Aberrant default mode functional connectivity in early onset schizophrenia

Cortical volume alterations in the limbic network in adolescents with high reactive aggression

Previous studies show aggression-related structural alterations in frontal and limbic brain regions. Most studies have focused on overall aggression, instead of its subtypes, and on specific regions instead of networks. This study aims to identify both brain networks and regions that are associated with reactive and proactive subtypes of aggression. Structural MRI data were collected from 340 adolescents (125 F/215 M) with a mean age of 16.29 (SD = 1.20). Aggression symptomology was indexed via the Reactive Proactive Aggression Questionnaire (RPQ). Freesurfer was used to estimate Cortical Volume (CV) from seven networks and regions within specific networks associated with aggression. Two multivariate analyses of covariance (MANCOVAs) were conducted on groups for low versus higher reactive and proactive RPQ scores. Our reactive aggression MANCOVA showed a main effect in CV [F(14,321) = 1.935, p = 0.022,ηp2 = 0.078] across all the 7-Networks. Unpacking this main effect revealed significant volumetric differences in the right Limbic Network (LN) (p = 0.029) and the Temporal Pole (p = 0.011), where adolescents in the higher reactive aggression group showed higher cortical volumes. Such findings are consistent with region/voxel-specific analyses that have associated atypical structure within the LN and reactive aggression. Moreover, the temporal pole is highly interconnected with regions important in the regulation and initiation of reactive aggression.

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.

Evaluation of functional MRI-based human brain parcellation: a review

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Cognitive control inhibition networks in adulthood are impaired by early iron deficiency in infancy

Iron deficiency, a common form of micronutrient deficiency, primarily affects children and women. The principal cause of iron deficiency is undernutrition in low-income countries and malnutrition in middle to upper income regions. Iron is a key element for myelin production, neuronal metabolism, and dopamine functions. Iron deficiency in early life can alter brain development and exert long-lasting effects. Control inhibition is an executive function that involves several brain regions, including the prefrontal cortex and caudate and sub-thalamic nuclei. Dopamine is the prevalent neurotransmitter underlying cognitive inhibition. We followed cohort study participants who had iron deficiency anemia in infancy as well non-anemic controls. At 22 years of age, the participants were subjected to functional magnetic resonance imaging (fMRI) to evaluate the correlation between functional connectivity and performance on an inhibitory cognitive task (Go/No-Go). We hypothesized that former iron deficient anemic (FIDA) participants demonstrate less strength in functional connectivity compared with controls (C). There were not significant group differences in the behavioral results in terms of accuracy and response time. A continuous covariate interaction analysis of functional connectivity and the Go/No-Go scores demonstrated significant differences between the FIDA and C groups. The FIDA participants demonstrated less strength in connectivity in brain regions related to control inhibition, including the medial temporal lobe, impairment in the integration of the default mode network (indicating decreased attention and alertness), and an increase in connectivity in posterior brain areas, all of which suggest slower circuitry maturation. The results support the hypothesis that FIDA young adults show differences in the connectivity of networks related to executive functions. These differences could increase their vulnerability to develop cognitive dysfunctions or mental disorders in adulthood.

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

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

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.

Inflammation is correlated with abnormal functional connectivity in unmedicated bipolar depression: an independent component analysis study of resting-state fMRI

BACKGROUND

Inflammation might play a role in bipolar disorder (BD), but it remains unclear the relationship between inflammation and brain structural and functional abnormalities in patients with BD. In this study, we focused on the alterations of functional connectivity (FC), peripheral pro-inflammatory cytokines and their correlations to investigate the role of inflammation in FC in BD depression.

METHODS

In this study, 42 unmedicated patients with BD II depression and 62 healthy controls (HCs) were enrolled. Resting-state-functional magnetic resonance imaging was performed in all participants and independent component analysis was used. Serum levels of Interleukin-6 (IL-6) and Interleukin-8 (IL-8) were measured in all participants. Correlation between FC values and IL-6 and IL-8 levels in BD was calculated.

RESULTS

Compared with the HCs, BD II patients showed decreased FC in the left orbitofrontal cortex (OFC) implicating the limbic network and the right precentral gyrus implicating the somatomotor network. BD II showed increased IL-6 (p = 0.039), IL-8 (p = 0.002) levels. Moreover, abnormal FC in the right precentral gyrus were inversely correlated with the IL-8 (r = -0.458, p = 0.004) levels in BD II. No significant correlation was found between FC in the left OFC and cytokines levels.

CONCLUSIONS

Our findings that serum IL-8 levels are associated with impaired FC in the right precentral gyrus in BD II patients suggest that inflammation might play a crucial role in brain functional abnormalities in BD.

Individual-specific functional connectome biomarkers predict schizophrenia positive symptoms during adolescent brain maturation

Even with an overarching functional dysconnectivity model of adolescent-onset schizophrenia (AOS), there have been no functional connectome (FC) biomarkers identified for predicting patients' specific symptom domains. Adolescence is a period of dramatic brain maturation, with substantial interindividual variability in brain anatomy. However, existing group-level hypotheses of AOS lack precision in terms of neuroanatomical boundaries. This study aimed to identify individual-specific FC biomarkers associated with schizophrenic symptom manifestation during adolescent brain maturation. We used a reliable individual-level cortical parcellation approach to map functional brain regions in each subject, that were then used to identify FC biomarkers for predicting dimension-specific psychotic symptoms in 30 antipsychotic-naïve first-episode AOS patients (recruited sample of 39). Age-related changes in biomarker expression were compared between these patients and 31 healthy controls. Moreover, 29 antipsychotic-naïve first-episode AOS patients (analyzed sample of 25) were recruited from another center to test the generalizability of the prediction model. Individual-specific FC biomarkers could significantly and better predict AOS positive-dimension symptoms with a relatively stronger generalizability than at the group level. Specifically, positive symptom domains were estimated based on connections between the frontoparietal control network (FPN) and salience network and within FPN. Consistent with the neurodevelopmental hypothesis of schizophrenia, the FPN-SN connection exhibited aberrant age-associated alteration in AOS. The individual-level findings reveal reproducible FPN-based FC biomarkers associated with AOS positive symptom domains, and highlight the importance of accounting for individual variation in the study of adolescent-onset disorders.

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.

Dynamic Alterations of Amplitude of Low-Frequency Fluctuations in Patients With Drug-Naïve First-Episode Early Onset Schizophrenia

Abnormalities in static neural activity have been widely reported in early onset schizophrenia (EOS). However, dynamic brain activity alterations over time in EOS are unclear. Here, we investigated whether temporal dynamic changes in spontaneous neural activity are influenced by EOS. A total of 78 drug-naïve first-episode patients with EOS and 90 healthy controls (HCs) were enrolled in this study. Dynamic amplitude of low-frequency fluctuations (dALFF) was performed to examine the abnormal time-varying local neural activity in EOS. Furthermore, we investigated the relationships between abnormalities in dALFF variability and clinical characteristics in EOS patients. Compared to HCs, EOS patients showed significantly decreased dALFF variability in the bilateral precuneus, right superior marginal gyrus, right post-central gyrus and increased dALFF in the right middle temporal gyrus (MTG). Moreover, increased dALFF variability in MTG was negatively associated with negative symptoms in EOS. Our findings reveal increased dynamic local neural activity in higher order networks of the cortex, suggesting that enhanced spontaneous brain activity may be a predominant neural marker for brain maturation. In addition, decreased dALFF variability in the default mode network (DMN) and limbic system may reflect unusually dynamic neural activity. This dysfunctional brain activity could distinguish between patients and HCs and deepen our understanding of the pathophysiological mechanisms of EOS.

