findings support the coexistence of auditory processing disorder, severe cognitive impairment, and formal thought disorder in a subgroup of schizophrenia patients. This may have important implications in schizophrenia research, as well as in early diagnosis and nonpharmacological treatment of the disorder.

Fronto-parietal network function during cued visual search in the first-episode schizophrenia spectrum

Cognitive impairments account for significant morbidity in schizophrenia and are present at disease onset. Controlled processes are particularly susceptible and may contribute to pervasive selective attention deficits. The present study assessed fronto-parietal attention network (FPAN) functioning during cue presentation on a visual search task in first-episode schizophrenia spectrum patients (FE) and its relation to symptom burden and community functioning. Brain activity was recorded with magnetoencephalography from 38 FE and 38 healthy controls (HC) during blocks of pop-out and serial search target detection. Activity during cue presentation was compared between groups across bilateral FPAN regions (frontal eye fields (FEF), inferior frontal gyrus (IFG), midcingulate cortex (MCC), and intraparietal sulcus (IPS)). FE exhibited greater right hemisphere IFG activity despite worse performance relative to HC. Performance and FPAN activity were not correlated in HC. Among FE, however, stronger activity within right hemisphere FEF and IFG was associated with faster responses. Stronger right IPS and left IFG activity in patients was also associated with reduced negative symptoms and improved community functioning, respectively. Increased reliance on the FPAN for task completion suggests an inefficient cognitive control network and might reflect a compensation for impaired attentional deployment during target detection, a strategy employed by those with less severe illness. These findings represent a critical step towards identifying the neural substrates of negative symptoms and impaired neurocognition at disease onset.

Functional connectivity of cerebellar dentate nucleus and cognitive impairments in patients with drug-naive and first-episode schizophrenia

Cognitive impairments are the hallmark of schizophrenia and prominent in the early episode stage. However, the underlying pathological mechanisms of cognitive impairments are not fully understood. This study aimed to investigate the abnormal functional connectivity (FC) of the cerebellar dentate nucleus (DN) and its correlation with cognitive impairments in patients with drug-naive and first-episode schizophrenia. Resting-state functional magnetic resonance imaging data were acquired in 47 patients and 43 healthy controls. Cognitive functions were assessed by number sequence span, verbal category fluency, digit-symbol coding tests. The results showed that the patients had deficits in all three cognitive tests compared to the controls. Furthermore, the increased FC of DN with the bilateral postcentral gyrus and decreased FC of DN with the right inferior temporal gyrus and regional cerebellum (e.g., Vermis 4-5 and Crus I) were observed in the patient group compared to the control group. Importantly, these abnormal DN FC significantly correlated with cognitive tests (e.g., number sequence span and digit-symbol coding) and clinical symptoms (e.g., negative symptom) in the patient group. The results suggested that abnormal FC of DN with cortical and subcortical regions was associated with cognitive impairments and symptom severity and might be an underlying neural mechanism in schizophrenia.

Cortical morphometric correlational networks associated with cognitive deficits in first episode schizophrenia

Schizophrenia (SCZ) is a chronic cognitive and behavioral disorder associated with abnormal cortical activity during information processing. Several brain structures associated with the seven performance domains evaluated using the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery (MCCB) have shown cortical volume loss in first episode schizophrenia (FES) patients. However, the relationship between morphological organization and MCCB performance remains unclear. Therefore, in the current observational study, high-resolution structural MRI scans were collected from 50 FES patients, and the morphometric correlation network (MCN) using cortical volume was established to characterize the cortical pattern associated with poorer MCCB performance. We also investigated topological properties, such as the modularity, the degree and the betweenness centrality. Our findings show structural volume was directly and strongly associated with the cognitive deficits of FES patients in the precuneus, anterior cingulate, and fusiform gyrus, as well as the prefrontal, parietal, and sensorimotor cortices. The medial orbitofrontal, fusiform, and superior frontal gyri were not only identified as the predominant nodes with high degree and betweenness centrality in the MCN, but they were also found to be critical in performance in several of the MCCB domains. Together, these results suggest a widespread cortical network is altered in FES patients and that performance on the MCCB domains is associated with the core pathophysiology of SCZ.

