Reduced intrinsic visual cortical connectivity is associated with impaired perceptual closure in schizophrenia

High-order network degree revealed shared and distinct features among adult schizophrenia, bipolar disorder and ADHD

Schizophrenia (SCHZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD) share clinical symptoms and risk genes, but the shared and distinct neural dynamic mechanisms at adults remain inadequately understood. Degree is a fundamental and important graph measure in network neuroscience, and we here used eigenmodes to extend the degree to hierarchical levels and compared the resting-state brain networks of three disorders and healthy controls (HC) at adults (age: 21-50 years old). First, compared to HC, SCHZ and BD patients exhibited substantially overlapped abnormalities in brain networks, wherein BD patients displayed more significant alterations. In contrast, ADHD patients exhibited few alterations. Second, compared to the graph theory measure, hierarchical degree better predicted the clinical symptoms of three disorders, and distinguished them from HC. Furthermore, three disorders shared associations of brain network abnormalities with dopamine receptors/transporters. Finally, the alterations in SCHZ and BD patients were associated with cellular localization and transport, as well as abnormal social behavior and communication, while ADHD patients were associated with energy production and transport. These findings provided a deep understanding of the shared and distinct neuropathology of three disorders and facilitated a more precise differentiation for them.

Polygenic Resilience Scores are Associated With Lower Penetrance of Schizophrenia Risk Genes, Protection Against Psychiatric and Medical Disorders, and Enhanced Mental Well-Being and Cognition

BACKGROUND AND HYPOTHESIS

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. We identified the first genomic resilience profile for SCZ, completely independent from known risk loci for SCZ, though it remains unclear whether resilience loci foster protection against adverse states associated with SCZ involving clinical, cognitive, and brain-structural phenotypes.

STUDY DESIGN

We analyzed genomic and phenotypic data from 459 784 participants from the UK Biobank, using regression models to estimate interaction effects of resilience and SCZ risk scores on phenotypes spanning multiple scales.

STUDY RESULTS

We found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and medical disorders (such as type 2 diabetes, cardiovascular, and digestive and metabolic disorders). Resilience loci also moderated the impact of SCZ loci, associated with protection against self-harm behavior and greater fluid intelligence scores. The main effects of resilience are also observed in the absence of a moderating effect in some instances, such as associations with larger brain structures.

CONCLUSIONS

Overall, this study highlights a wide range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Resilience loci may protect against serious psychiatric and medical outcomes, comorbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.

Impaired contour object perception in psychosis

BACKGROUND

Contour integration, the process of joining spatially separated elements into a single unified line, has consistently been found to be impaired in schizophrenia. Recent work suggests that this deficit could be associated with psychotic symptomatology, rather than a specific diagnosis such as schizophrenia.

METHODS

Examining a transdiagnostic sample of participants with psychotic psychopathology, we obtained quantitative indices of contour perception in a psychophysical behavioral task. We also measured responses during an analogous task using ultra-high field (7T) functional MRI.

RESULTS

We found impaired contour discrimination performance among people with psychotic psychopathology (PwPP, n = 63) compared to healthy controls (n = 34) and biological relatives of PwPP (n = 44). Participants with schizophrenia (n = 31) showed impaired task performance compared to participants with bipolar disorder (n = 18). FMRI showed higher responses in the lateral occipital cortex of PwPP compared to controls. Using task-based functional connectivity analyses, we observed abnormal connectivity between visual brain areas during contour perception among PwPP. These connectivity differences only emerged when participants had to distinguish the contour object from background distractors, suggesting that a failure to suppress noise elements relative to contour elements may underlie impaired contour processing in PwPP.

CONCLUSIONS

Our results are consistent with impaired contour integration in psychotic psychopathology, and especially schizophrenia, that is related to cognitive dysfunction, and may be linked to impaired functional connectivity across visual regions.

Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data

BACKGROUND

Real-valued mutual information (MI) has been used in spatial functional network connectivity (FNC) to measure high-order and nonlinear dependence between spatial maps extracted from magnitude-only functional magnetic resonance imaging (fMRI). However, real-valued MI cannot fully capture the group differences in spatial FNC from complex-valued fMRI data with magnitude and phase dependence.

METHODS

We propose a complete complex-valued MI method according to the chain rule of MI. We fully exploit the dependence among magnitudes and phases of two complex-valued signals using second and fourth-order joint entropies, and propose to use a Gaussian copula transformation with a lower bound property to avoid inaccurate estimation of joint probability density function when computing the joint entropies.

RESULTS

The proposed method achieves more accurate MI estimates than the two histogram-based (normal and symbolic approaches) and kernel density estimation methods for simulated signals, and enhances group differences in spatial functional network connectivity for experimental complex-valued fMRI data.

COMPARISON WITH EXISTING METHODS

Compared with the simplified complex-valued MI and real-valued MI, the proposed method yields higher MI estimation accuracy, leading to 17.4 % and 145.5 % wider MI ranges, and more significant connectivity differences between healthy controls and schizophrenia patients. A unique connection between executive control network (EC) and right frontal parietal areas, and three additional connections mainly related to EC are detected than the simplified complex-valued MI.

CONCLUSIONS

With capability in quantifying MI fully and accurately, the proposed complex-valued MI is promising in providing qualified FNC biomarkers for identifying mental disorders such as schizophrenia.

Implications of altered pyramidal cell morphology on clinical symptoms of neurodevelopmental disorders

The prevalence of pyramidal cells (PCs) in the mammalian cerebral cortex underscore their value as they play a crucial role in various brain functions, ranging from cognition, sensory processing, to motor output. PC morphology significantly influences brain connectivity and plays a critical role in maintaining normal brain function. Pathological alterations to PC morphology are thought to contribute to the aetiology of neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. This review explores the relationship between abnormalities in PC morphology in key cortical areas and the clinical manifestations in schizophrenia and ASD. We focus largely on human postmortem studies and provide evidence that dendritic segment length, complexity and spine density are differentially affected in these disorders. These morphological alterations can lead to disruptions in cortical connectivity, potentially contributing to the cognitive and behavioural deficits observed in these disorders. Furthermore, we highlight the importance of investigating the functional and structural characteristics of PCs in these disorders to illuminate the underlying pathogenesis and stimulate further research in this area.