Heterogeneity of Outcomes and Network Connectivity in Early-Stage Psychosis: A Longitudinal Study

Imaging studies in psychotic disorders typically examine cross-sectional relationships between magnetic resonance imaging (MRI) signals and diagnosis or symptoms. We sought to examine changes in network connectivity identified using resting-state functional MRI (fMRI) corresponding to divergent functional recovery trajectories and relapse in early-stage psychosis (ESP). Prior studies have linked schizophrenia to hyperconnectivity in the default mode network (DMN). Given the correlations between the DMN and behavioral impairments in psychosis, we hypothesized that dynamic changes in DMN connectivity reflect the heterogeneity of outcomes in ESP. Longitudinal data were collected from 66 ESP patients and 20 healthy controls. Longitudinal cluster analysis identified subgroups of patients with similar trajectories in terms of symptom severity and functional outcomes. DMN connectivity was measured in a subset of patients (n = 36) longitudinally over 2 scans separated by a mean of 12 months. We then compared connectivity between patients and controls, and among the different outcome trajectory subgroups. Among ESP participants, 4 subgroups were empirically identified corresponding to: "Poor," "Middle," "Catch-up," and "Good" trajectory outcomes in the complete dataset (n = 36), and an independent replication (n = 30). DMN connectivity changes differed significantly between functional subgroups (F3,32 = 6.06, P-FDR corrected = .01); DMN connectivity increased over time in the "Poor" outcome cluster (β = +0.145) but decreased over time in the "Catch-up" cluster (β = -0.212). DMN connectivity is dynamic and correlates with a change in functional status over time in ESP. This approach identifies a brain-based marker that reflects important neurobiological processes required to sustain functional recovery.

Clustering of Brain Function Network Based on Attribute and Structural Information and Its Application in Brain Diseases

At present, the diagnosis of brain disease is mainly based on the self-reported symptoms and clinical signs of the patient, which can easily lead to psychiatrists' bias. The purpose of this study is to develop a brain network clustering model to accurately identify brain diseases based on resting state functional magnetic resonance imaging (fMRI) in the absence of clinical information. We use cosine similarity and sub-network kernels to measure attribute similarity and structure similarity, respectively. By integrating the structure similarity and attribute similarity into one matrix, spectral clustering is used to achieve brain network clustering. Finally, we evaluate this method on three diseases: Alzheimer's disease, Bipolar disorder patients, and Schizophrenia. The performance of methods is evaluated by measuring clustering consistency. Clustering consistency is similar to clustering accuracy, which is used to evaluate the consistency between the clustering labels and clinical diagnostic labels of the subjects. The experimental results show that our proposed method can significantly improve clustering performance, with a consistency of 60.6% for Alzheimer's disease, with a consistency of 100% for Schizophrenia, with a consistency of 100% for Bipolar disorder patients.

State-Dependent Functional Dysconnectivity in Youth With Psychosis Spectrum Symptoms

Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8-22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.

A Review of Default Mode Network Connectivity and Its Association With Social Cognition in Adolescents With Autism Spectrum Disorder and Early-Onset Psychosis

Recent studies have demonstrated substantial phenotypic overlap, notably social impairment, between autism spectrum disorder (ASD) and schizophrenia. However, the neural mechanisms underlying the pathogenesis of social impairments across these distinct neuropsychiatric disorders has not yet been fully examined. Most neuroimaging studies to date have focused on adults with these disorders, with little known about the neural underpinnings of social impairments in younger populations. Here, we present a narrative review of the literature available through April 2020 on imaging studies of adolescents with either ASD or early-onset psychosis (EOP), to better understand the shared and unique neural mechanisms of social difficulties across diagnosis from a developmental framework. We specifically focus on functional connectivity studies of the default mode network (DMN), as the most extensively studied brain network relevant to social cognition across both groups. Our review included 29 studies of DMN connectivity in adolescents with ASD (Mean age range = 11.2-21.6 years), and 14 studies in adolescents with EOP (Mean age range = 14.2-24.3 years). Of these, 15 of 29 studies in ASD adolescents found predominant underconnectivity when examining DMN connectivity. In contrast, findings were mixed in adolescents with EOP, with five of 14 studies reporting DMN underconnectivity, and an additional six of 14 studies reporting both under- and over-connectivity of the DMN. Specifically, intra-DMN networks were more frequently underconnected in ASD, but overconnected in EOP. On the other hand, inter-DMN connectivity patterns were mixed (both under- and over-connected) for each group, especially DMN connectivity with frontal, sensorimotor, and temporoparietal regions in ASD, and with frontal, temporal, subcortical, and cerebellar regions in EOP. Finally, disrupted DMN connectivity appeared to be associated with social impairments in both groups, less so with other features distinct to each condition, such as repetitive behaviors/restricted interests in ASD and hallucinations/delusions in EOP. Further studies on demographically well-matched groups of adolescents with each of these conditions are needed to systematically explore additional contributing factors in DMN connectivity patterns such as clinical heterogeneity, pubertal development, and medication effects that would better inform treatment targets and facilitate prediction of outcomes in the context of these developmental neuropsychiatric conditions.

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed within-site and between-site generalizability of a machine learning classification framework which achieved excellent performance in a previous study using two independent resting-state functional magnetic resonance imaging data sets collected from different sites and scanners. We established within-site generalizability of the classification framework in the main data set using cross-validation. Then, we trained a model in the main data set and investigated between-site generalization in the validated data set using external validation. Finally, recognizing the poor between-site generalization performance, we updated the unsupervised algorithm to investigate if transfer learning using additional unlabeled data were able to improve between-site classification performance. Cross-validation showed that the published classification procedure achieved an accuracy of 0.73 using majority voting across all selected components. External validation found a classification accuracy of 0.55 (not significant) and 0.70 (significant) using the direct and transfer learning procedures, respectively. The failure of direct generalization from one site to another demonstrates the limitation of within-site cross-validation and points toward the need to incorporate efforts to facilitate application of machine learning across multiple data sets. The improvement in performance with transfer learning highlights the importance of taking into account the properties of data when constructing predictive models across samples and sites. Our findings suggest that machine learning classification result based on a single study should be interpreted cautiously.

Abnormal default-mode network homogeneity and its correlations with neurocognitive deficits in drug-naive first-episode adolescent-onset schizophrenia

The default mode network (DMN), is one of the most popularly employed resting-state networks applied in schizophrenia (SCZ) research. However, the homogeneity of this network in adolescent-onset SCZ (AOS) remains unknown. This study aims to use network homogeneity (NH) to explore the functional connectivity in the DMN of AOS patients. Resting-state functional magnetic resonance imaging scans were used to study 48 drug-naïve, first-episode AOS patients and 31 healthy age, gender, and education matched control. An automatic NH approach was employed to analyze the imaging dataset. Our results revealed that the patients had significantly higher NH values in the left medial prefrontal cortex (MPFC), and significantly lower values in the bilateral posterior cingulate cortex/precuneus (PCC/PCu) than those in healthy controls. We performed the receiver operating characteristic curve analysis to show that NH values of the left superior MPFC might be regarded as a potential marker in helping to identify patients. In addition, negative associations were found regarding abnormal values of NH in the left PCC/PCu as well as in the Maze and Stroop color-word tests in patients. The outcomes showed abnormal NH values in the DMN of drug-naïve, first-episode AOS suggesting specific functions of the DMN in the pathophysiology of SCZ.