Abnormalities in hemispheric lateralization of intra- and inter-hemispheric white matter connections in schizophrenia

Hemispheric lateralization is a prominent feature of the human brain and is grounded into intra- and inter-hemispheric white matter (WM) connections. However, disruptions in hemispheric lateralization involving both intra- and inter-hemispheric WM connections in schizophrenia is still unclear. Hence, a quantitative measure of the hemispheric lateralization of intra- and inter-hemispheric WM connections could provide new insights into schizophrenia. This work performed diffusion tensor imaging on 50 patients and 58 matched healthy controls. Using graph theory, the global and nodal efficiencies were computed for both intra- and inter-hemispheric networks. We found that patients with schizophrenia showed significantly decrease in both global and nodal efficiency of hemispheric networks relative to healthy controls. Specially, deficits in intra-hemispheric integration and inter-hemispheric communication were revealed in frontal and temporal regions for schizophrenia. We also found disrupted hemispheric asymmetries in brain regions associated with emotion, memory, and visual processes for schizophrenia. Moreover, abnormal hemispheric asymmetry of nodal efficiency was significantly correlated with the symptom of the patients. Our finding indicated that the hemispheric WM lateralization of intra- and inter-hemispheric connections could serve as a potential imaging biomarker for schizophrenia.

Updating and characterizing neuroanatomical markers in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis

Characterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess pathophysiological models of how the disorder develops is an important target for the clinical practice. We performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization. Results reveal a cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region found altered among c-HR, RDSZ and ChSZ. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ. These findings support the current neuroprogressive models of SZ and integrate this deterioration with the clinical evolution of the disease.

Evaluation of Effective Connectivity Between Brain Areas Activated During Simulated Driving Using Dynamic Causal Modeling

This study was examined the effective connectivity between brain areas activated during driving. Using a driving simulator, the subjects controlled a wheel with both of their hands as well as an accelerator and brake pedal with their right foot. Of the areas activated during driving, three areas from each hemisphere were analyzed for effective connectivity using dynamic causal modeling. In the right hemisphere, bidirectional connectivity was prominent between the inferior temporal gyrus, precuneus, and lingual gyrus, which provided driving input (driving input refers to the area of input among areas connected with effective connectivity). In the left hemisphere, the superior temporal gyrus provided driving input, and bidirectional connectivity was prominent between the superior temporal gyrus, inferior parietal lobule, and inferior frontal gyrus. The visual attention pathway was activated in the right hemisphere, whereas the inhibitory control movement and task-switching pathways, which are responsible for synesthesia, were activated in the left hemisphere. In both of the hemispheres, the visual attention, inhibitory control movement, and episodic memory retrieval pathways were prominent. The activation of these pathways indicates that driving requires multi-domain executive function in addition to vision. Moreover, pathway activation is influenced by the driving experience and familiarity of the driver. This study elucidated the overall effective connectivity between brain areas related to driving.

Deviant cortical sulcation related to schizophrenia and cognitive deficits in the second trimester

Objectives

Aberrant cortical development, inferred from cortical folding, is linked to the risk of schizophrenia. Cortical folds develop in a time-locked fashion during fetal growth. We leveraged this temporal specificity of sulcation to investigate the timing of the prenatal insult linked to schizophrenia and the cognitive impairment seen in this illness.

Methods

Anatomical MRI scans from 68 patients with schizophrenia and 72 controls were used to evaluate the sulcal depth of five major invariable primary sulci representing lobar development (calcarine sulcus, superior temporal sulcus, superior frontal sulcus, intraparietal sulcus and inferior frontal sulcus) with formation representing the distinct developmental periods.

Results

A repeated-measure ANOVA with five sulci and two hemispheres as the within-subject factors and gender, age and intracranial volume as covariates revealed a significant effect of diagnosis (F[1,134] = 14.8, p = 0.0002). Control subjects had deeper bilateral superior temporal, right inferior frontal and left calcarine sulci. A deeper superior frontal sulcus predicted better cognitive scores among patients.

Conclusion

Our results suggest that the gestational disruption underlying schizophrenia is likely to predate, if not coincide with the appearance of calcarine sulcus (early second trimester). Nevertheless, the burden of cognitive deficits may relate specifically to the aberrant superior frontal development apparent in late second trimester.