Impaired contour object perception in psychosis

Contour integration, the process of joining spatially separated elements into a single unified line, has consistently been found to be impaired in schizophrenia. Recent work suggests that this deficit could be associated with psychotic symptomatology, rather than a specific diagnosis such as schizophrenia. Examining a transdiagnostic sample of participants with psychotic psychopathology, we obtained quantitative indices of contour perception in a psychophysical behavioral task. We found impaired contour discrimination performance among people with psychotic psychopathology (PwPP, n = 62) compared to healthy controls (n = 34) and biological relatives of PwPP (n = 44). Participants with schizophrenia (n = 31) showed impaired task performance compared to participants with bipolar disorder (n = 18). We also measured responses during an analogous task using ultra-high field (7T) functional MRI and found higher responses in the lateral occipital cortex of PwPP compared to controls. Using task-based functional connectivity analyses, we observed abnormal connectivity between visual brain areas during contour perception among PwPP. These connectivity differences only emerged when participants had to distinguish the contour object from background distractors, suggesting that a failure to suppress noise elements relative to contour elements may underlie impaired contour processing in PwPP. Our results are consistent with impaired contour integration in psychotic psychopathology, and especially schizophrenia, that is related to cognitive dysfunction, and may be linked to impaired functional connectivity across visual regions.

Visual Neurophysiological Biomarkers for Patient Stratification and Treatment Development Across Neuropsychiatric Disorders

The human visual system begins in the retina and projects to cortex through both the thalamocortical and retinotectal visual pathways. The thalamocortical system is divided into separate magnocellular and parvocellular divisions, which engage separate layers of the lateral geniculate nucleus (LGN) and project preferentially to the dorsal and ventral visual streams, respectively. The retinotectal system, in contrast, projects to the superior colliculus, pulvinar nucleus of the thalamus and amygdala. The pulvinar nucleus also plays a critical role in the integration of information processing across early visual regions.The functions of the visual system can be assessed using convergent EEG- and functional brain imaging approaches, increasingly supplemented by simultaneously collected eye-tracking information. These approaches may be used for tracing the flow of information from retina through early visual regions, as well as the contribution of these regions to higher-order cognitive processing. A pathway of increasing interest in relationship to neuropsychiatric disorders is the primate-specific "third visual pathway" that relies extensively on motion-related input and contributes preferentially to social information processing. Thus, disturbances in the brain's responsiveness to motion stimuli may be especially useful as biomarkers for early visual dysfunction related to impaired social cognition.Visual event-related potentials (ERPs) can be collected with high-fidelity and have proven effective for the study of neuropsychiatric disorders such as schizophrenia and Alzheimer's disease, in which alterations in visual processing may occur early in the disorder, andautism-spectrum disorder (ASD), in which abnormal persistence of early childhood patterns may persist into adulthood, leading to impaired functioning of visual social pathways. The utility of visual ERPs as biomarkers for larger clinical studies is limited at present by the need for standardization of visual stimuli across laboratories, which requires specialized protocols and equipment. The development of optimized stimulation protocols as well as newer headset-based systems may increase the clinical utility of present stimulation approaches.

The hidden link: Investigating functional connectivity of rarely explored sub-regions of thalamus and superior temporal gyrus in Schizophrenia

Functional magnetic resonance imaging (fMRI) stands as a pivotal tool in advancing our comprehension of Schizophrenia, offering insights into functional segregations and integrations. Previous investigations employing either task-based or resting-state fMRI primarily focused on large main regions of interest (ROI), revealing the thalamus and superior temporal gyrus (STG) as prominently affected areas. Recent studies, however, unveiled the cytoarchitectural intricacies within these regions, prompting a more nuanced exploration. In this study, resting-state fMRI was conducted on 72 schizophrenic patients and 74 healthy controls to discern whether distinct thalamic nuclei and STG sub-regions exhibit varied functional integrational connectivity to main networks and to identify the most affected sub-regions in Schizophrenia. Employing seed-based analysis, six sub-ROIs - four in the thalamus and two in the STG - were selected. Our findings unveiled heightened positive functional connectivity in Schizophrenic patients, particularly toward the anterior STG (aSTG) and posterior STG (pSTG). Notably, positive connectivity emerged between the medial division of mediodorsal thalamic nuclei (MDm) and the visual network, while increased functional connectivity linked the ventral lateral nucleus of the thalamus with aSTG. This accentuated functional connectivity potentially influences these sub-regions, contributing to dysfunctions and manifesting symptoms such as language and learning difficulties alongside hallucinations. This study underscores the importance of delineating sub-regional dynamics to enhance our understanding of the nuanced neural alterations in Schizophrenia, paving the way for more targeted interventions and therapeutic approaches.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study

Background

Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years.

Methods

We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model.

Results

Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration.

Conclusions

These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

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

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

General psychopathology factor (p-factor) prediction using resting-state functional connectivity and a scanner-generalization neural network

The general psychopathology factor (p-factor) represents shared variance across mental disorders based on psychopathologic symptoms. The Adolescent Brain Cognitive Development (ABCD) Study offers an unprecedented opportunity to investigate functional networks (FNs) from functional magnetic resonance imaging (fMRI) associated with the psychopathology of an adolescent cohort (n > 10,000). However, the heterogeneities associated with the use of multiple sites and multiple scanners in the ABCD Study need to be overcome to improve the prediction of the p-factor using fMRI. We proposed a scanner-generalization neural network (SGNN) to predict the individual p-factor by systematically reducing the scanner effect for resting-state functional connectivity (RSFC). We included 6905 adolescents from 18 sites whose fMRI data were collected using either Siemens or GE scanners. The p-factor was estimated based on the Child Behavior Checklist (CBCL) scores available in the ABCD study using exploratory factor analysis. We evaluated the Pearson's correlation coefficients (CCs) for p-factor prediction via leave-one/two-site-out cross-validation (LOSOCV/LTSOCV) and identified important FNs from the weight features (WFs) of the SGNN. The CCs were higher for the SGNN than for alternative models when using both LOSOCV (0.1631 ± 0.0673 for the SGNN vs. 0.1497 ± 0.0710 for kernel ridge regression [KRR]; p < 0.05 from a two-tailed paired t-test) and LTSOCV (0.1469 ± 0.0381 for the SGNN vs. 0.1394 ± 0.0359 for KRR; p = 0.01). It was found that (a) the default-mode and dorsal attention FNs were important for p-factor prediction, and (b) the intra-visual FN was important for scanner generalization. We demonstrated the efficacy of our novel SGNN model for p-factor prediction while simultaneously eliminating scanner-related confounding effects for RSFC.