Instrumental rationality and suicide in schizophrenia: a case for rational suicide?

It is estimated that up to 7500 people develop schizophrenia each year in the UK. Schizophrenia has significant consequences, with 28% of the excess mortality in schizophrenia being attributed to suicide. Previous research suggests that suicide in schizophrenia may be more related to affective factors such as depression and hopelessness, rather than psychotic symptoms themselves. Considering suicide in schizophrenia within this framework enables us to develop a novel philosophical approach, in which suicide may not be related to loss of self-consciousness, thought processing dysfunctions or perception disturbances. The action of suicide may be due neither to persistent hallucinations nor other psychotic symptoms, such as delusional beliefs, but to other underexamined, perhaps rational reasons, such as extreme social isolation, severe depression or emotional withdrawal. This paper does not examine the moral character of suicide. Instead, it argues that we should conceive the action of suicide in schizophrenia as an act that is not necessarily irrational. People with schizophrenia might end their life based on reasons if suicide is the best means to achieve their ends. However, the paper does not support assisted suicide. It aims to provide a better understanding of the reasons why people take their own lives and suggests that understanding can inform effective interventions to reduce high rates of suicide.

The relationship between performance in a theory of mind task and intrinsic functional connectivity in youth with early onset psychosis

Psychotic disorders are characterized by theory of mind (ToM) impairment. Although ToM undergoes maturational changes throughout adolescence, there is a lack of studies examining ToM performance and its brain functional correlates in individuals with an early onset of psychosis (EOP; onset prior to age 18), and its relationship with age. Twenty-seven individuals with EOP were compared with 41 healthy volunteers using the "Reading-the-Mind-in-the-Eyes" Test, as a measure of ToM performance. A resting-state functional MRI scan was also acquired, in which the default mode network was used to identify areas relevant to ToM processing employing independent component analysis. Group effects revealed worse ToM performance and less intrinsic functional connectivity in the medial prefrontal cortex in EOP relative to healthy volunteers. Group by age interaction revealed age-positive associations in ToM task performance and in intrinsic connectivity in the medial prefrontal cortex in healthy volunteers, which were not present in EOP. Differences in ToM performance were partially mediated by intrinsic functional connectivity in the medial prefrontal cortex. Poorer ToM performance in EOP, coupled with less medial prefrontal cortex connectivity, could be associated with the impact of psychosis during a critical period of development of the social brain, limiting normative age-related maturation.

Altered Functional Connectivity of the Default Mode Network in Patients With Schizo-obsessive Comorbidity: A Comparison Between Schizophrenia and Obsessive-compulsive Disorder

Clinical and neuroimaging data support the idea that schizo-obsessive comorbidity (SOC), similar to obsessive-compulsive disorder (OCD) and schizophrenia (SCZ), may be a distinct brain disorder. In this study, we examined the strength of resting-state functional connectivity (rsFC) between 19 subregions of the default mode network (DMN) and whole brain voxels in 22 patients with SOC features, 20 patients with SCZ alone, 22 patients with OCD, and 22 healthy controls (HC). The main results demonstrated that patients with SOC exhibited the highest rsFC strength within subregions of the DMN and the lowest rsFC strength between the DMN and subregions of the salience network (SN) compared with the other 3 groups. In addition, compared with HCs, all 3 patient groups exhibited increased rsFC between subregions of the DMN and the executive control network (ECN). The SOC and SCZ group both exhibited increased rsFC between subregions of the DMN and the middle temporal gyrus, but the OCD group exhibited decreased rsFC between them. These findings highlight a specific alteration in functional connectivity in the DMN in patients with SOC, and provide new insights into the dysfunctional brain organization of different mental disorders.

Cerebellar abnormalities in first-episode, drug-naive schizophrenia at rest

The cerebellum plays a crucial role in higher cortical functions through a cerebellar-cerebral circuit. However, the specific mechanisms through which the cerebellum contributes to the neurobiology of schizophrenia remain unclear. Forty-nine first-episode, drug-naive patients with schizophrenia and 50 healthy controls underwent structural and resting-state functional magnetic resonance imaging (rs-fMRI). The MRI data were analyzed using voxel-based morphometry, amplitude of low-frequency fluctuations (ALFF), cerebellum homogeneity (CH), and seed-based functional connectivity (FC). Patients with schizophrenia did not have anatomical and CH alterations in the cerebellum compared with healthy controls. However, they exhibited decreased ALFF in the right Crus I and abnormal cerebellar FC with brain regions within the dorsal attention network, default-mode network, and ventral attention network. The findings indicate that cerebellar abnormalities in first-episode schizophrenia are mainly in the cerebellar-cerebral connectivities, which may contribute to the neurobiology of schizophrenia.

Abnormal neural activity as a potential biomarker for drug-naive first-episode adolescent-onset schizophrenia with coherence regional homogeneity and support vector machine analyses

BACKGROUND

Patients with adolescent-onset schizophrenia (AOS) hold the same but severe form of symptoms with adult-onset schizophrenia, and with worse outcome and poor treatment response to antipsychotics. Several dominant brain regions of schizophrenia patients show significantly abnormal structural and functional connectivity during resting-state scans. However, coherence regional homogeneity (Cohe-ReHo) in drug-naive first-episode patients with AOS remains unclear.

METHOD

A total of 48 drug-naive first-episode AOS outpatients and 31 healthy controls underwent resting-state functional magnetic resonance scans. Cohe-ReHo and support vector machine analyses were used to analyze the data.

RESULTS

Compared with the healthy controls, the AOS group showed significantly decreased Cohe-ReHo values distributed over brain regions, including the left postcentral gyrus, left superior temporal gyrus, left paracentral lobule, right precentral gyrus, right inferior parietal lobule (IPL), right middle frontal gyrus, and bilateral precuneus. No region with increased Cohe-ReHo values was observed in the AOS group compared with healthy controls. In addition, the right IPL was correlated with fluency (r=-0.324, p=0.030). However, the correlation was not significant after the Bonferroni correction at p<0.0083 (0.05/6). A combination of the Cohe-ReHo values in the bilateral precuneus and right IPL discriminated the patients from controls with the sensitivity, specificity, and accuracy of 91.67%, 87.10%, and 89.87%, respectively.

CONCLUSION

Our findings suggested that the AOS patients exhibited diminished Cohe-ReHo values in some regions within the DMN network and sensorimotor network. The abnormalities in particular brain regions (bilateral precuneus and right IPL) may serve as potential biomarkers for AOS.