Diagnosing schizophrenia with network analysis and a machine learning method

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Dynamic Causal Modelling suggests impaired effective connectivity in patients with schizophrenia spectrum disorders during gesture-speech integration

Integrating visual and auditory information during gesture-speech integration (GSI) is important for successful social communication, which is often impaired in schizophrenia. Several studies suggested the posterior superior temporal sulcus (pSTS) to be a relevant multisensory integration site. However, intact STS activation patterns were often reported in patients. Thus, here we used Dynamic Causal Modelling (DCM) to analyze whether information processing in schizophrenia spectrum disorders (SSD) is impaired during GSI on network level. We investigated GSI in three different samples. First, we replicated a recently published connectivity model for GSI in a healthy subject group (n = 19). Second, we investigated differences between patients with SSD and a matched healthy control group (n = 17 each). Participants were presented videos of an actor performing intrinsically meaningful gestures accompanied by spoken sentences in German or Russian, or just telling a German sentence without gestures. Across all groups, fMRI analyses revealed similar activation patterns, and DCM analyses resulted in the same winning model for GSI. This finding directly replicates previous results. However, patients revealed significantly reduced connectivity in the verbal pathway (from left middle temporal gyrus (MTG) to left STS). The clinical significance of this connection is supported by its correlations with the severity of concretism and a subscale of negative symptoms (SANS). Our model confirms the importance of the pSTS as integration site during audio-visual integration. Patients showed generally intact connectivity during GSI, but revealed impaired information transfer via the verbal pathway. This might be the basis of interpersonal communication problems in patients with SSD.

Developmental Pathoconnectomics and Advanced Fetal MRI

Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.

Aberrant Executive Control and Auditory Networks in Recent-Onset Schizophrenia

PURPOSE

Despite a large number of resting-state functional MRI (rsfMRI) studies in schizophrenia, current evidence on the abnormalities of functional connectivity (FC) of resting-state networks shows high variability, and the findings on recent-onset schizophrenia are insufficient compared to those on chronic schizophrenia.

PATIENTS AND METHODS

We performed a rsfMRI in 46 patients with recent-onset schizophrenia and 22 healthy controls. Group independent component brainmap and dual regression were performed for voxel-wise comparisons between the groups. Correlation of the symptom severity, cognitive function, duration of illness, and a total antipsychotics dose with FC was evaluated with Spearman's rho correlation.

RESULTS

The patient group had areas with a significantly decreased FC compared to that of the control group in which it existed in the left supplementary motor cortex and supramarginal gyrus (the executive control network) and the right postcentral gyrus (the auditory network). The patient group had a significant correlation of the total antipsychotics dose with the FC of the cluster in the left supplementary motor cortex in the executive control network.

CONCLUSION

Patients with recent-onset schizophrenia have decreased FC of the executive control and auditory networks compared to healthy controls.

Simultaneous fMRI-EEG-DTI recording of MMN in patients with schizophrenia

Functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and diffusion tensor imaging (DTI) recording have complementary spatiotemporal resolution limitations but can be powerful methods when used together to enable both functional and anatomical modeling, with each neuroimaging procedure used to maximum advantage. We recorded EEGs during event-related fMRI followed by DTI in 15 healthy volunteers and 12 patients with schizophrenia using an omission mismatch negativity (MMN) paradigm. Blood oxygenation level-dependent (BOLD) signal changes were calculated in a region of interest (ROI) analysis, and fractional anisotropy (FA) in the white matter fibers related to each area was compared between groups using tract-specific analysis. Patients with schizophrenia had reduced BOLD activity in the left middle temporal gyrus, and BOLD activity in the right insula and right parahippocampal gyrus significantly correlated with positive symptoms on the Positive and Negative Syndrome Scale (PANSS) and hostility subscores. BOLD activation of Heschl’s gyri also correlated with the limbic system, including the insula. FA values in the left anterior cingulate cortex (ACC) significantly correlated with changes in the BOLD signal in the right superior temporal gyrus (STG), and FA values in the right ACC significantly correlated with PANSS scores. This is the first study to examine MMN using simultaneous fMRI, EEG, and DTI recording in patients with schizophrenia to investigate the potential implications of abnormalities in the ACC and limbic system, including the insula and parahippocampal gyrus, as well as the STG. Structural changes in the ACC during schizophrenia may represent part of the neural basis for the observed MMN deficits. The deficits seen in the feedback/feedforward connections between the prefrontal cortex and STG modulated by the ACC and insula may specifically contribute to impaired MMN generation and clinical manifestations.