Magnocellular and parvocellular contributions to brain network dysfunction during learning and memory: Implications for schizophrenia

Memory deficits are core features of schizophrenia, and a central aim in biological psychiatry is to identify the etiology of these deficits. Scrutiny is naturally focused on the dorsolateral prefrontal cortex and the hippocampal cortices, given these structures' roles in memory and learning. The fronto-hippocampal framework is valuable but restrictive. Network-based underpinnings of learning and memory are substantially diverse and include interactions between hetero-modal and early sensory networks. Thus, a loss of fidelity in sensory information may impact memorial and cognitive processing in higher-order brain sub-networks, becoming a sensory source for learning and memory deficits. In this overview, we suggest that impairments in magno- and parvo-cellular visual pathways result in degraded inputs to core learning and memory networks. The ascending cascade of aberrant neural events significantly contributes to learning and memory deficits in schizophrenia. We outline the network bases of these effects, and suggest that any network perspectives of dysfunction in schizophrenia must assess the impact of impaired perceptual contributions. Finally, we speculate on how this framework enriches the space of biomarkers and expands intervention strategies to ameliorate this prototypical disconnection syndrome.

Abnormalities in visual cognition and associated impaired interactions between visual and attentional networks in schizophrenia and brief psychotic disorder

The extent and nature of cognitive impairment in brief psychotic disorder remains unclear, being rarely studied unlike schizophrenia. The present study hence sought to directly compare the visual cognitive dysfunction and its associated brain networks in brief psychotic disorder and schizophrenia. Data from picture completion (a complex visual task) and whole-brain functional connectome from resting-state fMRI were acquired from a sample of clinically stable patients with an established psychotic disorder (twenty with brief psychotic disorder, twenty with schizophrenia) and twenty-nine healthy controls. Group differences and the inter-relationships in task performances and brain networks were tested. Picture completion task deficits were found in brief psychotic disorder compared with healthy controls, though the deficits were less than schizophrenia. Task performance also correlated with severity of psychotic symptoms in patients. The task performance was inversely correlated with the functional connectivity between peripheral visual and attentional networks (dorsal attention and salience ventral attention), with increased functional connectivity in brief psychotic disorder compared with healthy controls and in schizophrenia compared with brief psychotic disorder. Present findings showed pronounced visual cognitive impairments in brief psychotic disorder that were worse in schizophrenia, underpinned by abnormal interactions between higher-order attentional and lower-order visual processing networks.

Reorganization of the functional connectome from rest to a visual perception task in schizophrenia and bipolar disorder

Functional connectome organization is altered in schizophrenia (SZ) and bipolar disorder (BD). However, it remains unclear whether network reorganization during a task relative to rest is also altered in these disorders. This study examined connectome organization in patients with SZ (N = 43) and BD (N = 42) versus healthy controls (HC; N = 39) using fMRI data during a visual object-perception task and at rest. Graph analyses were conducted for the whole-brain network using indices selected a priori: three reflecting network segregation (clustering coefficient, local efficiency, modularity), two reflecting integration (characteristic path length, global efficiency). Group differences were limited to network segregation and were more evident in SZ (clustering coefficient, modularity) than in BD (clustering coefficient) compared to HC. State differences were found across groups for segregation (local efficiency) and integration (characteristic path length). There was no group-by-state interaction for any graph index. In summary, aberrant network organization compared to HC was confirmed, and was more evident in SZ than in BD. Yet, reorganization was largely intact in both disorders. These findings help to constrain models of dysconnection in SZ and BD, suggesting that the extent of functional dysconnectivity in these disorders tends to persist across changes in mental state.

Nonlinear functional network connectivity in resting functional magnetic resonance imaging data

In this work, we focus on explicitly nonlinear relationships in functional networks. We introduce a technique using normalized mutual information (NMI) that calculates the nonlinear relationship between different brain regions. We demonstrate our proposed approach using simulated data and then apply it to a dataset previously studied by Damaraju et al. This resting-state fMRI data included 151 schizophrenia patients and 163 age- and gender-matched healthy controls. We first decomposed these data using group independent component analysis (ICA) and yielded 47 functionally relevant intrinsic connectivity networks. Our analysis showed a modularized nonlinear relationship among brain functional networks that was particularly noticeable in the sensory and visual cortex. Interestingly, the modularity appears both meaningful and distinct from that revealed by the linear approach. Group analysis identified significant differences in explicitly nonlinear functional network connectivity (FNC) between schizophrenia patients and healthy controls, particularly in the visual cortex, with controls showing more nonlinearity (i.e., higher normalized mutual information between time courses with linear relationships removed) in most cases. Certain domains, including subcortical and auditory, showed relatively less nonlinear FNC (i.e., lower normalized mutual information), whereas links between the visual and other domains showed evidence of substantial nonlinear and modular properties. Overall, these results suggest that quantifying nonlinear dependencies of functional connectivity may provide a complementary and potentially important tool for studying brain function by exposing relevant variation that is typically ignored. Beyond this, we propose a method that captures both linear and nonlinear effects in a "boosted" approach. This method increases the sensitivity to group differences compared to the standard linear approach, at the cost of being unable to separate linear and nonlinear effects.