Altered resting state functional connectivity in early course schizophrenia

Impaired connectivity is proposed to underlie pathophysiology of schizophrenia. Existing studies on functional connectivity show inconsistent results. We examined functional connectivity in a clinically homogenous sample of 34 early course schizophrenia patients compared with/to 19 healthy controls using resting state functional magnetic resonance imaging (rsfMRI). Mean duration of illness for schizophrenia patients was 4 ± 1.78 years. Following a comprehensive clinical assessment, rsfMRI data were acquired using a 3.0 T magnetic resonance imaging scanner, and analyzed using FSL version 5.01 software (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Compared to healthy controls, schizophrenia patients had significantly decreased functional connectivity in the left fronto-parietal network, lateral and medial visual network, motor network, default mode network and auditory network. Our data suggests significant functional hypoconnectivity in selected brain networks in early schizophrenia patients compared to controls. It is likely that the observed functional hypoconnectivity may be associated with features of schizophrenia other than those examined in this study. It is possible that hypoconnectivity is necessary but not sufficient to the clinical manifestation of schizophrenia. The examination of functional connectivity as a biomarker should be extended to a wider array of disease phenotypes to better understand its significance.

Frequency-specific alteration of functional connectivity density in antipsychotic-naive adolescents with early-onset schizophrenia

Early-onset schizophrenia (EOS) is a severe mental illness associated with dysconnectivity that widespread in the brain. However, the functional dysconnectivity in EOS are still mixed. Recently, studies have identified that functional connectivity (FC) arises from a band-limited slow rhythmic mechanism and suggested that the dysconnectivity at specific frequency bands may provide more robust biomarkers for schizophrenia. The frequency-specific changes of FC pattern in EOS remain unclear. To address this issue, resting-state functional magnetic resonance imaging data scans from 39 EOS patients (drug-naive) and 31 healthy controls (HCs) were used to assess the FC density (FCD) across slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz). Results revealed that a remarkable difference between the FCD of the two bands existed mainly in the default mode network (DMN) and subcortical areas. Compared with the HCs, EOS patients showed significantly altered FCD involved in audiovisual information processing, sensorimotor system, and social cognition. Importantly, a significant frequency-by-group interaction was observed in the left precuneus with significantly lower FCD in the slow-4 frequency band, but no significant effect in the slow-5 frequency band. In addition, decreased FC was found between the precuneus and other DMN regions in the slow-4 band. Furthermore, the change in FCD in precuneus was inversely proportional to the clinical symptom in slow-4 band, indicating the key role of precuneus in schizophrenia progress. Our findings demonstrated that the dysconnectivity pattern in EOS could be frequency-dependent.

Decreased Resting-State Interhemispheric Functional Connectivity Correlated with Neurocognitive Deficits in Drug-Naive First-Episode Adolescent-Onset Schizophrenia

BACKGROUND

Given that adolescence is a critical epoch in the onset of schizophrenia, studying aberrant brain changes in adolescent-onset schizophrenia, particularly in patients with drug-naive first-episode schizophrenia, is important to understand the biological mechanism of this disorder. Previous resting-state functional magnetic resonance imaging studies have shown abnormal functional connectivity in separate hemispheres in patients with adult-onset schizophrenia. Our aim to study adolescent-onset schizophrenia can provide clues for the early aetiology of schizophrenia.

METHOD

A total of 48 drug-naïve, first-episode, adolescent-onset schizophrenia outpatients and 31 healthy controls underwent resting-state functional magnetic resonance imaging scans. Data were subjected to voxel-mirrored homotopic connectivity and support vector machine analyses.

RESULTS

Compared with the healthy controls, the adolescent-onset schizophrenia group showed significantly lower voxel-mirrored homotopic connectivity values in different brain regions, including the fusiform gyrus, superior temporal gyrus/insula, precentral gyrus, and precuneus. Decreased voxel-mirrored homotopic connectivity values in the superior temporal gyrus/insula were significantly correlated with Trail-Making Test: Part A performance (r = -0.437, P = .002). A combination of the voxel-mirrored homotopic connectivity values in the precentral gyrus and precuneus may be used to discriminate patients with adolescent-onset schizophrenia from controls with satisfactory classification results, which showed sensitivity of 100%, specificity of 87.09%, and accuracy of 94.93%.

CONCLUSION

Our findings highlight resting-state interhemispheric FC abnormalities within the sensorimotor network of patients with adolescent-onset schizophrenia and confirm the relationship between adolescent-onset schizophrenia and adult-onset schizophrenia. These findings suggest that reduced interhemispheric connectivity within the sensorimotor network has a pivotal role in the pathogenesis of schizophrenia.

Common Dimensional Reward Deficits Across Mood and Psychotic Disorders: A Connectome-Wide Association Study

OBJECTIVE

Anhedonia is central to multiple psychiatric disorders and causes substantial disability. A dimensional conceptualization posits that anhedonia severity is related to a transdiagnostic continuum of reward deficits in specific neural networks. Previous functional connectivity studies related to anhedonia have focused on case-control comparisons in specific disorders, using region-specific seed-based analyses. Here, the authors explore the entire functional connectome in relation to reward responsivity across a population of adults with heterogeneous psychopathology.

METHOD

In a sample of 225 adults from five diagnostic groups (major depressive disorder, N=32; bipolar disorder, N=50; schizophrenia, N=51; psychosis risk, N=39; and healthy control subjects, N=53), the authors conducted a connectome-wide analysis examining the relationship between a dimensional measure of reward responsivity (the reward sensitivity subscale of the Behavioral Activation Scale) and resting-state functional connectivity using multivariate distance-based matrix regression.

RESULTS

The authors identified foci of dysconnectivity associated with reward responsivity in the nucleus accumbens, the default mode network, and the cingulo-opercular network. Follow-up analyses revealed dysconnectivity among specific large-scale functional networks and their connectivity with the nucleus accumbens. Reward deficits were associated with decreased connectivity between the nucleus accumbens and the default mode network and increased connectivity between the nucleus accumbens and the cingulo-opercular network. In addition, impaired reward responsivity was associated with default mode network hyperconnectivity and diminished connectivity between the default mode network and the cingulo-opercular network.

CONCLUSIONS

These results emphasize the centrality of the nucleus accumbens in the pathophysiology of reward deficits and suggest that dissociable patterns of connectivity among large-scale networks are critical to the neurobiology of reward dysfunction across clinical diagnostic categories.

Abnormal functional connectivity strength in patients with adolescent-onset schizophrenia: a resting-state fMRI study

Structural and functional abnormalities were reported in the brain of patients with adolescent-onset schizophrenia (AOS). However, evidence of abnormal functional connectivity of the brain in AOS patients is limited. Thus, we analyzed the resting-state functional magnetic resonance scans of 48 drug-naive AOS patients and 31 healthy controls to determine their functional connectivity strength (FCS) and examined if FCS abnormalities were correlated with clinical characteristics. Compared with healthy controls, AOS patients showed significantly increased FCS in the left cerebellum VI and right inferior frontal gyrus/insula. A positive correlation was observed between FCS values in the right inferior frontal gyrus/insula and general psychopathology scores of positive and negative syndrome scale. Results suggest that functional connectivity pattern is disrupted in drug-naive AOS patients. The FCS values in this abnormal region have potential for evaluating the disease severity.