Alteration of Semantic Networks during Swear Words Processing in Schizophrenia

Objective

Positive symptoms, such as delusion and hallucination, commonly include negative emotional content in schizophrenia. We investigated the neural basis implicated during the processing of strong negative emotional words in patients with schizophrenia.

Methods

In our study, 35 patients with schizophrenia and 19 healthy controls were recruited, and the participants were asked to passively view the words that contained swearing and neutral content during functional magnetic resonance imaging.

Results

Patients with schizophrenia, compared to healthy controls, showed hypoactivation to the swear and neutral words stimuli in the left inferior frontal gyrus, left middle frontal gyrus, and left angular/supramarginal gyrus. More specifically, patients with remitted schizophrenia were found to have greater activation to the stimuli in the left middle/inferior frontal gyrus than patients with active schizophrenia. Furthermore, in the analysis of regions of interests, the left inferior and middle frontal gyrus activity was related to the severity of positive symptoms, including delusion and suspiciousness.

Conclusion

Our results suggest that patients with schizophrenia have difficulty in semantic processing and inhibitory control of swear words, and these abnormalities may be connected with the severity of positive symptoms.

Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging

Structural brain abnormalities in schizophrenia have been well characterized with the application of univariate methods to magnetic resonance imaging (MRI) data. However, these traditional techniques lack sensitivity and predictive value at the individual level. Machine-learning approaches have emerged as potential diagnostic and prognostic tools. We used an anatomically and spatially regularized support vector machine (SVM) framework to categorize schizophrenia and healthy individuals based on whole-brain gray matter densities estimated using voxel-based morphometry from structural MRI scans. The regularized SVM model yielded recognition accuracy of 86.6% in the training set of 127 individuals and validation accuracy of 83.5% in an independent set of 85 individuals. A sequential region-of-interest (ROI) selection step was adopted for feature selection, improving recognition accuracy to 92.0% in the training set and 89.4% in the validation set. The combined model achieved 96.6% sensitivity and 74.1% specificity. Seven ROIs were identified as the optimal discriminatory subset: the occipital fusiform gyrus, middle frontal gyrus, pars opercularis of the inferior frontal gyrus, anterior superior temporal gyrus, superior frontal gyrus, left thalamus and left lateral ventricle. These findings demonstrate the utility of spatial and anatomical priors in SVM for neuroimaging analyses in conjunction with sequential ROI selection in the recognition of schizophrenia.

Callosal and subcortical white matter alterations in schizophrenia: A diffusion tensor imaging study at multiple levels

Diffusion tensor imaging and its distinct capability to detect micro-structural changes in vivo allows the exploration of white matter (WM) abnormalities in patients who have been diagnosed with schizophrenia; however, the results regarding the anatomical positions and degree of abnormalities are inconsistent. In order to obtain more robust and stable findings, we conducted a multi-level analysis to investigate WM disruption in a relatively large sample size (142 schizophrenia patients and 163 healthy subjects). Specifically, we evaluated the univariate fractional anisotropy (FA) in voxel level; the bivariate pairwise structural connectivity between regions using deterministic tractography as the network node defined by the Human Brainnetome Atlas; and the multivariate network topological properties, including the network hub, efficiency, small-worldness, and strength. Our data demonstrated callosal and subcortical WM alterations in patients with schizophrenia. These disruptions were evident in both voxel and connectivity levels and further supported by associations between FA values and illness duration. Based on the findings regarding topological properties, the structural network showed weaker global integration in patients with schizophrenia than in healthy subjects, while brain network hubs showed decreased functionality. We replicated these findings using an automated anatomical labeling atlas to define the network node. Our study indicates that callosal and subcortical WM disruptions are biomarkers for chronic schizophrenia.