Linked brain connectivity patterns with psychopathological and cognitive phenotypes in drug-naïve first-episode schizophrenia

Background

Schizophrenia is considered to be a disorder of dysconnectivity characterized by abnormal functional integration between distinct brain regions. Different brain connection abnormalities were found to be correlated with various clinical manifestations, but whether a common deficit in functional connectivity (FC) in relation to both clinical symptoms and cognitive impairments could present in first-episode patients who have never received any medication remains elusive.

Objective

To find a core deficit in the brain connectome that is related to both psychopathological and cognitive manifestations.

Methods

A total of 75 patients with first-episode schizophrenia and 51 healthy control participants underwent scanning of the brain and clinical ratings of behaviors. A principal component analysis was performed on the clinical ratings of symptom and cognition. Partial correlation analyses were conducted between the main psychopathological components and resting-state FC that were found abnormal in schizophrenia patients.

Results

Using the principal component analysis, the first principal component (PC1) explained 37% of the total variance of seven clinical features. The ratings of GAF and BACS contributed negatively to PC1, while those of PANSS, HAMD, and HAMA contributed positively. The FCs positively correlated with PC1 mainly included connections related to the insula, precuneus gyrus, and some frontal brain regions. FCs negatively correlated with PC1 mainly included connections between the left middle cingulate cortex and superior and middle occipital regions.

Conclusion

In conclusion, we found a linked pattern of FC associated with both psychopathological and cognitive manifestations in drug-naïve first-episode schizophrenia characterized as the dysconnection related to the frontal and visual cortex, which may represent a core deficit of brain FC in patients with schizophrenia.

Early visual processing and adaptation as markers of disease, not vulnerability: EEG evidence from 22q11.2 deletion syndrome, a population at high risk for schizophrenia

We investigated visual processing and adaptation in 22q11.2 deletion syndrome (22q11.2DS), a condition characterized by an increased risk for schizophrenia. Visual processing differences have been described in schizophrenia but remain understudied early in the disease course. Electrophysiology was recorded during a visual adaptation task with different interstimulus intervals to investigate visual processing and adaptation in 22q11.2DS (with (22q+) and without (22q−) psychotic symptoms), compared to control and idiopathic schizophrenia groups. Analyses focused on early windows of visual processing. While increased amplitudes were observed in 22q11.2DS in an earlier time window (90–140 ms), decreased responses were seen later (165–205 ms) in schizophrenia and 22q+. 22q11.2DS, and particularly 22q−, presented increased adaptation effects. We argue that while amplitude and adaptation in the earlier time window may reflect specific neurogenetic aspects associated with a deletion in chromosome 22, amplitude in the later window may be a marker of the presence of psychosis and/or of its chronicity/severity.

Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach

Previous deep learning methods have not captured graph or network representations of brain structural or functional connectome data. To address this, we developed the BrainNet-Global Covariance Pooling-Attention Convolutional Neural Network (BrainNet-GA CNN) by incorporating BrainNetCNN and global covariance pooling into the self-attention mechanism. Resting-state functional magnetic resonance imaging data were obtained from 171 patients with schizophrenia spectrum disorders (SSDs) and 161 healthy controls (HCs). We conducted an ablation analysis of the proposed BrainNet-GA CNN and quantitative performance comparisons with competing methods using the nested tenfold cross validation strategy. The performance of our model was compared with competing methods. Discriminative connections were visualized using the gradient-based explanation method and compared with the results obtained using functional connectivity analysis. The BrainNet-GA CNN showed an accuracy of 83.13%, outperforming other competing methods. Among the top 10 discriminative connections, some were associated with the default mode network and auditory network. Interestingly, these regions were also significant in the functional connectivity analysis. Our findings suggest that the proposed BrainNet-GA CNN can classify patients with SSDs and HCs with higher accuracy than other models. Visualization of salient regions provides important clinical information. These results highlight the potential use of the BrainNet-GA CNN in the diagnosis of schizophrenia.

Atypical Antipsychotics Mediate Dynamics of Intrinsic Brain Activity in Early-Stage Schizophrenia? A Preliminary Study

OBJECTIVE

Abnormalities of static brain activity have been reported in schizophrenia, but it remains to be clarified the temporal variability of intrinsic brain activities in schizophrenia and how atypical antipsychotics affect it.

METHODS

We employed a resting-state functional magnetic resonance imaging (rs-fMRI) and a sliding-window analysis of dynamic amplitude of low-frequency fluctuation (dALFF) to evaluate the dynamic brain activities in schizophrenia (SZ) patients before and after 8-week antipsychotic treatment. Twenty-six schizophrenia individuals and 26 matched healthy controls (HC) were included in this study.

RESULTS

Compared with HC, SZ showed stronger dALFF in the right inferior temporal gyrus (ITG.R) at baseline. After medication, the SZ group exhibited reduced dALFF in the right middle occipital gyrus (MOG.R) and increased dALFF in the left superior frontal gyrus (SFG.L), right middle frontal gyrus (MFG.R), and right inferior parietal lobule (IPL.R). Dynamic ALFF in IPL.R was found to significant negative correlate with the Scale for the Assessment of Negative Symptoms (SANS) scores at baseline.

CONCLUSION

Our results showed dynamic intrinsic brain activities altered in schizophrenia after short term antipsychotic treatment. The findings of this study support and expand the application of dALFF method in the study of the pathological mechanism in psychosis in the future.

