Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia

Visualizing functional network connectivity differences using an explainable machine-learning method

Objective. Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control. While machine learning models can improve classification accuracy, they often lack interpretability, making it difficult to understand how they arrive at their decisions.Approach. Explainable machine learning helps address this issue by identifying which features contribute most to the model's predictions. In this study, we introduce a novel framework leveraging SHapley Additive exPlanations (SHAPs) to identify crucial FNC features distinguishing between two distinct population classes.Main results. Initially, we validate our approach using synthetic data. Subsequently, applying our framework, we ascertain FNC biomarkers distinguishing between, controls and schizophrenia (SZ) patients with accuracy of 81.04% as well as middle aged adults and old aged adults with accuracy 71.38%, respectively, employing random forest, XGBoost, and CATBoost models.Significance. Our analysis underscores the pivotal role of the cognitive control network (CCN), subcortical network (SCN), and somatomotor network in discerning individuals with SZ from controls. In addition, our platform found CCN and SCN as the most important networks separating young adults from older.

Schizophrenia and Neurodevelopment: Insights From Connectome Perspective

BACKGROUND

Schizophrenia is conceptualized as a brain connectome disorder that can emerge as early as late childhood and adolescence. However, the underlying neurodevelopmental basis remains unclear. Recent interest has grown in children and adolescent patients who experience symptom onset during critical brain development periods. Inspired by advanced methodological theories and large patient cohorts, Chinese researchers have made significant original contributions to understanding altered brain connectome development in early-onset schizophrenia (EOS).

STUDY DESIGN

We conducted a search of PubMed and Web of Science for studies on brain connectomes in schizophrenia and neurodevelopment. In this selective review, we first address the latest theories of brain structural and functional development. Subsequently, we synthesize Chinese findings regarding mechanisms of brain structural and functional abnormalities in EOS. Finally, we highlight several pivotal challenges and issues in this field.

STUDY RESULTS

Typical neurodevelopment follows a trajectory characterized by gray matter volume pruning, enhanced structural and functional connectivity, improved structural connectome efficiency, and differentiated modules in the functional connectome during late childhood and adolescence. Conversely, EOS deviates with excessive gray matter volume decline, cortical thinning, reduced information processing efficiency in the structural brain network, and dysregulated maturation of the functional brain network. Additionally, common functional connectome disruptions of default mode regions were found in early- and adult-onset patients.

CONCLUSIONS

Chinese research on brain connectomes of EOS provides crucial evidence for understanding pathological mechanisms. Further studies, utilizing standardized analyses based on large-sample multicenter datasets, have the potential to offer objective markers for early intervention and disease treatment.

Identifying neurobiological heterogeneity in clinical high-risk psychosis: a data-driven biotyping approach using resting-state functional connectivity

To explore the neurobiological heterogeneity within the Clinical High-Risk (CHR) for psychosis population, this study aimed to identify and characterize distinct neurobiological biotypes within CHR using features from resting-state functional networks. A total of 239 participants from the Shanghai At Risk for Psychosis (SHARP) program were enrolled, consisting of 151 CHR individuals and 88 matched healthy controls (HCs). Functional connectivity (FC) features that were correlated with symptom severity were subjected to the single-cell interpretation through multikernel learning (SIMLR) algorithm in order to identify latent homogeneous subgroups. The cognitive function, clinical symptoms, FC patterns, and correlation with neurotransmitter systems of biotype profiles were compared. Three distinct CHR biotypes were identified based on 646 significant ROI-ROI connectivity features, comprising 29.8%, 19.2%, and 51.0% of the CHR sample, respectively. Despite the absence of overall FC differences between CHR and HC groups, each CHR biotype demonstrated unique FC abnormalities. Biotype 1 displayed augmented somatomotor connection, Biotype 2 shown compromised working memory with heightened subcortical and network-specific connectivity, and Biotype 3, characterized by significant negative symptoms, revealed extensive connectivity reductions along with increased limbic-subcortical connectivity. The neurotransmitter correlates differed across biotypes. Biotype 2 revealed an inverse trend to Biotype 3, as increased neurotransmitter concentrations improved functional connectivity in Biotype 2 but reduced it in Biotype 3. The identification of CHR biotypes provides compelling evidence for the early manifestation of heterogeneity within the psychosis spectrum, suggesting that distinct pathophysiological mechanisms may underlie these subgroups.

Schizophrenia spectrum disorders in children and adolescents: Clinical, phenomenological, diagnostic, and prognostic features across subtypes

Schizophrenia spectrum disorders (SSD) typically have a diagnostically recognizable onset in young adulthood, yet it is not unusual that help-seeking due to initial SSD-related clinical manifestations emerge in earlier developmental phases, such as childhood and adolescence. Varieties of SSD manifestations in children and adolescents can be distinguished according to variations in clinical expressivity, severity and timing (i.e. developmental stage). Some individuals may reach the full clinical threshold for a diagnosis of schizophrenia according to the same descriptive diagnostic criteria used for adults, and in this case, it's possible to distinguish a pre-pubertal onset in childhood (aka Very Early Onset Schizophrenia, VEOS) and a post-pubertal onset in adolescence (aka Early Onset Schizophrenia, EOS). Other individuals may not reach such clinically overt diagnostic threshold but nonetheless present Childhood Schizotypal Disorder (CSD) or a Clinical High-Risk for Psychosis (CHRP). While EOS is clinically more similar to the canonical adult-onset presentation, the other 3 subgroups (i.e. VEOS, CSD, CHRP) present more nuances and specific clinical characteristics, which require ad-hoc developmental and phenomenological considerations for appropriate differential diagnosis and prognosis. Therefore, current scoping review intends to saturate such knowledge gap with respect to early SSD-phenotypes.

Regional neural functional efficiency across schizophrenia, bipolar disorder, and major depressive disorder: a transdiagnostic resting-state fMRI study

BACKGROUND

Major psychiatric disorders (MPDs) are delineated by distinct clinical features. However, overlapping symptoms and transdiagnostic effectiveness of medications have challenged the traditional diagnostic categorisation. We investigate if there are shared and illness-specific disruptions in the regional functional efficiency (RFE) of the brain across these disorders.

METHODS

We included 364 participants (118 schizophrenia [SCZ], 80 bipolar disorder [BD], 91 major depressive disorder [MDD], and 75 healthy controls [HCs]). Resting-state fMRI was used to caclulate the RFE based on the static amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality and corresponding dynamic measures indicating variability over time. We used principal component analysis to obtain static and dynamic RFE values. We conducted functional and genetic annotation and enrichment analysis based on abnormal RFE profiles.

RESULTS

SCZ showed higher static RFE in the cortico-striatal regions and excessive variability in the cortico-limbic regions. SCZ and MDD shared lower static RFE with higher dynamic RFE in sensorimotor regions than BD and HCs. We observed association between static RFE abnormalities with reward and sensorimotor functions and dynamic RFE abnormalities with sensorimotor functions. Differential spatial expression of genes related to glutamatergic synapse and calcium/cAMP signaling was more likely in the regions with aberrant RFE.

CONCLUSIONS

SCZ shares more regions with disrupted functional integrity, especially in sensorimotor regions, with MDD rather than BD. The neural patterns of these transdiagnostic changes appear to be potentially driven by gene expression variations relating to glutamatergic synapses and calcium/cAMP signaling. The aberrant sensorimotor, cortico-striatal, and cortico-limbic integrity may collectively underlie neurobiological mechanisms of MPDs.