Classification of multi-site MR images in the presence of heterogeneity using multi-task learning

With the advent of Big Data Imaging Analytics applied to neuroimaging, datasets from multiple sites need to be pooled into larger samples. However, heterogeneity across different scanners, protocols and populations, renders the task of finding underlying disease signatures challenging. The current work investigates the value of multi-task learning in finding disease signatures that generalize across studies and populations. Herein, we present a multi-task learning type of formulation, in which different tasks are from different studies and populations being pooled together. We test this approach in an MRI study of the neuroanatomy of schizophrenia (SCZ) by pooling data from 3 different sites and populations: Philadelphia, Sao Paulo and Tianjin (50 controls and 50 patients from each site), which posed integration challenges due to variability in disease chronicity, treatment exposure, and data collection. Some existing methods are also tested for comparison purposes. Experiments show that classification accuracy of multi-site data outperformed that of single-site data and pooled data using multi-task feature learning, and also outperformed other comparison methods. Several anatomical regions were identified to be common discriminant features across sites. These included prefrontal, superior temporal, insular, anterior cingulate cortex, temporo-limbic and striatal regions consistently implicated in the pathophysiology of schizophrenia, as well as the cerebellum, precuneus, and fusiform, middle temporal, inferior parietal, postcentral, angular, lingual and middle occipital gyri. These results indicate that the proposed multi-task learning method is robust in finding consistent and reliable structural brain abnormalities associated with SCZ across different sites, in the presence of multiple sources of heterogeneity.

S-Ketamine-Induced NMDA Receptor Blockade during Natural Speech Production and Its Implications for Formal Thought Disorder in Schizophrenia: A Pharmaco-fMRI Study

Structural and functional changes in the lateral temporal language areas have been related to formal thought disorder (FTD) in schizophrenia. Continuous, natural speech production activates the right lateral temporal lobe in schizophrenia, as opposed to the left in healthy subjects. Positive and negative FTD can be elicited in healthy subjects by glutamatergic NMDA blockade with ketamine. It is unclear whether the glutamate system is related to the reversed hemispheric lateralization during speaking in patients. In a double-blind, crossover, placebo-controlled study, 15 healthy, male, right-handed volunteers overtly described 7 pictures for 3 min each while BOLD signal changes were acquired with fMRI. As a measure of linguistic demand, the number of words within 20 s epochs was correlated with BOLD responses. Participants developed S-ketamine-induced psychotic symptoms, particularly positive FTD. Ketamine vs placebo was associated with enhanced neural responses in the right middle and inferior temporal gyri. Similar to a previous fMRI study in schizophrenia patients vs healthy controls applying the same design, S-ketamine reversed functional lateralization during speech production in healthy subjects. Results demonstrate an association between glutamatergic imbalance, dysactivations in lateral temporal brain areas, and FTD symptom formation.

Decreased white matter FA values in the left inferior frontal gyrus is a possible intermediate phenotype of schizophrenia: evidences from a novel group strategy

Intermediate phenotype could be used to investigate genetic susceptibility. However, genetic and environmental heterogeneity may interfere with identification of intermediate phenotypes. In this study, we minimized these interferences by using a novel group strategy. A total of 22 drug-naive and first-episode schizophrenia (FES) patients, along with 22 of their kin healthy siblings (HS), 22 non-kin healthy siblings (nHS) of other schizophrenia patients and 22 healthy controls (HC), were recruited. Brain imaging was acquired from the participants. Voxel-based analysis was used to investigate differences in white matter integrity derived from diffusion tensor imaging among the four groups. Two cognitive tests related to our findings were selected to confirm the related phenotypic changes. All of the FES, HS, and nHS groups showed decreased fractional anisotropy (FA) values in the left inferior frontal gyrus (IFG) compared with the HC group (p < 0.05, FDR corrected). The scores of Hopkins Verbal learning Test-Revised and Animal Naming in FES patients were significantly lower than in participants belonging to the other three groups (p < 0.05). Significant correlation between Animal Naming scores and FA values in the left IFG was found in FES patients (r = 0.53, p = 0.01). Moreover, FES patients also showed decreased FA values in the left medial frontal gyrus, left inferior temporal gyrus, left parahippocampal gyrus, left posterior cingulate, and right middle temporal gyrus compared with HC (p < 0.05, FDR corrected). Decreased FA values in the left IFG is a possible intermediate phenotype of schizophrenia, and this finding supports the hypothesis that disrupted connectivity of white matter may be the key substrate of schizophrenia.