Frontal-posterior functional imbalance and aberrant function developmental patterns in schizophrenia

Schizophrenia (SZ) is a neurodevelopmental disorder. There remain significant gaps in understanding the neural trajectory across development in SZ. A major research focus is to clarify the developmental functional changes of SZ and to identify the specific timing, the specific brain regions, and the underlying mechanisms of brain alterations during SZ development. Regional homogeneity (ReHo) characterizing brain function was collected and analyzed on humans with SZ (hSZ) and healthy controls (HC) cross-sectionally, and methylazoxymethanol acetate (MAM) rats, a neurodevelopmental model of SZ, and vehicle rats longitudinally from adolescence to adulthood. Metabolomic and proteomic profiling in adult MAM rats and vehicle rats was examined and bioanalyzed. Compared to HC or adult vehicle rats, similar ReHo alterations were observed in hSZ and adult MAM rats, characterized by increased frontal (medial prefrontal and orbitofrontal cortices) and decreased posterior (visual and associated cortices) ReHo. Longitudinal analysis of MAM rats showed aberrant ReHo patterns as decreased posterior ReHo in adolescence and increased frontal and decreased posterior ReHo in adulthood. Accordingly, it was suggested that the visual cortex was a critical locus and adolescence was a sensitive window in SZ development. In addition, metabolic and proteomic alterations in adult MAM rats suggested that central carbon metabolism disturbance and mitochondrial dysfunction were the potential mechanisms underlying the ReHo alterations. This study proposed frontal-posterior functional imbalance and aberrant function developmental patterns in SZ, suggesting that the adolescent visual cortex was a critical locus and a sensitive window in SZ development. These findings from linking data between hSZ and MAM rats may have a significant translational contribution to the development of effective therapies in SZ.

Abnormal Function in Dentate Nuclei Precedes the Onset of Psychosis: A Resting-State fMRI Study in High-Risk Individuals

OBJECTIVE

The cerebellum serves a wide range of functions and is suggested to be composed of discrete regions dedicated to unique functions. We recently developed a new parcellation of the dentate nuclei (DN), the major output nuclei of the cerebellum, which optimally divides the structure into 3 functional territories that contribute uniquely to default-mode, motor-salience, and visual processing networks as indexed by resting-state functional connectivity (RsFc). Here we test for the first time whether RsFc differences in the DN, precede the onset of psychosis in individuals at risk of developing schizophrenia.

METHODS

We used the magnetic resonance imaging (MRI) dataset from the Shanghai At Risk for Psychosis study that included subjects at high risk to develop schizophrenia (N = 144), with longitudinal follow-up to determine which subjects developed a psychotic episode within 1 year of their functional magnetic resonance imaging (fMRI) scan (converters N = 23). Analysis used the 3 functional parcels (default-mode, salience-motor, and visual territory) from the DN as seed regions of interest for whole-brain RsFc analysis.

RESULTS

RsFc analysis revealed abnormalities at baseline in high-risk individuals who developed psychosis, compared to high-risk individuals who did not develop psychosis. The nature of the observed abnormalities was found to be anatomically specific such that abnormal RsFc was localized predominantly in cerebral cortical networks that matched the 3 functional territories of the DN that were evaluated.

CONCLUSIONS

We show for the first time that abnormal RsFc of the DN may precede the onset of psychosis. This new evidence highlights the role of the cerebellum as a potential target for psychosis prediction and prevention.

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.

Multiple overlapping dynamic patterns of the visual sensory network in schizophrenia

Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, which we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between the middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.

Relationships Among Retinal Nerve Fiber Layer Thickness, Vascular Endothelial Growth Factor, and Cognitive Impairment in Patients with Schizophrenia

BACKGROUND

Studies have suggested retinal nerve fiber layer (RNFL) involvement in the pathogenesis of schizophrenia. Additionally, research has shown that vascular endothelial growth factor (VEGF) potentially contributes to the pathophysiology of psychiatric disorders. Therefore, this study aimed to investigate VEGF, RNFL, and correlations with cognitive impairments in schizophrenia patients.

METHODS

Patients with schizophrenia (n = 138) were compared to healthy controls (n = 160). RNFLs were measured with optical coherence tomography (OCT). The Stroop color and word test (SCWT) was used to evaluate neurocognition. Blood samples were collected to measure VEGF. SPSS 20.0 was used to perform analysis of covariance, t-tests, partial correlation analysis, and linear regression.

RESULTS

Thinner RNFLs were found in schizophrenia patients (p < 0.001). RNFL showed a significant correlation with SCWT scores (all p < 0.05). Serum level of VEGF was lower in patients with schizophrenia (p = 0.010). Total and inferior RNFL thicknesses of right eyes were positively correlated to VEGF level (RNFL total thickness p = 0.032, inferior thickness p = 0.014).Total RNFL thicknesses were shown to be reduced following a prolonged duration of illness (both p < 0.01).

CONCLUSION

These findings suggest that patients with schizophrenia have degeneration with RNFL thickness following illness duration, which may contribute to neurocognitive impairments observed in schizophrenia. VEGF is speculated to play some important role on RNFL degeneration with schizophrenia patients.

Structural and Functional Connectivity of Visual Cortex in Schizophrenia and Bipolar Disorder: A Graph-Theoretic Analysis

Visual processing abnormalities in schizophrenia (SZ) are poorly understood, yet predict functional outcomes in the disorder. Bipolar disorder (BD) may involve similar visual processing deficits. Converging evidence suggests that visual processing may be relatively normal at early stages of visual processing such as early visual cortex (EVC), but that processing abnormalities may become more pronounced by mid-level visual areas such as lateral occipital cortex (LO). However, little is known about the connectivity of the visual system in SZ and BD. If the flow of information to, from, or within the visual system is disrupted by reduced connectivity, this could help to explain perceptual deficits. In the present study, we performed a targeted analysis of the structural and functional connectivity of the visual system using graph-theoretic metrics in a sample of 48 SZ, 46 BD, and 47 control participants. Specifically, we calculated parallel measures of local efficiency for EVC and LO from both diffusion weighted imaging data (structural) and resting-state (functional) imaging data. We found no structural connectivity differences between the groups. However, there was a significant group difference in functional connectivity and a significant group-by-region interaction driven by reduced LO connectivity in SZ relative to HC, whereas BD was approximately intermediate to the other 2 groups. We replicated this pattern of results using a different brain atlas. These findings support and extend theoretical models of perceptual dysfunction in SZ, providing a framework for further investigation of visual deficits linked to functional outcomes in SZ and related disorders.