Intrinsic brain abnormalities in young healthy adults with childhood trauma: A resting-state functional magnetic resonance imaging study of regional homogeneity and functional connectivity

OBJECTIVE

Childhood trauma confers great risk for the development of multiple psychiatric disorders; however, the neural basis for this association is still unknown. The present resting-state functional magnetic resonance imaging study aimed to detect the effects of childhood trauma on brain function in a group of young healthy adults.

METHODS

In total, 24 healthy individuals with childhood trauma and 24 age- and sex-matched adults without childhood trauma were recruited. Each participant underwent resting-state functional magnetic resonance imaging scanning. Intra-regional brain activity was evaluated by regional homogeneity method and compared between groups. Areas with altered regional homogeneity were further selected as seeds in subsequent functional connectivity analysis. Statistical analyses were performed by setting current depression and anxiety as covariates.

RESULTS

Adults with childhood trauma showed decreased regional homogeneity in bilateral superior temporal gyrus and insula, and the right inferior parietal lobule, as well as increased regional homogeneity in the right cerebellum and left middle temporal gyrus. Regional homogeneity values in the left middle temporal gyrus, right insula and right cerebellum were correlated with childhood trauma severity. In addition, individuals with childhood trauma also exhibited altered default mode network, cerebellum-default mode network and insula-default mode network connectivity when the left middle temporal gyrus, right cerebellum and right insula were selected as seed area, respectively.

CONCLUSION

The present outcomes suggest that childhood trauma is associated with disturbed intrinsic brain function, especially the default mode network, in adults even without psychiatric diagnoses, which may mediate the relationship between childhood trauma and psychiatric disorders in later life.

Resting-state functional connectivity changes within the default mode network and the salience network after antipsychotic treatment in early-phase schizophrenia

OBJECTIVE

Abnormal resting-state functional connectivity (FC), particularly in the default mode network (DMN) and the salience network (SN), has been reported in schizophrenia, but little is known about the effects of antipsychotics on these networks. The purpose of this study was to examine the effects of atypical antipsychotics on DMN and SN and the relationship between these effects and symptom improvement in patients with schizophrenia.

METHODS

This was a prospective study of 33 patients diagnosed with schizophrenia and treated with antipsychotics at Shanghai Mental Health Center. Thirty-three healthy controls matched for age and gender were recruited. All subjects underwent functional magnetic resonance imaging (fMRI). Healthy controls were scanned only once; patients were scanned before and after 6-8 weeks of treatment.

RESULTS

In the DMN, the patients exhibited increased FC after treatment in the right superior temporal gyrus, right medial frontal gyrus, and left superior frontal gyrus and decreased FC in the right posterior cingulate/precuneus (P<0.005). In the SN, the patients exhibited decreased FC in the right cerebellum anterior lobe and left insula (P<0.005). The FC in the right posterior cingulate/precuneus in the DMN negatively correlated with the difference between the Clinical Global Impression (CGI) score pre/post-treatment (r=-0.564, P=0.023) and negative trends with the difference in the Positive and Negative Syndrome Scale (PANSS) total score pre/post-treatment (r=-0.475, P=0.063) and the difference in PANSS-positive symptom scores (r=-0.481, P=0.060).

CONCLUSION

These findings suggest that atypical antipsychotics could regulate the FC of certain key brain regions within the DMN in early-phase schizophrenia, which might be related to symptom improvement. However, the effects of atypical antipsychotics on SN are less clear.

Disruptions in the left frontoparietal network underlie resting state endophenotypic markers in schizophrenia

Advances in functional brain imaging have improved the search for potential endophenotypic markers in schizophrenia. Here, we employed independent component analysis (ICA) and dynamic causal modeling (DCM) in resting state fMRI on a sample of 35 schizophrenia patients, 20 first-degree relatives and 35 control subjects. Analysis on ICA-derived networks revealed increased functional connectivity between the left frontoparietal network (FPN) and left temporal and parietal regions in schizophrenia patients (P < 0.001). First-degree relatives shared this hyperconnectivity, in particular in the supramarginal gyrus (SMG; P = 0.008). DCM analysis was employed to further explore underlying effective connectivity. Results showed increased inhibitory connections to the left angular gyrus (AG) in schizophrenia patients from all other nodes of the left FPN (P < 0.001), and in particular from the left SMG (P = 0.001). Relatives also showed a pattern of increased inhibitory connections to the left AG (P = 0.008). Furthermore, the patient group showed increased excitatory connectivity between the left fusiform gyrus and the left SMG (P = 0.002). This connection was negatively correlated to inhibitory afferents to the left AG (P = 0.005) and to the negative symptom score on the PANSS scale (P = 0.001, r = -0.51). Left frontoparietotemporal dysfunction in schizophrenia has been previously associated with a range of abnormalities, including formal thought disorder, working memory dysfunction and sensory hallucinations. Our analysis uncovered new potential endophenotypic markers of schizophrenia and shed light on the organization of the left FPN in patients and their first-degree relatives. Hum Brain Mapp 38:1741-1750, 2017. © 2017 Wiley Periodicals, Inc.

Autism As a Disorder of High Intelligence

A suite of recent studies has reported positive genetic correlations between autism risk and measures of mental ability. These findings indicate that alleles for autism overlap broadly with alleles for high intelligence, which appears paradoxical given that autism is characterized, overall, by below-average IQ. This paradox can be resolved under the hypothesis that autism etiology commonly involves enhanced, but imbalanced, components of intelligence. This hypothesis is supported by convergent evidence showing that autism and high IQ share a diverse set of convergent correlates, including large brain size, fast brain growth, increased sensory and visual-spatial abilities, enhanced synaptic functions, increased attentional focus, high socioeconomic status, more deliberative decision-making, profession and occupational interests in engineering and physical sciences, and high levels of positive assortative mating. These findings help to provide an evolutionary basis to understanding autism risk as underlain in part by dysregulation of intelligence, a core human-specific adaptation. In turn, integration of studies on intelligence with studies of autism should provide novel insights into the neurological and genetic causes of high mental abilities, with important implications for cognitive enhancement, artificial intelligence, the relationship of autism with schizophrenia, and the treatment of both autism and intellectual disability.

Association of familial risk for schizophrenia with thalamic and medial prefrontal functional connectivity during attentional control

Anomalies in behavioral correlates of attentional processing and related brain activity are crucial correlates of schizophrenia and associated with familial risk for this brain disorder. However, it is not clear how brain functional connectivity during attentional processes is key for schizophrenia and linked with trait vs. state related variables. To address this issue, we investigated patterns of functional connections during attentional control in healthy siblings of patients with schizophrenia, who share with probands genetic features but not variables related to the state of the disorder. 356 controls, 55 patients with schizophrenia on stable treatment with antipsychotics and 40 healthy siblings of patients with this brain disorder underwent the Variable Attentional Control (VAC) task during fMRI. Independent Component Analysis (ICA) is allowed to identify independent components (IC) of BOLD signal recorded during task performance. Results indicated reduced connectivity strength in patients with schizophrenia as well as in their healthy siblings in left thalamus within an attentional control component and greater connectivity in right medial prefrontal cortex (PFC) within the so-called Default Mode Network (DMN) compared to healthy individuals. These results suggest a relationship between familial risk for schizophrenia and brain functional networks during attentional control, such that this biological phenotype may be considered a useful intermediate phenotype in order to link genes effects to aspects of the pathophysiology of this brain disorder.