Considering the role of adolescent sex steroids in schizophrenia

Schizophrenia is a disabling illness that is typically first diagnosed during late adolescence to early adulthood. It has an unremitting course and is often treatment-resistant. Many clinical aspects of the illness suggest that sex steroid-nervous system interactions may contribute to the onset, course of symptoms and the cognitive impairment displayed by men and women with schizophrenia. Here, we discuss the actions of oestrogen and testosterone on the brain during adolescent development and in schizophrenia from the perspective of experimental studies in animals, human post-mortem studies, magnetic resonance imaging studies in living humans and clinical trials of sex steroid-based treatments. We present evidence of potential beneficial, as well as detrimental, effects of both testosterone and oestrogen. We provide a rationale for the necessity to further elucidate sex steroid mechanisms of action at different ages, sexes and brain regions to more fully understand the role of testosterone and oestrogen in the pathophysiology of schizophrenia. The weight of the evidence suggests that sex steroid hormones influence mammalian brain function, including both cognition and emotion, and that pharmaceutical agents aimed at sex steroid receptors appear to provide a novel treatment avenue to reduce symptoms and improve cognition in men and women with schizophrenia.

Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity

Background: Patients with treatment-resistant schizophrenia (TRS) and non-treatment-resistant schizophrenia (NTRS) respond to antipsychotic drugs differently. Previous studies demonstrated that patients with TRS or NTRS exhibited abnormal neural activity in different brain regions. Accordingly, in the present study, we tested the hypothesis that a regional homogeneity (ReHo) approach could be used to distinguish between patients with TRS and NTRS. Methods: A total of 17 patients with TRS, 17 patients with NTRS, and 29 healthy controls (HCs) matched in sex, age, and education levels were recruited to undergo resting-state functional magnetic resonance imaging (RS-fMRI). ReHo was used to process the data. ANCOVA followed by post-hoc t-tests, receiver operating characteristic curves (ROC), and correlation analyses were applied for the data analysis. Results: ANCOVA analysis revealed widespread differences in ReHo among the three groups in the occipital, frontal, temporal, and parietal lobes. ROC results indicated that the optimal sensitivity and specificity of the ReHo values in the left postcentral gyrus, left inferior frontal gyrus/triangular part, and right fusiform could differentiate TRS from NTRS, TRS from HCs, and NTRS from HCs were 94.12 and 82.35%, 100 and 86.21%, and 82.35 and 93.10%, respectively. No correlation was found between abnormal ReHo and clinical symptoms in patients with TRS or NTRS. Conclusions: TRS and NTRS shared most brain regions with abnormal neural activity. Abnormal ReHo values in certain brain regions might be applied to differentiate TRS from NTRS, TRS from HC, and NTRS from HC with high sensitivity and specificity.

White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies

Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.

Connectivity-based parcellation of the anterior limb of the internal capsule

The anterior limb of the internal capsule (ALIC) is an important locus of frontal-subcortical fiber tracts involved in cognitive and limbic feedback loops. However, the structural organization of its component fiber tracts remains unclear. Therefore, although the ALIC is a promising target for various neurosurgical procedures for psychiatric disorders, more precise understanding of its organization is required to optimize target localization. Using diffusion tensor imaging (DTI) collected on healthy subjects by the Human Connectome Project (HCP), we generated parcellations of the ALIC by dividing it according to structural connectivity to various frontal regions. We then compared individuals' parcellations to evaluate the ALIC's structural consistency. All 40 included subjects demonstrated a posterior-superior to anterior-inferior axis of tract organization in the ALIC. Nonetheless, subdivisions of the ALIC were found to vary substantially, as voxels in the average parcellation were accurately assigned for a mean of only 66.2% of subjects. There were, however, some loci of consistency, most notably in the region maximally connected to orbitofrontal cortex. These findings clarify the highly variable organization of the ALIC and may represent a tool for patient-specific targeting of neuromodulation. Hum Brain Mapp 38:6107-6117, 2017. © 2017 Wiley Periodicals, Inc.