Altered intrinsic neural activity and its molecular analyses in first-episode schizophrenia with auditory verbal hallucinations

Background

Auditory verbal hallucinations (AVHs) are one of the signature positive symptoms of schizophrenia, affecting a substantial portion of patients with schizophrenia. These hallucinations seriously impact the lives of patients, resulting in a substantial social burden. Recent studies have shown a significant correlation between abnormal local brain activity and the neurobiological mechanisms of AVHs. However, it is not fully clear whether altered intrinsic brain activity in schizophrenia patients with AVHs is correlated with specific neurotransmitter systems.

Methods

We included 50 first-episode, drug-naïve schizophrenia patients with AVHs, 50 patients without AVHs (NAVHs), and 50 age- and sex-matched healthy controls (HCs). The amplitude of low-frequency fluctuation (ALFF) was utilized to explore the altered intrinsic brain activity in the AVH group. Subsequently, we spatially correlated the altered ALFF with neurotransmitter maps using JuSpace.

Results

In our study, compared to HCs, the AVH group exhibited significantly reduced ALFF in multiple brain regions, mainly including the left precuneus, bilateral supplementary motor areas, bilateral paracentral lobules, bilateral precentral gyri, and bilateral postcentral gyri. The NAVH group showed significantly reduced ALFF in the left inferior occipital gyrus, left calcarine gyrus, and left lingual gyrus compared to HCs. Furthermore, the AVH group showed higher ALFF in the right inferior frontal gyrus compared to the NAVH group. Additionally, these ALFF alterations in the AVH group were closely related to three neurotransmitters, including dopamine, serotonin and norepinephrine.

Conclusion

We link neurotransmitters to abnormal intrinsic brain activity in first-episode, drug-naïve schizophrenia patients with AVHs, contributing to a comprehensive understanding of the pathophysiological processes and treatment pathways underlying AVHs.

White matter functional networks in the developing brain

Background

Functional magnetic resonance imaging (fMRI) is widely used to depict neural activity and understand human brain function. Studies show that functional networks in gray matter undergo complex transformations from neonatal age to childhood, supporting rapid cognitive development. However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear.

Purpose

Aims to examine and compare white matter functional networks in neonates and 8-year-old children.

Methods

We acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks' characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter.

Results

White matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (p < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds (p < 0.05). Additionally, 8-year-olds showed a greater distribution of brain activity energy in the high-frequency range of 0.01-0.15 Hz. Significant developmental differences in brain white matter functional networks exist between the two group, characterized by increased inter-network FC, decreased intra-network FC, and higher high-frequency energy distribution. Similar findings were also observed in gray matter functional networks.

Conclusion

White matter functional networks can be reliably measured in the developing brain, and the differences in these networks reflect functional differentiation and integration in brain development.

Incremental predictive value of genetic risk and functional brain connectivity in determining antipsychotic response in schizophrenia

We aimed to assess the incremental value of schizophrenia polygenic risk score (PgRS) and resting-state functional brain connectivity (rsFC) when added to clinical data in predicting the six-week response to oral risperidone (Risperdal) in schizophrenia. Fifty-seven, 54, and 43 individuals in a group of never-before-treated first-episode schizophrenia had good quality whole-genome sequencing (10x), rsFC, and both genomic and rsFC data, respectively, at baseline. Symptom severity ratings were obtained at baseline and six-weeks of oral risperidone (Risperdal) treatment. The primary outcome was the percentage change in the Positive and Negative Syndrome Scale Total scores after risperidone (Risperdal) treatment. Clinical, PgRS, and rsFC determinants of treatment response were first evaluated independently. Subsequently, three blocks of hierarchical multiple regression analyses with leave-one-out cross-validation (n = 43), were implemented to study clinical, clinical + PgRS and clinical + PgRS + rsFC determinants of treatment response. While the combined clinical variables did not show a statistically significant prediction of treatment response, adding PgRS (9 % R2 change) and rsFC (26 % R2 change) in hierarchical steps, significantly improved the overall proportion of variance explained in treatment response. This proof-of-concept investigation underscores the incremental benefits offered by genetic and neuroimaging metrics over clinical measures in determining prospectively-ascertained short-term treatment response in first-episode schizophrenia.

A connectome-based model of delusion in schizophrenia using functional connectivity under working memory task

Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.

Brain network functional connectivity changes in long illness duration chronic schizophrenia

Introduction

Chronic schizophrenia has a course of 5 years or more and has a widespread abnormalities in brain functional connectivity. This study aimed to find characteristic functional and structural changes in a long illness duration chronic schizophrenia (10 years or more).

Methods

Thirty-six patients with a long illness duration chronic schizophrenia and 38 healthy controls were analyzed by independent component analysis of brain network functional connectivity. Correlation analysis with clinical duration was performed on six resting state networks: auditory network, default mode network, dorsal attention network, fronto-parietal network, somatomotor network, and visual network.

Results

The differences in the resting state network between the two groups revealed that patients exhibited enhanced inter-network connections between default mode network and multiple brain networks, while the inter-network connections between somatomotor network, default mode network and visual network were reduced. In patients, functional connectivity of Cuneus_L was negatively correlated with illness duration. Furthermore, receiver operating characteristic curve of functional connectivity showed that changes in Thalamus_L, Rectus_L, Frontal_Mid_R, and Cerebelum_9_L may indicate a longer illness duration chronic schizophrenia.

Discussion

In our study, we also confirmed that the course of disease is significantly associated with specific brain regions, and the changes in specific brain regions may indicate that chronic schizophrenia has a course of 10 years or more.

Dynamic structure-function coupling across three major psychiatric disorders

BACKGROUND

Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).

METHODS

We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time.

RESULTS

The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.

CONCLUSIONS

These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Cross-cohort replicable resting-state functional connectivity in predicting symptoms and cognition of schizophrenia

Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well as cognitive impairments. Despite a plethora of studies leveraging functional connectivity (FC) from functional magnetic resonance imaging (fMRI) to predict symptoms and cognitive impairments of SZ, the findings have exhibited great heterogeneity. We aimed to identify congruous and replicable connectivity patterns capable of predicting positive and negative symptoms as well as cognitive impairments in SZ. Predictable functional connections (FCs) were identified by employing an individualized prediction model, whose replicability was further evaluated across three independent cohorts (BSNIP, SZ = 174; COBRE, SZ = 100; FBIRN, SZ = 161). Across cohorts, we observed that altered FCs in frontal-temporal-cingulate-thalamic network were replicable in prediction of positive symptoms, while sensorimotor network was predictive of negative symptoms. Temporal-parahippocampal network was consistently identified to be associated with reduced cognitive function. These replicable 23 FCs effectively distinguished SZ from healthy controls (HC) across three cohorts (82.7%, 90.2%, and 86.1%). Furthermore, models built using these replicable FCs showed comparable accuracies to those built using the whole-brain features in predicting symptoms/cognition of SZ across the three cohorts (r = .17-.33, p < .05). Overall, our findings provide new insights into the neural underpinnings of SZ symptoms/cognition and offer potential targets for further research and possible clinical interventions.