Disrupted amplitude of low-frequency fluctuations in antipsychotic-naïve adolescents with early-onset schizophrenia

Evidence points to a crucial role for altered neural oscillations and synchrony in the pathophysiology of schizophrenia. Previous resting state functional magnetic resonance imaging (fMRI) studies found aberrant amplitudes of low-frequency oscillations in adult patients with schizophrenia. Whether the abnormality is also present in adolescents with early-onset schizophrenia (EOS) is largely unknown. We recruited 39 adolescents with a first episode of EOS and 31 age- and education- matched healthy controls. Resting state fMRI was obtained using an echo-planar imaging sequence. Voxel-wise amplitude of low-frequency (0.01-0.08Hz) fluctuations (ALFF) was compared between groups. We investigated seed-based functional connectivity between significantly disturbed ALFF regions and whole brain voxels in all participants. EOS participants exhibited significantly increased ALFF values in the orbitofrontal cortex (OFC) and decreased ALFF in the ventral precuneus compared with controls. Decreased ALFF values in the precuneus of EOS showed a significant negative correlation with negative symptom scores on the Positive and Negative Syndrome Scale. Disturbed functional connectivity mainly occurred between the orbitofrontal cortex and the temporal cortex in EOS. These findings demonstrate abnormal spontaneous neuronal activity and functional connectivity in the frontal and parietal cortex of EOS. Aberrant ALFF in the precuneus might be a biomarker of EOS.

Altered Cortico-Striatal Connectivity in Offspring of Schizophrenia Patients Relative to Offspring of Bipolar Patients and Controls

Schizophrenia (SZ) and bipolar disorder (BD) share clinical features, genetic risk factors and neuroimaging abnormalities. There is evidence of disrupted connectivity in resting state networks in patients with SZ and BD and their unaffected relatives. Resting state networks are known to undergo reorganization during youth coinciding with the period of increased incidence for both disorders. We therefore focused on characterizing resting state network connectivity in youth at familial risk for SZ or BD to identify alterations arising during this period. We measured resting-state functional connectivity in a sample of 106 youth, aged 7-19 years, comprising offspring of patients with SZ (N = 27), offspring of patients with BD (N = 39) and offspring of community control parents (N = 40). We used Independent Component Analysis to assess functional connectivity within the default mode, executive control, salience and basal ganglia networks and define their relationship to grey matter volume, clinical and cognitive measures. There was no difference in connectivity within any of the networks examined between offspring of patients with BD and offspring of community controls. In contrast, offspring of patients with SZ showed reduced connectivity within the left basal ganglia network compared to control offspring, and they showed a positive correlation between connectivity in this network and grey matter volume in the left caudate. Our findings suggest that dysconnectivity in the basal ganglia network is a robust correlate of familial risk for SZ and can be detected during childhood and adolescence.

Interaction among subsystems within default mode network diminished in schizophrenia patients: A dynamic connectivity approach

Default mode network (DMN) has been reported altered in schizophrenia (SZ) using static connectivity analysis. However, the studies on dynamic characteristics of DMN in SZ are still limited. In this work, we compare dynamic connectivity within DMN between 82 healthy controls (HC) and 82 SZ patients using resting-state fMRI. Firstly, dynamic DMN was computed using a sliding time window method for each subject. Then, the overall connectivity strengths were compared between two groups. Furthermore, we estimated functional connectivity states using K-means clustering, and then investigated group differences with respect to the connectivity strengths in states, the dwell time in each state, and the transition times between states. Finally, graph metrics of time-varying connectivity patterns and connectivity states were assessed. Results suggest that measured by the overall connectivity, HC showed stronger inter-subsystem interaction than patients. Compared to HC, patients spent more time in the states with nodes sparsely connected. For each state, SZ patients presented relatively weaker connectivity strengths mainly in inter-subsystem. Patients also exhibited lower values in averaged node strength, clustering coefficient, global efficiency, and local efficiency than HC. In summary, our findings indicate that SZ show impaired interaction among DMN subsystems, with a reduced central role for posterior cingulate cortex (PCC) and anterior medial prefrontal cortex (aMPFC) hubs as well as weaker interaction between dorsal medial prefrontal cortex (dMPFC) subsystem and medial temporal lobe (MTL) subsystem. For SZ, decreased integration of DMN may be associated with impaired ability in making self-other distinctions and coordinating present mental states with episodic decisions about future.

Default mode network maturation and psychopathology in children and adolescents

BACKGROUND

The human default mode (DMN) is involved in a wide array of mental disorders. Current knowledge suggests that mental health disorders may reflect deviant trajectories of brain maturation.

METHOD

We studied 654 children using functional magnetic resonance imaging (fMRI) scans under a resting-state protocol. A machine-learning method was used to obtain age predictions of children based on the average coefficient of fractional amplitude of low frequency fluctuations (fALFFs) of the DMN, a measure of spontaneous local activity. The chronological ages of the children and fALFF measures from regions of this network, the response and predictor variables were considered respectively in a Gaussian Process Regression. Subsequently, we computed a network maturation status index for each subject (actual age minus predicted). We then evaluated the association between this maturation index and psychopathology scores on the Child Behavior Checklist (CBCL).

RESULTS

Our hypothesis was that the maturation status of the DMN would be negatively associated with psychopathology. Consistent with previous studies, fALFF significantly predicted the age of participants (p < .001). Furthermore, as expected, we found an association between the DMN maturation status (precocious vs. delayed) and general psychopathology scores (p = .011).

CONCLUSIONS

Our findings suggest that child psychopathology seems to be associated with delayed maturation of the DMN. This delay in the neurodevelopmental trajectory may offer interesting insights into the pathophysiology of mental health disorders.

Connectome-wide network analysis of youth with Psychosis-Spectrum symptoms

Adults with psychotic disorders have dysconnectivity in critical brain networks, including the default mode (DM) and the cingulo-opercular (CO) networks. However, it is unknown whether such deficits are present in youth with less severe symptoms. We conducted a multivariate connectome-wide association study examining dysconnectivity with resting state functional magnetic resonance imaging in a population-based cohort of 188 youths aged 8-22 years with psychosis-spectrum (PS) symptoms and 204 typically developing (TD) comparators. We found evidence for multi-focal dysconnectivity in PS youths, implicating the bilateral anterior cingulate, frontal pole, medial temporal lobe, opercular cortex and right orbitofrontal cortex. Follow-up seed-based and network-level analyses demonstrated that these results were driven by hyper-connectivity among DM regions and diminished connectivity among CO regions, as well as diminished coupling between frontal and DM regions. Collectively, these results provide novel evidence for functional dysconnectivity in PS youths, which show marked correspondence to abnormalities reported in adults with established psychotic disorders.

Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone

Objective

To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks.

Material and methods

34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps.

Results

In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone.

Conclusions

Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity.

•

We found widespread functional dysconnectivity in unmedicated patients with schizophrenia.

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Large scale functional networks appear differentially affected in the disorder.

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Attenuation of dysconnectivity with risperidone is seen only to a limited extent.