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in, eg, perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Perceptual variability may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients (N = 20), synesthetes (N = 20), and controls (N = 26). Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors-introduced during the hysteresis experiment-lowered thresholds but did not normalize perception. Our results imply that perceptual variability might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.

Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity

Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

Deficits and compensation: Attentional control cortical networks in schizophrenia

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Examined attention systems in SzP with resting-state connectivity and task fMRI.

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SzP have functional connectivity deficits in late visual cortex and prefrontal areas.

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Task performance correlated with ventral attention network deactivation in SzP only.

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This relationship is mediated by connectivity of key attentional control components.

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Results reveal deficits and potential compensation in SzP visual processing/attention.

Visual processing and attention deficits are responsible for a substantial portion of the disability caused by schizophrenia, but the source of these deficits remains unclear. In 35 schizophrenia patients (SzP) and 34 healthy controls (HC), we used a rapid serial visual presentation (RSVP) visual search task designed to activate/deactivate the cortical components of the attentional control system (i.e. the dorsal and ventral attention networks, lateral prefrontal regions in the frontoparietal network, and cingulo-opercular/salience networks), along with resting state functional connectivity, to examine the integrity of these components. While we find that behavioral performance and activation/deactivation of the RSVP task are largely similar between groups, SzP exhibited decreased functional connectivity within late visual components and between prefrontal and other components. We also find that performance correlates with the deactivation of the ventral attention network in SzP only. This relationship is mediated by the functional connectivity of critical components of the attentional control system. In summary, our results suggest that the attentional control system is potentially used to compensate for visual cortex deficits. Furthermore, prefrontal deficits in SzP may interfere with this compensatory use of the attentional control system. In addition to highlighting focal deficits and potential compensatory mechanisms in visual processing and attention, our findings point to the attentional control system as a potential target for rehabilitation and neuromodulation-based treatments for visual processing deficits in SzP.

A common variant of the NOTCH4 gene modulates functional connectivity of the occipital cortex and its relationship with schizotypal traits

BACKGROUND

Schizotypal traits are considered as inheritable traits and the endophenotype for schizophrenia. A common variant in the NOTCH4 gene, rs204993, has been linked with schizophrenia, but the neural underpinnings are largely unknown.

METHODS

In present study, we compared the differences of brain functions between different genotypes of rs204993 and its relationship with schizotypal traits among 402 Chinese Han healthy volunteers. The brain function was evaluated with functional connectivity strength (FCS) using the resting-state functional magnetic resonance image(rs-fMRI). The schizotypal traits were measured by the schizotypal personality questionnaire (SPQ).

RESULTS

Our results showed that carriers with the AA genotype showed reduced FCS in the left occipital cortex when compared with carriers with the AG and GG genotypes, and the carriers with the AG genotype showed reduced FCS in the left occipital cortex when compared with carriers with the GG genotype. The FCS values in the left occipital lobe were negatively associated with the SPQ scores and its subscale scores within the carriers with the GG genotype, but not within the carriers with AA or AG genotype.

CONCLUSION

Our results suggested that the common variant in the NOTCH4 gene, rs204993, modulates the function of the occipital cortex, which may contribute to schizotypal traits. These findings provide insight for genetic effects on schizotypal traits and its potential neural substrate.

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker

The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing individual brain health and for identifying neurodegenerative and neuropsychiatric diseases. Using a large-scale structural covariance network (SCN)-based framework with machine learning algorithms, we demonstrate this framework's ability to predict individual brain age in a large sample of middle-to-late age adults, and highlight its clinical specificity for several disease populations from a network perspective. A proposed estimator with 40 SCNs could predict individual brain age, balancing between model complexity and prediction accuracy. Notably, we found that the most significant SCN for predicting brain age included the caudate nucleus, putamen, hippocampus, amygdala, and cerebellar regions. Furthermore, our data indicate a larger brain age disparity in patients with schizophrenia and Alzheimer's disease than in healthy controls, while this metric did not differ significantly in patients with major depressive disorder. These findings provide empirical evidence supporting the estimation of brain age from a brain network perspective, and demonstrate the clinical feasibility of evaluating neurological diseases hypothesized to be associated with accelerated brain aging.

Context-dependent dynamic functional connectivity alteration of lateral occipital cortex in schizophrenia

Schizophrenia has long been associated with dysfunction in visual perception. One important region underlying this is lateral occipital cortex (LOC), a mid-level visual region critical for object recognition. Although LOC of patients has exhibited structural and functional abnormalities in MR brain imaging studies, how it interacts with other networks over time under rest and with task demands remains to be clarified. The present study investigated the spatial-temporal interaction of LOC with other brain networks by examining functional connectivity communities of the brain over time. We found increased temporal instability of LOC connectivity over time under both resting and task-switching conditions in patients. In the resting state, LOC of patients had increased interaction with the frontoparietal task-control network (FPTC) and thalamus compared with controls, while during task switching, LOC showed increased interaction with the default mode network (DMN). Temporal instability of LOC connectivity was positively correlated with patients' switching cost during task performance and with hallucination severity. These results indicate that reduced stability of LOC connectivity may be an important factor underlying neurocognitive dysfunctions and symptom severity in schizophrenia.

Visual Cortical Alterations and their Association with Negative Symptoms in Antipsychotic-Naïve First Episode Psychosis

Visual perceptual and processing deficits are common in schizophrenia and possibly point towards visual pathway alterations. However, no studies have examined visual cortical morphology in first-episode psychosis (FEP). In an antipsychotic-naïve FEP population, we investigated primary visual (V1), association area (V2), and motion perception (V5/MT) morphology compared to controls. We found reductions in the V1 and V2 areas, greater MT area and lower MT thickness in the FEP-schizophrenia group when compared to controls. Also, lower MT thickness was associated with worse negative symptoms. Our results shed light on this poorly studied area of visual cortex morphology in FEP.

Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns

Resting-state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partitioned heritability analysis for multidimensional functional connectivity patterns, which revealed the common and unique enrichment patterns of the genetic contributions to brain connectivity patterns for several gene sets linked to brain functions, including the genes expressed preferentially in the central nervous system and those associated with intelligence, educational attainment, attention-deficit/hyperactivity disorder, and schizophrenia. These results for the first time reveal the genetic architecture of multidimensional brain connectivity patterns across different networks and advance our understanding of the complex relationship between gene sets, neural networks, and behaviors.

Abnormalities of intrinsic regional brain activity in first-episode and chronic schizophrenia: a meta-analysis of resting-state functional MRI

BACKGROUND

Resting-state functional MRI (fMRI) studies have provided much evidence for abnormal intrinsic brain activity in schizophrenia, but results have been inconsistent.

METHODS

We conducted a meta-analysis of whole-brain, resting-state fMRI studies that explored differences in amplitude of low-frequency fluctuation (ALFF) between people with schizophrenia (including first episode and chronic) and healthy controls.

RESULTS

A systematic literature search identified 24 studies comparing a total of 1249 people with schizophrenia and 1179 healthy controls. Overall, patients with schizophrenia displayed decreased ALFF in the bilateral postcentral gyrus, bilateral precuneus, left inferior parietal gyri and right occipital lobe, and increased ALFF in the right putamen, right inferior frontal gyrus, left inferior temporal gyrus and right anterior cingulate cortex. In the subgroup analysis, patients with first-episode schizophrenia demonstrated decreased ALFF in the bilateral inferior parietal gyri, right precuneus and left medial prefrontal cortex, and increased ALFF in the bilateral putamen and bilateral occipital gyrus. Patients with chronic schizophrenia showed decreased ALFF in the bilateral postcentral gyrus, left precuneus and right occipital gyrus, and increased ALFF in the bilateral inferior frontal gyri, bilateral superior frontal gyrus, left amygdala, left inferior temporal gyrus, right anterior cingulate cortex and left insula.

LIMITATIONS

The small sample size of our subgroup analysis, predominantly Asian samples, processing steps and publication bias could have limited the accuracy of the results.

CONCLUSION

Our comprehensive meta-analysis suggests that findings of aberrant regional intrinsic brain activity during the initial stages of schizophrenia, and much more widespread damage with the progression of disease, may contribute to our understanding of the progressive pathophysiology of schizophrenia.

Multimodal Computational Modeling of Visual Object Recognition Deficits but Intact Repetition Priming in Schizophrenia

The term perceptual closure refers to the neural processes responsible for "filling-in" missing information in the visual image under highly adverse viewing conditions such as fog or camouflage. Here we used a closure task that required the participants to identify barely recognizable fragmented line-drawings of common objects. Patients with schizophrenia have been shown to perform poorly on this task. Following priming, controls and importantly patients can complete the line-drawings at greater levels of fragmentation behaviorally, suggesting an improvement in their ability to perform the task. Closure phenomena have been shown to involve a distributed network of cortical regions, notably the lateral occipital complex (LOC) of the ventral visual stream, dorsal visual stream (DS), hippocampal formation (HIPP) and the prefrontal cortex (PFC). We have previously demonstrated the failure of closure processes in schizophrenia and shown that the dysregulation in the sensory information transmitted to the prefrontal cortex plays a critical role in this failure. Here, using a multimodal imaging approach in patients, combining event related electrophysiological recordings (ERP) and functional magnetic resonance imaging (fMRI), we characterize the spatiotemporal dynamics of priming in perceptual closure. Using directed functional connectivity measures we demonstrate that priming modifies the network-level interactions between the nodes of closure processing in a manner that is functionally advantageous to patients resulting in the mitigation of their deficit in perceptual closure.

Evidence for intact stimulus-specific neural adaptation for visual objects in schizophrenia and bipolar disorder: An ERP study

People with schizophrenia (SZ) or bipolar disorder (BD) experience dysfunction in visual processing. Dysfunctional neural tuning, in which neurons and neuronal populations are selectively activated by specific features of visual stimuli, may contribute to these deficits. Few studies have examined this possibility and there are inconsistent findings of tuning deficits in the literature. We utilized an event-related potential (ERP) paradigm to examine neural adaptation for visual objects, a measure of neural tuning whereby neurons respond less strongly to the repeated presentation of the same stimulus. Seventy-seven SZ, 53 BD, and 49 healthy comparison participants (HC) were examined. In three separate conditions, pictures of objects were presented repeatedly: the same object (SS), different objects from the same category (e.g., two different vases; SD), or different objects from different categories (e.g., a barrel and a clock, DD). Mass-univariate cluster-based permutation analyses identified electrodes and time-windows in which there were significant differences between the SS vs. DD and the SD vs. DD conditions. Mean ERP amplitudes were extracted from these clusters and analyzed for group differences. Results revealed a significant condition difference over parieto-occipital electrodes for the SS-DD comparison between 109–164 ms and for the SD-DD comparison between 78–203 ms, with larger amplitudes in the DD compared to either SS or SD condition. However, there were no significant differences in the pattern of results between groups. Thus, while we found neural adaptation effects using this ERP paradigm, we did not find evidence of group differences. Our results suggest that people with SZ or BD may not exhibit deficits in neural tuning for processing of visual objects using this EEG task with rapidly presented stimuli. However, the results are inconsistent with other studies using different methodologies (e.g., fMRI, behavioral tasks) that have found tuning deficits in people with schizophrenia.

Altered topological characteristics of morphological brain network relate to language impairment in high genetic risk subjects and schizophrenia patients

OBJECTIVE

Evidence suggests relationships between abnormalities in various cortical and subcortical brain structures and language dysfunction in individuals with schizophrenia, and to some extent in those with increased genetic risk for this diagnosis. The topological features of the structural brain network at the systems-level and their impact on language function in schizophrenia and in those at high genetic risk has been less well studied.