From periphery immunity to central domain through clinical interview as a new insight on schizophrenia

Identifying disease predictors through advanced statistical models enables the discovery of treatment targets for schizophrenia. In this study, a multifaceted clinical and laboratory analysis was conducted, incorporating magnetic resonance spectroscopy with immunology markers, psychiatric scores, and biochemical data, on a cohort of 45 patients diagnosed with schizophrenia and 51 healthy controls. The aim was to delineate predictive markers for diagnosing schizophrenia. A logistic regression model was used, as utilized to analyze the impact of multivariate variables on the prevalence of schizophrenia. Utilization of a stepwise algorithm yielded a final model, optimized using Akaike's information criterion and a logit link function, which incorporated eight predictors (White Blood Cells, Reactive Lymphocytes, Red Blood Cells, Glucose, Insulin, Beck Depression score, Brain Taurine, Creatine and Phosphocreatine concentration). No single factor can reliably differentiate between healthy patients and those with schizophrenia. Therefore, it is valuable to simultaneously consider the values of multiple factors and classify patients using a multivariate model.

Functional network interactions in patients with schizophrenia with persistent auditory verbal hallucinations: A multimodal MRI fusion approach using three-way pICA

Over the last decade, there have been an increasing number of functional magnetic resonance imaging (fMRI) studies examining brain activity in schizophrenia (SZ) patients with persistent auditory verbal hallucinations (AVH) using either task-based or resting-state fMRI (rs-fMRI) paradigms. Such data have been conventionally collected and analyzed as distinct modalities, disregarding putative crossmodal interactions. Recently, it has become possible to incorporate two or more modalities in one comprehensive analysis to uncover hidden patterns of neural dysfunction not sufficiently captured by separate analysis. A novel multivariate fusion approach to multimodal data analysis, i.e., parallel independent component analysis (pICA), has been previously shown to be a powerful tool in this regard. We utilized three-way pICA to study covarying components among fractional amplitude of low-frequency fluctuations (fALFF) for rs-MRI and task-based activation computed from an alertness and a working memory (WM) paradigm of 15 SZ patients with AVH, 16 non-hallucinating SZ patients (nAVH), and 19 healthy controls (HC). The strongest connected triplet (false discovery rate (FDR)-corrected pairwise correlations) comprised a frontostriatal/temporal network (fALFF), a temporal/sensorimotor network (alertness task), and a frontoparietal network (WM task). Frontoparietal and frontostriatal/temporal network strength significantly differed between AVH patients and HC. Phenomenological features such as omnipotence and malevolence of AVH were associated with temporal/sensorimotor and frontoparietal network strength. The transmodal data confirm a complex interplay of neural systems subserving attentional processes and cognitive control interacting with speech and language processing networks. In addition, the data emphasize the importance of sensorimotor regions modulating specific symptom dimensions of AVH.

Motion and Form Perception in Childhood-Onset Schizophrenia

(1) Background: Childhood-onset schizophrenia (COS) is a rare type of psychotic disorder characterized by delusions, hallucinations, grossly disorganized behavior, and poor psychosocial functioning. The etiology of COS is unknown, but neurodevelopmental factors are likely to play a critical role. A potential neurodevelopmental anomaly marker is the dorsal visual system dysfunction, which is implicated in motion perception, spatial functions, and attention. (2) Methods: To elucidate the role of the dorsal visual system in COS, we investigated 21 patients with COS and 21 control participants matched for age, sex, education, IQ, and parental socioeconomic status. Participants completed a motion and form coherence task, during which one assesses an individual's ability to detect the direction of motion within a field of moving elements or dots and to recognize a meaningful form or object from a set of fragmented or disconnected visual elements, respectively. (3) Results: The patients with COS were impaired in both visual tasks compared to the control participants, but the evidence for the deficit was more substantial for motion perception than for form perception (form: BF10 = 27.22; motion: BF10 = 6.97 × 106). (4) Conclusions: These results highlight the importance of dorsal visual stream vulnerability in COS, a potential marker of neurodevelopmental anomalies.

Cortical structural changes of morphometric similarity network in early-onset schizophrenia correlate with specific transcriptional expression patterns

BACKGROUND

This study aimed to investigate the neuroanatomical subtypes among early-onset schizophrenia (EOS) patients by exploring the association between structural alterations and molecular mechanisms using a combined analysis of morphometric similarity network (MSN) changes and specific transcriptional expression patterns.

METHODS

We recruited 206 subjects aged 7 to 17 years, including 100 EOS patients and 106 healthy controls (HC). Heterogeneity through discriminant analysis (HYDRA) was used to identify the EOS subtypes within the MSN strength. The differences in morphometric similarity between each EOS subtype and HC were compared. Furthermore, we examined the link between morphometric changes and brain-wide gene expression in different EOS subtypes using partial least squares regression (PLS) weight mapping, evaluated genetic commonalities with psychiatric disorders, identified functional enrichments of PLS-weighted genes, and assessed cellular transcriptional signatures.

RESULTS

Two distinct MSN-based EOS subtypes were identified, each exhibiting different abnormal MSN strength and cognitive functions compared to HC. The PLS1 score mapping demonstrated anterior-posterior gradients of gene expression in EOS1, whereas inverse distributions were observed in EOS2 cohorts. Genetic commonalities were identified in autistic disorder and adult schizophrenia with EOS1 and inflammatory bowel diseases with EOS2 cohorts. The EOS1 PLS1- genes (Z < -5) were significantly enriched in synaptic signaling-related functions, whereas EOS2 demonstrated enrichments in virtual infection-related pathways. Furthermore, the majority of observed associations with EOS1-specific MSN strength differences contributed to specific transcriptional changes in astrocytes and neurons.

CONCLUSIONS

The findings of this study provide a comprehensive analysis of neuroanatomical subtypes in EOS, shedding light on the intricate relationships between macrostructural and molecular aspects of the EOS disease.

Sex-dependent emergence of prepubertal social dysfunction and augmented dopamine activity in a neurodevelopmental rodent model relevant for schizophrenia

Schizophrenia is a neurodevelopmental psychiatric disorder that often emerges in adolescence, is characterized by social dysfunction, and has an earlier onset in men. These features have been replicated in rats exposed to the mitotoxin methylazoxymethanol acetate (MAM) on gestational day (GD) 17, which as adults exhibit behavioral impairments and dopamine (DA) system changes consistent with a schizophrenia-relevant rodent model. In humans, social withdrawal is a negative symptom that often precedes disease onset and DA system dysfunction and is more pronounced in men. Children and adolescents at high-risk for schizophrenia exhibit social deficits prior to psychotic symptoms (i.e., prodromal phase), which can be used as a predictive marker for future psychopathology. Adult MAM rats also exhibit deficient social interaction, but less is known regarding the emergence of social dysfunction in this model, whether it varies by sex, and whether it is linked to disrupted DA function. To this end, we characterized the ontogeny of social and DA dysfunction in male and female MAM rats during the prepubertal period (postnatal days 33-43) and found sex-specific changes in motivated social behaviors (play, approach) and DA function. Male MAM rats exhibited reduced social approach and increased VTA DA neuron activity compared to saline-treated (SAL) males, whereas female MAM rats exhibited enhanced play behaviors compared to SAL females but no changes in social approach or VTA population activity during this period. These findings demonstrate sex differences in the emergence of social and DA deficits in the MAM model, in which females exhibit delayed emergence.

Large-scale brain functional network abnormalities in social anxiety disorder

BACKGROUND

Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value.

METHODS

Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses.

RESULTS

SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy.

CONCLUSIONS

SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.

Electroconvulsive Therapy Reduces Protein Expression Level of EP300 and Improves Psychiatric Symptoms and Disturbance of Thought in Patients with Schizophrenia

Objective

Although electroconvulsive therapy (ECT) has been employed as an effective treatment strategy and to improve mental symptoms in schizophrenia (SCZ), its action mechanisms remain unclear. Our previous study found that some genes and biological pathways were closely related to ECT through genetic technology analysis, such as LTP pathway and EP300. This study combined with healthy controls and symptomatology analysis to further explore the changes of expression of EP300 protein in treatment and related symptoms of SCZ.