Cellular and circuit models of increased resting-state network gamma activity in schizophrenia

Schizophrenia (SCZ) is a disorder characterized by positive symptoms (hallucinations, delusions), negative symptoms (blunted affect, alogia, reduced sociability, and anhedonia), as well as persistent cognitive deficits (memory, concentration, and learning). While the biology underlying subjective experiences is difficult to study, abnormalities in electroencephalographic (EEG) measures offer a means to dissect potential circuit and cellular changes in brain function. EEG is indispensable for studying cerebral information processing due to the introduction of techniques for the decomposition of event-related activity into its frequency components. Specifically, brain activity in the gamma frequency range (30-80Hz) is thought to underlie cognitive function and may be used as an endophenotype to aid in diagnosis and treatment of SCZ. In this review we address evidence indicating that there is increased resting-state gamma power in SCZ. We address how modeling this aspect of the illness in animals may help treatment development as well as providing insights into the etiology of SCZ.

Multivariate analyses applied to fetal, neonatal and pediatric MRI of neurodevelopmental disorders

Multivariate analysis (MVA) is a class of statistical and pattern recognition methods that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of medical neuroimaging-related challenges including identifying variables associated with a measure of clinical importance (i.e. patient outcome), creating diagnostic tests, assisting in characterizing developmental disorders, understanding disease etiology, development and progression, assisting in treatment monitoring and much more. Compared to adults, imaging of developing immature brains has attracted less attention from MVA researchers. However, remarkable MVA research growth has occurred in recent years. This paper presents the results of a systematic review of the literature focusing on MVA technologies applied to neurodevelopmental disorders in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. The goal of this manuscript is to provide a concise review of the state of the scientific literature on studies employing brain MRI and MVA in a pre-adult population. Neurological developmental disorders addressed in the MVA research contained in this review include autism spectrum disorder, attention deficit hyperactivity disorder, epilepsy, schizophrenia and more. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in pediatric/neonatal/fetal brain MRI, the field is still young and considerable research growth remains ahead of us.

Dysfunctional resting-state connectivities of brain regions with structural deficits in drug-naive first-episode schizophrenia adolescents

OBJECTIVE

Individuals with adolescent-onset schizophrenia (AOS) are a subgroup of patients who present clinical symptoms between 13 and 18years of age. Little is known about neurodevelopmental abnormalities in this patient population. The present study was to examine possible resting-state dysfunctional connectivity of brain regions with altered gray matter volume in AOS.

METHODS

Gray matter volume was investigated by voxel-based morphometry (VBM) analysis. Resting-state functional connectivity analysis was used to examine the correlations between regions with structural deficits and the remaining regions.

RESULTS

Thirty-seven first-episode schizophrenia adolescents and 30 healthy controls were enrolled. Compared to the controls, the patients showed significantly decreased gray matter volumes in the right superior temporal gyrus (STG) and middle temporal gyrus (MTG) (ps<0.05). With the right STG as seed, significantly reduced connectivities were found within the frontal-temporal networks in the patient group (ps<0.05). With the right MTG as seed, the patient group showed significantly reduced connectivities in the default-mode networks and visual networks (ps<0.05). Compared to significant correlations in the controls (p=0.02), the patients had no observed correlations between functional connectivity of the right STG and gray matter volume of this region. Significant positive correlations were found between functional connectivity of the right STG with the left middle frontal gyrus and the Positive and Negative Syndrome Scale total scores (p=0.048) after controlling the confounding variables.

CONCLUSIONS

These findings show dysfunctional resting-state connectivities of the right STG and MTG with decreased gray matter volume in adolescents with AOS, suggesting that neurodevelopmental abnormalities may be present in AOS.

Subjective Effects of Ethanol, Morphine, Δ(9)-Tetrahydrocannabinol, and Ketamine Following a Pharmacological Challenge Are Related to Functional Brain Connectivity

This analysis examines the neuronal foundation of drug-induced psychomimetic symptoms by relating the severity of these symptoms to changes in functional connectivity for a range of different psychoactive compounds with varying degrees of psychomimetic effects. The repeated measures design included 323 resting-state functional magnetic resonance imaging time series and measures of subjective effects in 36 healthy male volunteers. Four different pharmacological challenges with ethanol, morphine, Δ(9)-tetrahydrocannabinol, and ketamine (12 subjects per drug) were applied. A set of 10 "template" resting-state networks was used to determine individual connectivity maps. Linear regression was used for each individual subject to relate these connectivity maps to three clusters of drug-induced subjective psychomimetic effects ("perception," "relaxation," and "dysphoria") as measured with visual analogue scales. Group analysis showed that the subjective effects of perception correlated significantly across drugs with the connectivity of the posterior cingulate cortex and precentral gyrus with the sensorimotor network (p < 0.005, corrected). No significant correlations were found for relaxation or dysphoria. The posterior cingulate cortex has a role in visuospatial evaluation and the precentral gyrus has been associated with auditory hallucinations. Both the posterior cingulate cortex and the precentral gyrus show changes in activation in patients with schizophrenia, which can be related to the severity of positive symptoms (i.e., hallucinations and delusions), and have previously been related to changes induced by psychoactive drugs. The similarity of functional connectivity changes for drug-induced psychomimetic effects and symptoms of psychosis provides further support for the use of pharmacological challenges with psychomimetic drugs as models for psychosis.

Diametrical diseases reflect evolutionary-genetic tradeoffs: Evidence from psychiatry, neurology, rheumatology, oncology and immunology

Tradeoffs centrally mediate the expression of human adaptations. We propose that tradeoffs also influence the prevalence and forms of human maladaptation manifest in disease. By this logic, increased risk for one set of diseases commonly engenders decreased risk for another, diametric, set of diseases. We describe evidence for such diametric sets of diseases from epidemiological, genetic and molecular studies in four clinical domains: (i) psychiatry (autism vs psychotic-affective conditions), (ii) rheumatology (osteoarthritis vs osteoporosis), (iii) oncology and neurology (cancer vs neurodegenerative disorders) and (iv) immunology (autoimmunity vs infectious disease). Diametric disorders are important to recognize because genotypes or environmental factors that increase risk for one set of disorders protect from opposite disorders, thereby providing novel and direct insights into disease causes, prevention and therapy. Ascertaining the mechanisms that underlie disease-related tradeoffs should also indicate means of circumventing or alleviating them, and thus reducing the incidence and impacts of human disease in a more general way.

Structural and functional connectivity in the default mode network in 22q11.2 deletion syndrome

BACKGROUND

The neural endophenotype associated with 22q11.2 deletion syndrome (22q11DS) includes deviant cortical development and alterations in brain connectivity. Resting-state functional magnetic resonance imaging (fMRI) findings also reported disconnectivity within the default mode network (DMN). In this study, we explored the relationship between functional and structural DMN connectivity and their changes with age in patients with 22q11DS in comparison to control participants. Given previous evidence of an association between DMN disconnectivity and the manifestation of psychotic symptoms, we further investigated this relationship in our group of patients with 22q11DS.