METHOD

Single-subject morphological brain network was constructed in a total of 71 subjects (20 patients with schizophrenia, 19 individuals at high genetic risk for schizophrenia, and 32 controls). Among these 71 subjects, 56 were involved in our previous neuroimaging studies. Graphic Theoretical Techniques was applied to calculate the global and nodal topological characteristics of the morphological brain network of each participant. Index scores for five language-related cognitive tests were also attained from each participant.

RESULTS

Significantly smaller nodal degree in bilateral superior occipital gyri (SOG) were observed in individuals with schizophrenia, as compared to the controls and those at high risk; while significantly reduced nodal betweenness centrality (quantifying the level of a node in connecting other nodes in the network) in right middle frontal gyrus (MFG) was found in the high-risk group, relative to controls. The right MFG nodal efficiency and hub capacity (represented by both nodal degree and betweenness centrality) of the morphological brain network were negatively associated with the wide range achievement test (WRAT) standard performance score; while the right SOG nodal degree was positively associated with the WRAT standard performance score, in the entire study sample.

CONCLUSIONS

These findings enhance the understanding of structural brain abnormalities at the systems-level in individuals with schizophrenia and those at high genetic risk, which may serve as critical neural substrates for the origin of the language-related impairments and symptom manifestations of schizophrenia.

Gestalt Perception in Children With Visual Impairments: Item-Specific Performance and Looking Behavior

Visual closure is the ability to visualize a complete whole when an incomplete picture is presented. The aim of the present study was to investigate the Kaufman Gestalt closure task in children with cerebral and ocular visual impairments. Looking behavior was assessed by an eye tracker system to quantify the number and duration of fixations. We found that children with visual impairments due to cerebral damage show weaker Gestalt perception and had different looking patterns than children with ocular or without visual impairments. Children with brain damage performed significantly worse on the animate items than the group without brain damage.

Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia

BACKGROUND

The functional architecture of resting-state networks (RSNs) is defined by their connectivity and metastability. Disrupted RSN connectivity has been amply demonstrated in schizophrenia while the role of metastability remains poorly defined. Here, we undertake a comprehensive characterisation of RSN organization in schizophrenia and test its contribution to the clinical profile of this disorder.

METHODS

We extracted RSNs representing the default mode (DMN), central executive (CEN), salience (SAL), language (LAN), sensorimotor (SMN), auditory (AN) and visual (VN) networks from resting-state functional magnetic resonance imaging data obtained from patients with schizophrenia (n = 85) and healthy individuals (n = 48). For each network, we computed its functional cohesiveness and integration and used the Kuramoto order parameter to compute metastability. We used stepwise multiple regression analyses to test these RSN features as predictors of symptom severity in patients.

RESULTS

RSN features respectively explained 14%, 17%, 12% and 5% of the variance in positive, negative, anxious/depressive and agitation/disorganization symptoms. Lower functional integration between the DMN, CEN and SMN primarily contributed to positive symptoms. The functional properties of the SAL network were key predictors of all other symptom dimensions; specifically, lower cohesiveness of the SAL, lower integration of this network with the LAN and higher integration with the CEN respectively contributed to negative, anxious/depressive and disorganization symptoms. Increased SAL metastability was associated with negative symptoms.

CONCLUSIONS

These results confirm the primacy of the SAL network for schizophrenia and demonstrate that abnormalities in RSN connectivity and metastability are significant predictors of schizophrenia-related psychopathology.

A Connectome-wide Functional Signature of Transdiagnostic Risk for Mental Illness

BACKGROUND

High rates of comorbidity, shared risk, and overlapping therapeutic mechanisms have led psychopathology research toward transdiagnostic dimensional investigations of clustered symptoms. One influential framework accounts for these transdiagnostic phenomena through a single general factor, sometimes referred to as the p factor, associated with risk for all common forms of mental illness.

METHODS

We build on previous research identifying unique structural neural correlates of the p factor by conducting a data-driven analysis of connectome-wide intrinsic functional connectivity (n = 605).

RESULTS

We demonstrate that higher p factor scores and associated risk for common mental illness maps onto hyperconnectivity between visual association cortex and both frontoparietal and default mode networks.

CONCLUSIONS

These results provide initial evidence that the transdiagnostic risk for common forms of mental illness is associated with patterns of inefficient connectome-wide intrinsic connectivity between visual association cortex and networks supporting executive control and self-referential processes, networks that are often impaired across categorical disorders.

Varieties of Self Disorder: A Bio-Pheno-Social Model of Schizophrenia

The self-disorder model offers a unifying way of conceptualizing schizophrenia's highly diverse symptoms (positive, negative, disorganized), of capturing their distinctive bizarreness, and of conceiving their longitudinal development. These symptoms are viewed as differing manifestations of an underlying disorder of ipseity or core-self: hyper-reflexivity/diminished-self-presence with accompanying disturbances of "grip" or "hold" on reality. Recent revision to this phenomenological theory, in particular distinguishing primary-vs-secondary factors, offers a bio-pheno-social model that is consistent with recent empirical findings and offers several advantages: (1) It helps account for the temporal variations of the symptoms or syndrome, including longitudinal progression, but also the shorter-term, situationally reactive, and sometimes defensive or quasi-intentional variability of symptom-expression that can occur in schizophrenia (consistent with understanding some aspects of ipseity-disturbance as dynamic and mutable, involving shifting attitudes or experiential orientations). (2) It accommodates the overlapping of some key schizophrenic symptoms with certain nonschizophrenic conditions involving dissociation (depersonalization, derealization), including depersonalization disorder and panic disorder, thereby acknowledging both shared and distinguishing symptoms. (3) It integrates recent neurocognitive and neurobiological as well as psychosocial (eg, influence of trauma and culture) findings into a coherent but multi-factorial neuropsychological account. An adequate model of schizophrenia will postulate shared disturbances of core-self experiences that nevertheless can follow several distinct pathways and occur in various forms. Such a model is preferable to uni-dimensional alternatives-whether of schizophrenia or ipseity-disturbance-given its ability to account for distinctive yet varying experiential and neurocognitive abnormalities found in research on schizophrenia, and to integrate these with recent psychosocial and neurobiological findings.