Methods

One hundred and one patients with SCZ and 45 healthy controls (HCs) were enrolled in this study. Patients with SCZ received acute courses of 6 times bilateral ECT. The peripheral blood of patients with SCZ (BECT: before ECT; AECT: after ECT) and the HCs was collected to calculate the changes of expression level of EP300 protein by enzyme-linked immunosorbent assay. The Positive and Negative Symptoms Scale (PANSS) was used to evaluate the severity of symptoms of SCZ patients and the efficiency of the ECT.

Results

There was a statistical difference of EP300 protein expression in patients with SCZ (BECT and AECT) (F = 114.5, p < 0.05). ECT reduced plasma expression level of EP300 protein in patients with SCZ, which was not statistically different from that in HCs (t = 4.47, p = 0.20). The change of the expression level of EP300 protein in patients with SCZ (BECT and AECT) has a positive correlation with reduction rate of positive symptoms (r = 0.228, p < 0.05) and disturbance of thought (r = 0.219, p < 0.05).

Conclusion

Our study suggests that the expression level of EP300 protein has a significant change in patients with SCZ treating with ECT, and EP300 may have some connections with positive symptoms and disturbance thought of patients with SCZ.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia

Background and objective

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition.

Methods

A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores.

Results

Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC).

Conclusion

Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.

Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Disrupted control of brain state transitions may contribute to the diverse dysfunctions of cognition, emotion, and behavior that are fundamental to schizophrenia. Control theory provides the rationale for evaluating brain state transitions from a controllability perspective, which may help reveal the brain mechanism for clinical features such as cognitive control deficits associated with schizophrenia. We hypothesized that brain controllability would be altered in patients with schizophrenia, and that controllability of brain networks would be related to clinical symptomatology.

STUDY DESIGN

Controllability measurements of functional brain networks, including average controllability and modal controllability, were calculated and compared between 125 first-episode never-treated patients with schizophrenia and 133 healthy controls (HCs). Associations between controllability metrics and clinical symptoms were evaluated using sparse canonical correlation analysis.

STUDY RESULTS

Compared to HCs, patients showed significantly increased average controllability (PFDR = .023) and decreased modal controllability (PFDR = .023) in dorsal anterior cingulate cortex (dACC). General psychopathology symptoms and positive symptoms were positively correlated with average controllability in regions of default mode network and negatively associated with average controllability in regions of sensorimotor, dorsal attention, and frontoparietal networks.

CONCLUSIONS

Our findings suggest that altered controllability of functional activity in dACC may play a critical role in the pathophysiology of schizophrenia, consistent with the importance of this region in cognitive and brain state control operations. The demonstration of associations of functional controllability with psychosis symptoms suggests that the identified alterations in average controllability of brain function may contribute to the severity of acute psychotic illness in schizophrenia.

Widespread Intra- and Inter-Network Dysconnectivity among Large-Scale Resting State Networks in Schizophrenia

Schizophrenia is characterized by the distributed dysconnectivity of resting-state multiple brain networks. However, the abnormalities of intra- and inter-network functional connectivity (FC) in schizophrenia and its relationship to symptoms remain unknown. The aim of the present study is to compare the intra- and inter-connectivity of the intrinsic networks between a large sample of patients with schizophrenia and healthy controls. Using the Region of interest (ROI) to ROI FC analyses, the intra- and inter-network FC of the eight resting state networks [default mode network (DMN); salience network (SN); frontoparietal network (FPN); dorsal attention network (DAN); language network (LN); visual network (VN); sensorimotor network (SMN); and cerebellar network (CN)] were investigated in 196 schizophrenia and 169-healthy controls. Compared to the healthy control group, the schizophrenia group exhibited increased intra-network FC in the DMN and decreased intra-network FC in the CN. Additionally, the schizophrenia group showed the decreased inter-network FC mainly involved the SN-DMN, SN-LN and SN-CN while increased inter-network FC in the SN-SMN and SN-DAN (p < 0.05, FDR-corrected). Our study suggests widespread intra- and inter-network dysconnectivity among large-scale RSNs in schizophrenia, mainly involving the DMN, SN and SMN, which may further contribute to the dysconnectivity hypothesis of schizophrenia.

Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia

BACKGROUND

Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks.

METHODS

We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls).

RESULTS

We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal-parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05).

CONCLUSIONS

The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory-motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

Increased structural connectivity in high schizotypy

The link between brain structural connectivity and schizotypy was explored in two healthy participant cohorts, collected at two different neuroimaging centres, comprising 140 and 115 participants, respectively. The participants completed the Schizotypal Personality Questionnaire (SPQ), through which their schizotypy scores were calculated. Diffusion-MRI data were used to perform tractography and to generate the structural brain networks of the participants. The edges of the networks were weighted with the inverse radial diffusivity. Graph theoretical metrics of the default mode, sensorimotor, visual, and auditory subnetworks were derived and their correlation coefficients with the schizotypy scores were calculated. To the best of our knowledge, this is the first time that graph theoretical measures of structural brain networks are investigated in relation to schizotypy. A positive correlation was found between the schizotypy score and the mean node degree and mean clustering coefficient of the sensorimotor and the default mode subnetworks. The nodes driving these correlations were the right postcentral gyrus, the left paracentral lobule, the right superior frontal gyrus, the left parahippocampal gyrus, and the bilateral precuneus, that is, nodes that exhibit compromised functional connectivity in schizophrenia. Implications for schizophrenia and schizotypy are discussed.

Common abnormal connectivity in first-episode and chronic schizophrenia in pre- and post-central regions: Implications for neuromodulation targeting

Schizophrenia is a neurodevelopmental disorder manifesting differing impairments at early onset and chronic disease stages. Brain imaging research suggests a core pathological region in patients with first-episode schizophrenia is Broca's area. With disease progression, alterations in thalamic connectivity becomes more prevalent. Understanding the common circuitry underlying pathology in these two groups might highlight a critical common network and novel targets for treatment. In this study, 937 subject samples were collected including patients with first-episode schizophrenia and those with chronic schizophrenia. We used hypothesis-based voxel-level functional connectivity analyses to calculate functional connectivity using the left Broca's area and thalamus as regions of interest in those with first-episode and chronic schizophrenia, respectively. We show for the first time that in both patients with first-episode and chronic schizophrenia the greatest functional connectivity disruption ended in the pre- and postcentral regions. At the early-onset stage, the core brain region is abnormally connected to pre- and postcentral areas responsible for mouth movement, while in the chronic stage, it expanded to a wider range of sensorimotor areas. Our findings suggest that expanding the focus on the low-order sensory-motor systems beyond high-order cognitive impairments in schizophrenia may show potential for neuromodulation treatment, given the relative accessibility of these cortical regions and their functional and structural connections to the core region at different stages of illness.