The Arcuate Fasciculus Network and Verbal Deficits in Psychosis

Background

Verbal learning (VL) and fluency (VF) are prominent cognitive deficits in psychosis, of which the precise neuroanatomical contributions are not fully understood. We investigated the arcuate fasciculus (AF) and its associated cortical regions to identify structural abnormalities contributing to these verbal impairments in early stages of psychotic illness.

Methods

Twenty-six individuals with recent-onset psychosis and 27 healthy controls underwent cognitive testing (MATRICS Consensus Cognitive Battery) and structural/diffusion-weighted MRI. Bilaterally, AF anisotropy and cortical thickness, surface area and volume of seven cortical regions were investigated in relation to VL and VF performance in both groups.

Results

Reduced right superior temporal gyrus surface area and volume related to better VF in controls. In psychosis, greater right pars opercularis volume and reduced left lateralization of this region related to better VL, while greater right long AF fractional anisotropy and right pars orbitalis volume related to better VF, these findings not present in controls. Psychosis had reduced right pars orbitalis thickness compared to controls.

Conclusion

Anatomical substrates for normal processing of VL and VF appear altered in recent-onset psychosis. A possible aberrant role of the right hemisphere arcuate fasciculus and fronto-temporal cortical regions in psychosis may contribute to deficits in VL and VF.

Shared abnormality of white matter integrity in schizophrenia and bipolar disorder: A comparative voxel-based meta-analysis

Patients with schizophrenia and bipolar disorder (BD) shared a significant overlap in genetic susceptibility, pharmacological treatment responses, neuropsychological deficits, and epidemiological features. However, it remains unknown whether these clinical overlaps are mediated by shared or disorder-specific abnormalities of white matter integrity. In this voxel-based meta-analytic comparison of whole-brain white matter integrity, we aimed to identify the shared or disorder-specific structural abnormalities between schizophrenia and BD. A comprehensive literature search was conducted up to February 2016 to identify studies that compared between patients and healthy controls (HC) by using whole-brain diffusion approach (schizophrenia: 24 datasets with 754 patients vs. 775 HC; BD: 23 datasets with 705 patients vs. 679 HC). Voxel-wise meta-analyses were conducted and restricted to unified template using seed-based d-Mapping. Abnormal white matter integrity was calculated within each condition and a direct comparison of effect size was performed of alterations between two conditions. Two regions with significant reductions of fractional anisotropy (FA) characterized abnormal water diffusion in both disorders: the genu of the corpus callosum (CC) and posterior cingulum fibers. There was no significant difference found between the two disorders. Our results highlighted shared impairments of FA at genu of the CC and left posterior cingulum fibers, which suggests that, phenotypic overlap between schizophrenia and BD could be related to common brain circuit dysfunction.

Comparison of large-scale human brain functional and anatomical networks in schizophrenia

Schizophrenia is a disease with disruptions in thought, emotion, and behavior. The dysconnectivity hypothesis suggests these disruptions are due to aberrant brain connectivity. Many studies have identified connectivity differences but few have been able to unify gray and white matter findings into one model. Here we develop an extension of the Network-Based Statistic (NBS) called NBSm (Multimodal Network-based statistic) to compare functional and anatomical networks in schizophrenia. Structural, resting functional, and diffusion magnetic resonance imaging data were collected from 29 chronic patients with schizophrenia and 29 healthy controls. Images were preprocessed, and average time courses were extracted for 90 regions of interest (ROI). Functional connectivity matrices were estimated by pairwise correlations between wavelet coefficients of ROI time series. Following diffusion tractography, anatomical connectivity matrices were estimated by white matter streamline counts between each pair of ROIs. Global and regional strength were calculated for each modality. NBSm was used to find significant overlap between functional and anatomical components that distinguished health from schizophrenia. Global strength was decreased in patients in both functional and anatomical networks. Regional strength was decreased in all regions in functional networks and only one region in anatomical networks. NBSm identified a distinguishing functional component consisting of 46 nodes with 113 links (p < 0.001), a distinguishing anatomical component with 47 nodes and 50 links (p = 0.002), and a distinguishing intermodal component with 26 nodes (p < 0.001). NBSm is a powerful technique for understanding network-based group differences present in both anatomical and functional data. In light of the dysconnectivity hypothesis, these results provide compelling evidence for the presence of significant overlapping anatomical and functional disruption in people with schizophrenia.