METHODS

T1-weighted, diffusion, and resting-state fMRI scans were acquired from 41 patients with 22q11DS and 43 control participants aged 6 to 28 years. A data-driven approach based on independent component analysis (ICA) was used to identify the DMN and to define regions of interest for the structural and functional connectivity analysis. Prodromal psychotic symptoms were assessed in adolescents and adults using the positive symptom scores of the Structured Interview of Prodromal Syndromes (SIPS). Connectivity measures were compared between groups and correlated with age. Repeating the between-group analysis in three different age bins further assessed the presence of age-related alterations in DMN connectivity. Structural and functional connectivity measures were then correlated with the SIPS scores.

RESULTS

A simultaneous reduction of functional and structural connectivity between core medial nodes of the DMN was observed. Furthermore, structural connectivity measures significantly increased with age in the control group but not in patients with 22q11DS, suggesting the presence of an age-related alteration of the DMN structural connections. No correlations were found between the DMN disconnectivity and expression of prodromal symptoms in 22q11DS.

CONCLUSIONS

These findings indicate the presence of functional and structural DMN disconnectivity in 22q11DS and that patients with 22q11DS fail to develop normal structural connections between medial DMN nodes. This suggests the presence of altered neurodevelopmental trajectories in 22q11DS.

Default mode network connectivity as a function of familial and environmental risk for psychotic disorder

Background

Research suggests that altered interregional connectivity in specific networks, such as the default mode network (DMN), is associated with cognitive and psychotic symptoms in schizophrenia. In addition, frontal and limbic connectivity alterations have been associated with trauma, drug use and urban upbringing, though these environmental exposures have never been examined in relation to DMN functional connectivity in psychotic disorder.

Methods

Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 non-psychotic siblings of patients with psychotic disorder and 72 healthy controls. Posterior cingulate cortex (PCC) seed-based correlation analysis was used to estimate functional connectivity within the DMN. DMN functional connectivity was examined in relation to group (familial risk), group × environmental exposure (to cannabis, developmental trauma and urbanicity) and symptomatology.

Results

There was a significant association between group and PCC connectivity with the inferior parietal lobule (IPL), the precuneus (PCu) and the medial prefrontal cortex (MPFC). Compared to controls, patients and siblings had increased PCC connectivity with the IPL, PCu and MPFC. In the IPL and PCu, the functional connectivity of siblings was intermediate to that of controls and patients. No significant associations were found between DMN connectivity and (subclinical) psychotic/cognitive symptoms. In addition, there were no significant interactions between group and environmental exposures in the model of PCC functional connectivity.

Discussion

Increased functional connectivity in individuals with (increased risk for) psychotic disorder may reflect trait-related network alterations. The within-network “connectivity at rest” intermediate phenotype was not associated with (subclinical) psychotic or cognitive symptoms. The association between familial risk and DMN connectivity was not conditional on environmental exposure.

Dissociation of anatomical and functional alterations of the default-mode network in first-episode, drug-naive schizophrenia

OBJECTIVE

Anatomical and functional alterations of the default-mode network (DMN) have been implicated in the pathophysiology of schizophrenia. However, no study is engaged to explore whether structural and functional abnormalities of the DMN overlap in schizophrenia. This study was undertaken to examine whether anatomical and functional abnormalities are present in similar or different brain regions of the DMN in first-episode, drug-naive schizophrenia.

METHODS

Forty-nine first-episode, drug-naive schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent structural and resting-state functional magnetic resonance imaging (fMRI) scanning. The voxel-based morphometry (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze imaging data.

RESULTS

The patients exhibited significantly decreased gray matter volume (GMV) in the left medial prefrontal cortex (orbital part) and increased fALFF in the left posterior cingulate cortex compared with the controls. No overlap of brain regions with anatomical and functional abnormalities was observed in the patient group. There was also no correlation between decreased GMV/increased fALFF and clinical variables in patients.

CONCLUSIONS

A dissociation pattern of brain regions with anatomical and functional changes within the DMN is revealed in schizophrenia patients.

SIGNIFICANCE

Our findings suggest that brain functional and anatomical abnormalities within the DMN might contribute independently to the pathophysiology of schizophrenia.

Aberrant Functional Connectivity in the Default Mode and Central Executive Networks in Subjects with Schizophrenia - A Whole-Brain Resting-State ICA Study

Neurophysiological changes of schizophrenia are currently linked to disturbances in connectivity between functional brain networks. Functional magnetic resonance imaging studies on schizophrenia have focused on a few selected networks. Also previously, it has not been possible to discern whether the functional alterations in schizophrenia originate from spatial shifting or amplitude alterations of functional connectivity. In this study, we aim to discern the differences in schizophrenia patients with respect to spatial shifting vs. signal amplitude changes in functional connectivity in the whole-brain connectome. We used high model order-independent component analysis to study some 40 resting-state networks (RSN) covering the whole cortex. Group differences were analyzed with dual regression coupled with y-concat correction for multiple comparisons. We investigated the RSNs with and without variance normalization in order to discern spatial shifting from signal amplitude changes in 43 schizophrenia patients and matched controls from the Northern Finland 1966 Birth Cohort. Voxel-level correction for multiple comparisons revealed 18 RSNs with altered functional connectivity, 6 of which had both spatial and signal amplitude changes. After adding the multiple comparison, y-concat correction to the analysis for including the 40 RSNs as well, we found that four RSNs showed still changes. These robust changes actually seem encompass parcellations of the default mode network and central executive networks. These networks both have spatially shifted connectivity and abnormal signal amplitudes. Interestingly the networks seem to mix their functional representations in areas like left caudate nucleus and dorsolateral prefrontal cortex. These changes overlapped with areas that have been related to dopaminergic alterations in patients with schizophrenia compared to controls.

The reduction of volume and fiber bundle connections in the hippocampus of EGR3 transgenic schizophrenia rats

BACKGROUND AND OBJECTIVE

There is a growing consensus that schizophrenia is ultimately caused by abnormal communication between spatially disparate brain structures. White matter fasciculi represent the primary infrastructure for long distance communication in the brain. In this study, we aimed to investigate the white matter connection in schizophrenia susceptible brain regions of early growth response factor 3 (EGR3) expressing rats.

METHODS

A rat model of schizophrenia was created by the transfection of the EGR3 gene into rat hippocampus. All animals were placed in a fixation system using a commercial rat-dedicated coil. Schizophrenia susceptible brain regions were scanned using in vivo diffusion tensor magnetic resonance imaging. The volume, quantity, average length of fiber bundles, fractional anisotropy, apparent diffusion coefficient, the relative heterosexual fraction, and volume ratio were collected in the whole brain and schizophrenia related brain areas (the hippocampus, thalamus, and prefrontal lobe). MedINRIA software was used for data processing of diffusion tensor and fiber bundles tracking. The fibronectin in relevant brain regions was also analyzed.

RESULTS

There was a significant decrease in the volume of the fiber beam through the left hippocampus dentate in the schizophrenia model group in comparison to the control group and the risperidone treatment group (P<0.05). A significant reduction in the volume and number of the fiber bundles was also observed in left prefrontal-left hippocampus, left hippocampus-left thalamus, left prefrontal-left hippocampus-left thalamus areas in the model group (all P<0.05).

CONCLUSION

The volume of hippocampus and the number of fiber bundles were reduced in EGR3 transgenic schizophrenia rats, and are the most sensitive indicators in schizophrenia. The diffusion tensor imaging technique plays an important role in the evaluation of patients with schizophrenia.