Youth with Down syndrome display widespread increased functional connectivity during rest

Studies of resting-state functional connectivity in young people with Down syndrome (DS) have yielded conflicting results. Some studies have found increased connectivity while others have found a mix of increased and decreased connectivity. No studies have examined whole-brain connectivity at the voxel level in youth with DS during an eyes-open resting-state design. Additionally, no studies have examined the relationship between connectivity and network selectivity in youth with DS. Thus, the current study sought to fill this gap in the literature. Nineteen youth with DS (Mage = 16.5; range 7-23; 13 F) and 33 typically developing (TD) youth (Mage = 17.5; range 6-24; 18 F), matched on age and sex, completed a 5.25-min eyes-open resting-state fMRI scan. Whole-brain functional connectivity (average Pearson correlation of each voxel with every other voxel) was calculated for each individual and compared between groups. Network selectivity was then calculated and correlated with functional connectivity for the DS group. Results revealed that whole-brain functional connectivity was significantly higher in youth with DS compared to TD controls in widespread regions throughout the brain. Additionally, participants with DS had significantly reduced network selectivity compared to TD peers, and selectivity was significantly related to connectivity in all participants. Exploratory behavioral analyses revealed that regions showing increased connectivity in DS predicted Verbal IQ, suggesting differences in connectivity may be related to verbal abilities. These results indicate that network organization is disrupted in youth with DS such that disparate networks are overly connected and less selective, suggesting a potential target for clinical interventions.

Frequency-Specific Analysis of the Dynamic Reconfiguration of the Brain in Patients with Schizophrenia

The analysis of resting-state fMRI signals usually focuses on the low-frequency range/band (0.01−0.1 Hz), which does not cover all aspects of brain activity. Studies have shown that distinct frequency bands can capture unique fluctuations in brain activity, with high-frequency signals (>0.1 Hz) providing valuable information for the diagnosis of schizophrenia. We hypothesized that it is meaningful to study the dynamic reconfiguration of schizophrenia through different frequencies. Therefore, this study used resting-state functional magnetic resonance (RS-fMRI) data from 42 schizophrenia and 40 normal controls to investigate dynamic network reconfiguration in multiple frequency bands (0.01−0.25 Hz, 0.01−0.027 Hz, 0.027−0.073 Hz, 0.073−0.198 Hz, 0.198−0.25 Hz). Based on the time-varying dynamic network constructed for each frequency band, we compared the dynamic reconfiguration of schizophrenia and normal controls by calculating the recruitment and integration. The experimental results showed that the differences between schizophrenia and normal controls are observed in the full frequency, which is more significant in slow3. In addition, as visual network, attention network, and default mode network differ a lot from each other, they can show a high degree of connectivity, which indicates that the functional network of schizophrenia is affected by the abnormal brain state in these areas. These shreds of evidence provide a new perspective and promote the current understanding of the characteristics of dynamic brain networks in schizophrenia.

Sleep as a window on the sensorimotor foundations of the developing hippocampus

The hippocampal formation plays established roles in learning, memory, and related cognitive functions. Recent findings also suggest that the hippocampus integrates sensory feedback from self-generated movements to modulate ongoing motor responses in a changing environment. Such findings support the view of Bland and Oddie (Behavioural Brain Research, 2001, 127, 119-136) that the hippocampus is a site of sensorimotor integration. In further support of this view, we review neurophysiological evidence in developing rats that hippocampal function is built on a sensorimotor foundation and that this foundation is especially evident early in development. Moreover, at those ages when the hippocampus is first establishing functional connectivity with distant sensory and motor structures, that connectivity is preferentially expressed during periods of active (or REM) sleep. These findings reinforce the notion that sleep, as the predominant state of early infancy, provides a critical context for sensorimotor development, including development of the hippocampus and its associated network.

Altered brain network in first-episode, drug-naive patients with major depressive disorder

BACKGROUND

Resting-state functional magnetic resonance imaging has been widely used for the assessment of brain functional network, yet with inconsistent results. The present study aimed to investigate intranetwork and internetwork connectivity differences between patients with major depressive disorder (MDD) and healthy controls at the integrity, network and edge levels of 8 well-defined resting state networks.

METHODS

Thirty patients with MDD and sixty-three healthy control subjects were recruited in this study.

RESULTS

Compared with healthy controls, patients with MDD showed increased node degree in the right amygdala and putamen, increased connectivity strength in the deep gray matter network (DGN) and increased functional connectivity in intranetwork and internetwork. Meanwhile, MDD showed decreased connectivity strength in visual network-DGN pair.

LIMITATIONS

The sample size was small, and all patients in this study were of Asian ethnicity, especially Han individuals.

CONCLUSIONS

These findings demonstrate that MDD cases and healthy controls may have divergent intranetwork and internetwork connectivity at an early stage without confounding influence of medication. These differences may underlie cognitive and behavioral alterations in patients with MDD. And these differences may help with the discrimination of patients and healthy people at an early stage of MDD. More studies in the future are warranted to assist in the diagnosis of this burdensome disease.

Abnormal Brain Structure Morphology in Early-Onset Schizophrenia

With less exposure to environmental and medication influences, individuals with early-onset schizophrenia (EOS) may provide valuable evidence to study the pathogenesis and phenotypic pattern of schizophrenia.T1-weighted magnetic resonance images were collected in 60 individuals with EOS and 40 healthy controls. Voxel-based morphometry and surface-based morphometry analyzes were performed. Gray matter volume, cortical thickness and cortical surface area were compared between the EOS and healthy controls and among schizophrenia subgroups (with or without family history of schizophrenia). Compared with healthy controls, the EOS group had reduced gray matter volume in the bilateral middle temporal gyrus and reduced cortical thickness in several brain regions. The sporadic early onset schizophrenia and the familial early onset schizophrenia showed different brain structure morphology. These findings suggest that abnormal brain structure morphology, especially in the temporal and frontal lobes, may be an important pathophysiological feature of EOS.

Altered topographical organization of grey matter structural network in early-onset schizophrenia

Schizophrenia is characterized by both disrupted neurodevelopmental processes and abnormal brain connectivity. However, few studies have examined the atypical features of brain network topography associated with schizophrenia during childhood and adolescence. We used graph theory to compare the grey matter structural networks of individuals (aged 10-15 years) with early-onset schizophrenia (EOS) (n = 25) and a typically-developing (TD) comparison group (n = 31). Compared with the TD group, EOS patients showed significantly increased clustering and local efficiency across a range of network densities (0.3 - 0.4). The network of EOS patients also had more modules (6 modules in EOS vs. 3 modules in controls), indicating a more segregated network at the cost of functional integration. Although our results were preliminary and failed to survive corrections for multiple comparisons, EOS patients might be characterized by altered nodal centrality in several higher-order associative regions including the prefrontal cortex, the hippocampus and the cerebellum. The EOS structural network also lacked the typical left-hemispheric-dominant hub distribution compared with the TD group. These findings suggest that brain structural network was not only globally but also regionally altered in EOS patients.

Frequency-specific altered global signal topography in drug-naïve first-episode patients with adolescent-onset schizophrenia

Adolescent-onset schizophrenia (AOS) is a severe neuropsychiatric disease associated with frequency-specific abnormalities across distributed neural systems in a slow rhythm. Recently, functional magnetic resonance imaging (fMRI) studies have determined that the global signal. (GS) is an important source of the local neuronal activity in 0.01-0.1 Hz frequency band. However, it remains unknown whether the effects follow a specific spatially preferential pattern in different frequency bands in schizophrenia. To address this issue, resting-state fMRI data from 39 drug-naïve AOS patients and 31 healthy controls (HCs) were used to assess the changes in GS topography patterns in the slow-4 (0.027-0.073 Hz) and slow-5 bands (0.01-0.027 Hz). Results revealed that GS mainly affects the default mode network (DMN) in slow-4 and sensory regions in the slow-5 band respectively, and GS has a stronger driving effect in the slow-5 band. Moreover, significant frequency-by-group interaction was observed in the frontoparietal network. Compared with HCs, patients with AOS exhibited altered GS topography mainly located in the DMN. Our findings demonstrated that the influence of the GS on brain networks altered in a frequency-specific way in schizophrenia.