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A novel method for the unified analysis of functional and anatomical networks in schizophrenia is proposed.

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The methodology extends existing networkbased analyses to test brain network differences across imaging modalities.

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A fundamental disrupted network was found in those with schizophrenia when compared to healthy, agematched controls.

Brain substrates underlying auditory speech priming in healthy listeners and listeners with schizophrenia

BACKGROUND

Under 'cocktail party' listening conditions, healthy listeners and listeners with schizophrenia can use temporally pre-presented auditory speech-priming (ASP) stimuli to improve target-speech recognition, even though listeners with schizophrenia are more vulnerable to informational speech masking.

METHOD

Using functional magnetic resonance imaging, this study searched for both brain substrates underlying the unmasking effect of ASP in 16 healthy controls and 22 patients with schizophrenia, and brain substrates underlying schizophrenia-related speech-recognition deficits under speech-masking conditions.

RESULTS

In both controls and patients, introducing the ASP condition (against the auditory non-speech-priming condition) not only activated the left superior temporal gyrus (STG) and left posterior middle temporal gyrus (pMTG), but also enhanced functional connectivity of the left STG/pMTG with the left caudate. It also enhanced functional connectivity of the left STG/pMTG with the left pars triangularis of the inferior frontal gyrus (TriIFG) in controls and that with the left Rolandic operculum in patients. The strength of functional connectivity between the left STG and left TriIFG was correlated with target-speech recognition under the speech-masking condition in both controls and patients, but reduced in patients.

CONCLUSIONS

The left STG/pMTG and their ASP-related functional connectivity with both the left caudate and some frontal regions (the left TriIFG in healthy listeners and the left Rolandic operculum in listeners with schizophrenia) are involved in the unmasking effect of ASP, possibly through facilitating the following processes: masker-signal inhibition, target-speech encoding, and speech production. The schizophrenia-related reduction of functional connectivity between the left STG and left TriIFG augments the vulnerability of speech recognition to speech masking.

Brain connectivity and auditory hallucinations: In search of novel noninvasive brain stimulation therapeutic approaches for schizophrenia

Auditory verbal hallucinations (AVH) are among the most characteristic symptoms of schizophrenia and have been linked to likely disturbances of structural and functional connectivity within frontal, temporal, parietal and subcortical networks involved in language and auditory functions. Resting-state functional magnetic resonance imaging (fMRI) has shown that alterations in the functional connectivity activity of the default-mode network (DMN) may also subtend hallucinations. Noninvasive neurostimulation techniques such as repetitive transcranial magnetic stimulation (rTMS) have the ability to modulate activity of targeted cortical sites and their associated networks, showing a high potential for modulating altered connectivity subtending schizophrenia. Notwithstanding, the clinical benefit of these approaches remains weak and variable. Further studies in the field should foster a better understanding concerning the status of networks subtending AVH and the neural impact of rTMS in relation with symptom improvement. Additionally, the identification and characterization of clinical biomarkers able to predict response to treatment would be a critical asset allowing better care for patients with schizophrenia.

Aberrant structural and functional connectivity in the salience network and central executive network circuit in schizophrenia

Consistent structural and functional abnormities have been detected in the salience network (SN) and the central-executive network (CEN) in schizophrenia. SN, known for its critical role in switching CEN and default-mode network (DMN) during cognitively demanding tasks, is proved to show aberrant regulation on the interaction between DMN and CEN in schizophrenia. However, it has not been elucidated whether there is a direct alteration of structural and functional connectivity between SN and CEN. 22 schizophrenia patients and 21 healthy controls were recruited for functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) in present study. The results show that schizophrenia patients had lower fractional anisotropy (FA) in right inferior long fasciculus (ILF), left inferior fronto-occipital fasciculus (IFOF) and callosal body than healthy controls. Significantly reduced functional connectivity was also found between right fronto-insular cortex (rFIC) and right posterior parietal cortex (rPPC). FA in right ILF was positively correlated with the functional connectivity of rFIC-rPPC. Therefore, we proposed a disruption of structural and functional connectivity and a positive anatomo-functional relationship in SN-CEN circuit, which might account for a core feature of schizophrenia.