Abnormality of subcortical volume and resting functional connectivity in adolescents with early-onset and prodromal schizophrenia

OBJECTIVE

Studies have found that there may be qualitative changes in brain structure and function in adolescents with early-onset schizophrenia (EOS) and prodromal schizophrenia (PDS). However, the abnormal brain structure and function of adolescents with EOS and PDS have received little attention, and their underlying neural mechanisms are still unknown.

METHODS

In this study, structural and resting-state functional magnetic resonance imaging (fMRI) were used to compare the subcortical volume and functional connectivity (FC) among EOS, PDS, and a control group. The Positive and Negative Symptom Scale (PNASS) questionnaire was used for clinical evaluation. Structural MRI was used to calculate cortical-based morphological volume and subcortical volume, and resting-state fMRI was used to analyze seed-based FC.

RESULTS

Structural MRI analyses showed that the gray matter volume of the hippocampus in EOS was significantly smaller than that in the control group, and the gray matter volume of the hippocampus, amygdala, and caudate nucleus in PDS was significantly smaller than that in the control group. Additionally, correlation analysis showed that the gray matter volume of the hippocampus was significantly negatively correlated with the negative symptom score of PANSS in EOS. When the hippocampus was used as the seed, fMRI analysis found that the FC between the hippocampus and the posterior cingulate gyrus and precuneus in EOS was significantly weaker than that in the control group.

CONCLUSION

Our results indicate that the brain structure and function are abnormal in EOS and PDS, with abnormalities mainly concentrated in the limbic system, including the hippocampus, amygdala, caudate nucleus, cingulate gyrus, and precuneus. These findings provide a new direction for early intervention and improvement of the prognosis of schizophrenic patients.

Resting-State Functional Connectivity and Psychopathology in Klinefelter Syndrome (47, XXY)

Klinefelter syndrome (47, XXY; henceforth: XXY syndrome) is a high-impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first study to map alterations of functional brain connectivity in XXY syndrome and relate these changes to brain anatomy and psychopathology. We used resting-state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males to 1) implement a brain-wide screen for altered global resting-state functional connectivity (rsFC) in XXY versus XY males and 2) decompose these alterations through seed-based analysis. We then compared these rsFC findings with measures of regional brain anatomy, psychopathology, and cognition. XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC)-reflecting DLPFC overconnectivity with diverse rsFC networks. Functional overconnectivity was partly coupled to co-occurring regional volumetric changes in XXY syndrome, and variation in DLPFC-precuneus rsFC was correlated with the severity of psychopathology. By providing the first view of altered rsFC in XXY syndrome and contextualizing observed changes relative to neuroanatomy and behavior, our study helps to advance biological understanding of XXY syndrome-both as a disorder in its own right and more broadly as a model of genetic risk for psychopathology.

Dynamic functional connectivity and its anatomical substrate reveal treatment outcome in first-episode drug-naïve schizophrenia

Convergent evidence has suggested a significant effect of antipsychotic exposure on brain structure and function in patients with schizophrenia, yet the characteristics of favorable treatment outcome remains largely unknown. In this work, we aimed to examine how large-scale brain networks are modulated by antipsychotic treatment, and whether the longitudinal changes could track the improvements of psychopathologic scores. Thirty-four patients with first-episode drug-naïve schizophrenia and 28 matched healthy controls were recruited at baseline from Shanghai Mental Health Center. After 8 weeks of antipsychotic treatment, 24 patients were re-scanned. Through a systematical dynamic functional connectivity (dFC) analysis, we investigated the schizophrenia-related intrinsic alterations of dFC at baseline, followed by a longitudinal study to examine the influence of antipsychotic treatment on these abnormalities by comparing patients at baseline and follow-up. A structural connectivity (SC) association analysis was further carried out to investigate longitudinal anatomical changes that underpin the alterations of dFC. We found a significant symptomatic improvement-related increase in the occurrence of a dFC state characterized by stronger inter-network integration. Furthermore, symptom reduction was correlated with increased FC variability in a unique connectomic signature, particularly in the connections within the default mode network and between the auditory, cognitive control, and cerebellar network to other networks. Additionally, we observed that the SC between the superior frontal gyrus and medial prefrontal cortex was decreased after treatment, suggesting a relaxation of normal constraints on dFC. Taken together, these findings provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network. Moreover, our identified neuroimaging markers tied to the neurobiology of schizophrenia could be used as potential indicators in predicting the treatment outcome of antipsychotics.

Frequency-specific alternations in the moment-to-moment BOLD signals variability in schizophrenia

Variability of neuronal activity is considered as the fundamental mechanism for the flexible and optimal brain function. Moreover, different frequency neuro signal is related to specific function. While little is currently known regarding changes in spontaneous BOLD variability of schizophrenia. The current study used resting-state fMRI data from 53 chronic schizophrenic subjects and 67 healthy subjects to investigate this issue. The data-driven method was used to measure the BOLD variability (MSSD: mean square successive difference) in two different frequency bands respectively (slow-5: 0.01-0.027 Hz; slow-4:0.027-0.073 Hz). Schizophrenic subjects exhibited decreased BOLD variability in thalamus region, sensorimotor and visual networks, and increased BOLD variability in salience network compared to matched healthy controls. Moreover, the interaction effects between frequency and group were observed in thalamus and right dorsolateral prefrontal cortex (DLPFC). These findings identified that altered BOLD variability is frequency dependent in schizophrenia. Importantly, the severity of patients' negative symptom was related to the increased BOLD variability of DLPFC within slow-4 frequency band, highlighting the evidence that abnormal BOLD variability of frontal cortex is likely to have effects on the pathophysiology of negative symptom in schizophrenia.

Enhanced inter-regional coupling of neural responses and repetition suppression provide separate contributions to long-term behavioral priming

Stimulus identification commonly improves with repetition over long delays ("repetition priming"), whereas neural activity commonly decreases ("repetition suppression"). Multiple models have been proposed to explain this brain-behavior relationship, predicting alterations in functional and/or effective connectivity (Synchrony and Predictive Coding models), in the latency of neural responses (Facilitation model), and in the relative similarity of neural representations (Sharpening model). Here, we test these predictions with fMRI during overt and covert naming of repeated and novel objects. While we find partial support for predictions of the Facilitation and Sharpening models in the left fusiform gyrus and left frontal cortex, the data were most consistent with the Synchrony model, with increased coupling between right temporoparietal and anterior cingulate cortex for repeated objects that correlated with priming magnitude across participants. Increased coupling and repetition suppression varied independently, each explaining unique variance in priming and requiring modifications of all current models.

Characterizing the theory of mind network in schizophrenia reveals a sparser network structure

Impaired social functioning is a hallmark of schizophrenia and altered functional integration between distant brain regions are expected to account for signs and symptoms of the disorder. The functional neuroarchitecture of a network relevant for social functioning, the mentalizing network, is however poorly understood. In this study we examined dysfunctions of the mentalizing network in patients with schizophrenia compared to healthy controls via dynamic causal modelling and an interactive social decision-making game. Network characteristics were analyzed on a single subject basis whereas graph theoretic metrics such as in-degree, out-degree and edge-connectivity per network node were compared between the groups. The results point to a sparser network structure in patients with schizophrenia and highlight the dorsomedial prefrontal cortex as a disconnected network hub receiving significantly less input from other brain regions in the network. Further analyses suggest that integrating pathways from the right and the left temporo-parietal junction into the dorsomedial prefrontal cortex were less frequently found in patients with schizophrenia. Brain and behavior analyses further suggest that the connectivity-intactness within the entire network is associated with functional interpersonal behavior during the task. Thus, the neurobiological alterations within the mentalizing network in patients with schizophrenia point to a specific integration deficit between core brain regions underlying the generation of higher-order representations and thereby provide a potential treatment target.

A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

Static and dynamic functional network connectivity (FNC) are typically studied separately, which makes us unable to see the full spectrum of connectivity in each analysis. Here, we propose an approach called filter-banked connectivity (FBC) to estimate connectivity while preserving its full frequency range and subsequently examine both static and dynamic connectivity in one unified approach. First, we demonstrate that FBC can estimate connectivity across multiple frequencies missed by a sliding-window approach. Next, we use FBC to estimate FNC in a resting-state fMRI dataset including schizophrenia patients (SZ) and typical controls (TC). The FBC results are clustered into different network states. Some states showed weak low-frequency strength and as such were not captured in the window-based approach. Additionally, we found that SZs tend to spend more time in states exhibiting higher frequencies compared with TCs who spent more time in lower frequency states. Finally, we show that FBC enables us to analyze static and dynamic connectivity in a unified way. In summary, FBC offers a novel way to unify static and dynamic connectivity analyses and can provide additional information about the frequency profile of connectivity patterns.

Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review

Psychotic disorders are highly debilitating and constitute a major public health burden. Identifying markers of psychosis risk and resilience is a necessary step toward understanding etiology and informing prevention and treatment efforts in individuals at clinical high risk (CHR) for psychosis. In this context, it is important to consider that neural risk markers have been particularly useful in identifying mechanistic determinants along with predicting clinical outcomes. Notably, despite a growing body of supportive literature and the promise of recent findings identifying potential neural markers, the current work on CHR resilience markers has received little attention. The present review provides a brief overview of brain-based risk markers with a focus on predicting symptom course. Next, the review turns to protective markers, examining research from nonpsychiatric and schizophrenia fields to build an understanding of framing, priorities, and potential, applying these ideas to contextualizing a small but informative body of resiliency-relevant CHR research. Four domains (neurocognition, emotion regulation, allostatic load, and sensory and sensorimotor function) were identified and are discussed in terms of behavioral and neural markers. Taken together, the literature suggests significant predictive value for brain-based markers for individuals at CHR for psychosis, and the limited but compelling resiliency work highlights the critical importance of expanding this promising area of inquiry.

Altered default mode network functional connectivity in individuals with co-occurrence of schizotypy and obsessive-compulsive traits

In this study, we examined differences in resting-state functional connectivity between sub-regions of the Default Mode Network (DMN) and whole brain voxels in 22 individuals with high schizo-obsessive traits (SOT), 30 with high schizotypal traits (SCT) alone, 20 with high obsessive-compulsive traits (OCT) alone and 30 with low trait scores (LT). We found that the SOT group showed the most reduced functional connectivity within the DMN compared with the other groups. The SOT group also showed increased connectivity between the DMN and the Salience Network, and between the DMN and the Auditory Network compared with the LT group. The SCT group exhibited increased connectivity between the DMN and the Salience Network, and between the DMN and the Executive Control Network (ECN) compared with the LT group. The OCT group exhibited decreased connectivity within the DMN, between the DMN and the Salience Network, and between the DMN and the ECN compared with the LT group. These findings highlight different changes in DMN-related functional connectivity associated with high SOT, SCT and OCT traits and may provide insight into the dysfunctional brain networks in the early stage of schizophrenia spectrum disorders.

Neurological Soft Signs Predict Auditory Verbal Hallucinations in Patients With Schizophrenia

Neurological soft signs (NSS) are well documented in individuals with schizophrenia (SZ), yet so far, the relationship between NSS and specific symptom expression is unclear. We studied 76 SZ patients using magnetic resonance imaging (MRI) to determine associations between NSS, positive symptoms, gray matter volume (GMV), and neural activity at rest. SZ patients were hypothesis-driven stratified according to the presence or absence of auditory verbal hallucinations (AVH; n = 34 without vs 42 with AVH) according to the Brief Psychiatric Rating Scale. Structural MRI data were analyzed using voxel-based morphometry, whereas intrinsic neural activity was investigated using regional homogeneity (ReHo) measures. Using ANCOVA, AVH patients showed significantly higher NSS in motor and integrative functions (IF) compared with non-hallucinating (nAVH) patients. Partial correlation revealed that NSS IF were positively associated with AVH symptom severity in AVH patients. Such associations were not confirmed for delusions. In region-of-interest ANCOVAs comprising the left middle and superior temporal gyri, right paracentral lobule, and right inferior parietal lobule (IPL) structure and function, significant differences between AVH and nAVH subgroups were not detected. In a binary logistic regression model, IF scores and right IPL ReHo were significant predictors of AVH. These data suggest significant interrelationships between sensorimotor integration abilities, brain structure and function, and AVH symptom expression.

Cognitive remediation and brain connectivity: A resting-state fMRI study in patients with schizophrenia

Cognitive remediation is able to improve activation patterns in the frontal lobe but only few data on neuroconnectivity has been reported yet. Resting-state approach is a neuroimaging methodology with potentiality for testing neuroconnectivity in the context of cognitive remediation in schizophrenia. A resting-state fMRI data was acquired in part of the sample (n = 26 patients, n = 10 healthy controls) of a partner study (NCT02341131) testing the effects of cognitive remediation. A data-driven approach using independent component analysis (ICA) was used to identify functional brain networks, which were compared between groups and group per time using a dual-regression approach. ICA results revealed reduced functional connectivity between patients and controls in sensorimotor, basal ganglia, default mode and visual networks at baseline (p<0.05 FWE-corrected). After treatment, time per group analyses evidenced increased connectivity in sensorimotor network. Furthermore, group comparison at follow-up showed similar connectivity patterns between patients and healthy controls in sensorimotor network, but also in default mode and basal ganglia networks. No differences between treatment groups were found. Our results add some evidence to the hypothesis of altered connectivity in schizophrenia, and the possibility to modify some aspects of brain connectivity networks after psychological interventions.

Compression of Cerebellar Functional Gradients in Schizophrenia

Our understanding of cerebellar involvement in brain disorders has evolved from motor processing to high-level cognitive and affective processing. Recent neuroscience progress has highlighted hierarchy as a fundamental principle for the brain organization. Despite substantial research on cerebellar dysfunction in schizophrenia, there is a need to establish a neurobiological framework to better understand the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellum in schizophrenia. To help to establish such a framework, we investigated the abnormalities in the distribution of sensorimotor-supramodal hierarchical processing topography in the cerebellum and cerebellar-cerebral circuits in schizophrenia using a novel gradient-based resting-state functional connectivity (FC) analysis (96 patients with schizophrenia vs 120 healthy controls). We found schizophrenia patients showed a compression of the principal motor-to-supramodal gradient. Specifically, there were increased gradient values in sensorimotor regions and decreased gradient values in supramodal regions, resulting in a shorter distance (compression) between the sensorimotor and supramodal poles of this gradient. This pattern was observed in intra-cerebellar, cerebellar-cerebral, and cerebral-cerebellar FC. Further investigation revealed hyper-connectivity between sensorimotor and cognition areas within cerebellum, between cerebellar sensorimotor and cerebral cognition areas, and between cerebellar cognition and cerebral sensorimotor areas, possibly contributing to the observed compressed pattern. These findings present a novel mechanism that may underlie the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellar and cerebro-cerebellar circuits in schizophrenia. Within this framework of abnormal motor-to-supramodal organization, a cascade of impairments stemming from disrupted low-level sensorimotor system may in part account for high-level cognitive cerebellar dysfunction in schizophrenia.

Altered functional connectivity during speech perception in congenital amusia

Individuals with congenital amusia have a lifelong history of unreliable pitch processing. Accordingly, they downweight pitch cues during speech perception and instead rely on other dimensions such as duration. We investigated the neural basis for this strategy. During fMRI, individuals with amusia (N = 15) and controls (N = 15) read sentences where a comma indicated a grammatical phrase boundary. They then heard two sentences spoken that differed only in pitch and/or duration cues and selected the best match for the written sentence. Prominent reductions in functional connectivity were detected in the amusia group between left prefrontal language-related regions and right hemisphere pitch-related regions, which reflected the between-group differences in cue weights in the same groups of listeners. Connectivity differences between these regions were not present during a control task. Our results indicate that the reliability of perceptual dimensions is linked with functional connectivity between frontal and perceptual regions and suggest a compensatory mechanism.

Reconfiguration of Dynamic Functional Connectivity in Sensory and Perceptual System in Schizophrenia

Schizophrenia is thought as a self-disorder with dysfunctional brain connectivity. This self-disorder is often attributed to high-order cognitive impairment. Yet due to the frequent report of sensorial and perceptual deficits, it has been hypothesized that self-disorder in schizophrenia is dysfunctional communication between sensory and cognitive processes. To further verify this assumption, the present study comprehensively examined dynamic reconfigurations of resting-state functional connectivity (rsFC) in schizophrenia at voxel level, region level, and network levels (102 patients vs. 124 controls). We found patients who show consistently increased rsFC variability in sensory and perceptual system, including visual network, sensorimotor network, attention network, and thalamus at all the three levels. However, decreased variability in high-order networks, such as default mode network and frontal-parietal network were only consistently observed at region and network levels. Taken together, these findings highlighted the rudimentary role of elevated instability of information communication in sensory and perceptual system and attenuated whole-brain integration of high-order network in schizophrenia, which provided novel neural evidence to support the hypothesis of disrupted perceptual and cognitive function in schizophrenia. The foci of effects also highlighted that targeting perceptual deficits can be regarded as the key to enhance our understanding of pathophysiology in schizophrenia and promote new treatment intervention.

Transdiagnostic Dysfunctions in Brain Modules Across Patients with Schizophrenia, Bipolar Disorder, and Major Depressive Disorder: A Connectome-Based Study

Psychiatric disorders, including schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), share clinical and neurobiological features. Because previous investigations of functional dysconnectivity have mainly focused on single disorders, the transdiagnostic alterations in the functional connectome architecture of the brain remain poorly understood. We collected resting-state functional magnetic resonance imaging data from 512 participants, including 121 with SCZ, 100 with BD, 108 with MDD, and 183 healthy controls. Individual functional brain connectomes were constructed in a voxelwise manner, and the modular architectures were examined at different scales, including (1) global modularity, (2) module-specific segregation and intra- and intermodular connections, and (3) nodal participation coefficients. The correlation of these modular measures with clinical scores was also examined. We reliably identify common alterations in modular organization in patients compared to controls, including (1) lower global modularity; (2) lower modular segregation in the frontoparietal, subcortical, visual, and sensorimotor modules driven by more intermodular connections; and (3) higher participation coefficients in several network connectors (the dorsolateral prefrontal cortex and angular gyrus) and the thalamus. Furthermore, the alterations in the SCZ group are more widespread than those of the BD and MDD groups and involve more intermodular connections, lower modular segregation and higher connector integrity. These alterations in modular organization significantly correlate with clinical scores in patients. This study demonstrates common hyper-integrated modular architectures of functional brain networks among patients with SCZ, BD, and MDD. These findings reveal a transdiagnostic mechanism of network dysfunction across psychiatric disorders from a connectomic perspective.

Cerebellar-cortical dysconnectivity in resting-state associated with sensorimotor tasks in schizophrenia

Abnormalities of cerebellar function have been implicated in the pathophysiology of schizophrenia. Since the cerebellum has afferent and efferent projections to diverse brain regions, abnormalities in cerebellar lobules could affect functional connectivity with multiple functional systems in the brain. Prior studies, however, have not examined the relationship of individual cerebellar lobules with motor and nonmotor resting‐state functional networks. We evaluated these relationships using resting‐state fMRI in 30 patients with a schizophrenia‐spectrum disorder and 37 healthy comparison participants. For connectivity analyses, the cerebellum was parcellated into 18 lobular and vermal regions, and functional connectivity of each lobule to 10 major functional networks in the cerebrum was evaluated. The relationship between functional connectivity measures and behavioral performance on sensorimotor tasks (i.e., finger‐tapping and postural sway) was also examined. We found cerebellar–cortical hyperconnectivity in schizophrenia, which was predominantly associated with Crus I, Crus II, lobule IX, and lobule X. Specifically, abnormal cerebellar connectivity was found to the cerebral ventral attention, motor, and auditory networks. This cerebellar–cortical connectivity in the resting‐state was differentially associated with sensorimotor task‐based behavioral measures in schizophrenia and healthy comparison participants—that is, dissociation with motor network and association with nonmotor network in schizophrenia. These findings suggest that functional association between individual cerebellar lobules and the ventral attentional, motor, and auditory networks is particularly affected in schizophrenia. They are also consistent with dysconnectivity models of schizophrenia suggesting cerebellar contributions to a broad range of sensorimotor and cognitive operations.

Abnormal amygdala subregional-sensorimotor connectivity correlates with positive symptom in schizophrenia

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Functional connectivity between amygdala subregions and the brain was studied with resting-state (RS) functional MRI.

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RS functional connectivity was compared between patients with first episode schizophrenia (FES) and healthy controls.

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FES patients showed changes in functional connectivity between amygdala subregions and sensorimotor cortex.

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Altered basolateral amygdala-precentral gyrus connectivity correlated with positive symptoms in FES patients.

Altered resting-state functional connectivity (rsFC) of the amygdala has been demonstrated to be implicated in schizophrenia neuronal pathophysiology. However, whether rsFC of amygdala subregions is differentially affected in schizophrenia remains unclear. This study compared the functional networks of each amygdala subdivision between healthy controls (HC) and patients with first-episode schizophrenia (FES). In total, 47 HC and 78 patients with FES underwent resting-state functional magnetic resonance imaging. The amygdala was divided into the following three subregions using the Juelich histological atlas: basolateral amygdala (BLA), centromedial amygdala (CMA), and superficial amygdala (SFA). The rsFC of the three amygdala subdivisions was computed and compared between the two groups. Significantly increased rsFC of the right CMA with the right postcentral gyrus and decreased rsFC of the right BLA with the left precentral gyrus were observed in the FES group compared with the HC group. Notably, the right BLA-left precentral gyrus connectivity was negatively correlated with positive symptoms and conceptual disorganization in patients with FES. In conclusion, this study found that patients with FES had abnormal functional connectivity in the amygdala subregions, and the altered rsFC was associated with positive symptoms. The present findings demonstrate the disruptive rsFC patterns of amygdala subregional-sensorimotor networks in FES and may provide new insights into the neuronal pathophysiology of FES.