Neural primacy of the salience processing system in schizophrenia

Whole-brain intrinsic functional connectivity predicts symptoms and functioning in early psychosis

Theories of psychotic illness suggest that abnormal intrinsic functional connectivity may explain its characteristic positive and disorganization symptoms as well as lead to impaired general functioning. Here we used resting state functional magnetic resonance imaging (fMRI) to evaluate associations between these symptoms and the degree to which global connectivity is abnormal in early psychosis (EP). Eighty-six healthy controls (HCs) and 108 individuals with EP with resting state fMRI data were included in primary analyses. The EP group included 83 participants with schizophrenia-spectrum disorders and 25 with bipolar disorder type I with psychotic features. A global intrinsic connectivity "similarity index" for each EP individual was determined by calculating its correlation with the average HC connectivity matrix extracted using Schaefer atlases of multiple parcellations (100, 200, 300, and 400 region parcellations). As hypothesized, connectivity similarity with the average HC matrix was negatively associated with Brief Psychiatric Rating Scale total score, Scale for the Assessment of Positive Symptoms total score, and disorganization symptoms. Similarity was also positively associated with Global Assessment of Functioning score. Results were not driven by sex or diagnosis effects and were consistent across parcellation schemes. These results support the hypothesis that changes in whole-brain connectivity patterns are associated with psychosis symptoms and support the use of functional connectivity as a biomarker for these symptoms in EP.

Altered connectivity between the central executive network and the salience network in delusion-prone individuals: A resting state eLORETA report

Although the Triple Network (TN) model has been proposed as a valid neurophysiological framework for conceptualizing delusion-like experiences, the neurodynamics of TN in relation to delusion proneness have been relatively understudied in nonclinical samples so far. Therefore, the main aim of the current study was to investigate the functional connectivity of resting state electroencephalography (EEG) in subjects with high levels of delusion proneness. Twenty-one delusion-prone (DP) individuals and thirty-seven non-delusion prone (N-DP) individuals were included in the study. The exact Low-Resolution Electromagnetic Tomography (eLORETA) software was used for all EEG analyses. Compared to N-DP participants, DP individuals showed an increas of theta connectivity (T = 3.618; p = 0.045) between the Salience Network (i.e., the left anterior insula) and the Central Executive Network (i.e., the left posterior parietal cortex). Increased theta connectivity was also positively correlated with the frequency of delusional experiences (rho = 0.317; p = 0.015). Our results suggest that increased theta connectivity between the Salience Network and the Central Executive Network may underline brain correlates of altered resting state salience detection, information processing, and cognitive control processes typical of delusional thinking.

Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder

INTRODUCTION

The dynamics of large-scale networks, which are known as distributed sets of functionally synchronized brain regions and include the visual network (VIN), somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network (FPN), and default mode network (DMN), play important roles in emotional and cognitive processes in humans. Although disruptions in these large-scale networks are considered critical for the pathophysiological mechanisms of psychiatric disorders, their role in psychiatric disorders remains unknown. We aimed to elucidate the aberrant dynamics across large-scale networks in patients with schizophrenia (SZ) and mood disorders.

METHODS

We performed energy-landscape analysis to investigate the aberrant brain dynamics of seven large-scale networks across 50 healthy controls (HCs), 36 patients with SZ, and 42 patients with major depressive disorder (MDD) recruited at Wakayama Medical University. We identified major patterns of brain activity using energy-landscape analysis and estimated their duration, occurrence, and ease of transition.

RESULTS

We identified four major brain activity patterns that were characterized by the activation patterns of the DMN and VIN (state 1, DMN (-) VIN (-); state 2, DMN (+) VIN (+); state 3, DMN (-) VIN (+); and state 4, DMN (+) VIN (-)). The duration of state 1 and the occurrence of states 1 and 2 were shorter in the SZ group than in HCs and the MDD group, and the duration of state 3 was longer in the SZ group. The ease of transition between states 3 and 4 was larger in the SZ group than in the HCs and the MDD group. The ease of transition from state 3 to state 4 was negatively associated with verbal fluency in patients with SZ. The current study showed that the brain dynamics was more disrupted in SZ than in MDD.

CONCLUSIONS

Energy-landscape analysis revealed aberrant brain dynamics across large-scale networks between SZ and MDD and their associations with cognitive abilities in SZ, which cannot be captured by conventional functional connectivity analyses. These results provide new insights into the pathophysiological mechanisms underlying SZ and mood disorders.

Dysregulated Salience Network Control over Default-Mode and Central-Executive Networks in Schizophrenia Revealed Using Stochastic Dynamical Causal Modeling

Introduction: Neuroimaging studies suggest that the human brain consists of intrinsically organized, large-scale neural networks. Among these networks, the interplay among the default-mode network (DMN), salience network (SN), and central-executive network (CEN) has been widely used to understand the functional interaction patterns in health and disease. This triple network model suggests that the SN causally controls over the DMN and CEN in healthy individuals. This interaction is often referred to as SN's dynamic regulating mechanism. However, such interactions are not well understood in individuals with schizophrenia. Methods: In this study, we leveraged resting-state functional magnetic resonance imaging data from schizophrenia (n = 67) and healthy controls (n = 81) and evaluated the directional functional interactions among DMN, SN, and CEN using stochastic dynamical causal modeling methodology. Results: In healthy controls, our analyses replicated previous findings that SN regulates DMN and CEN activities (Mann-Whitney U test; p < 10-8). In schizophrenia, however, our analyses revealed a disrupted SN-based controlling mechanism over the DMN and CEN (Mann-Whitney U test; p < 10-16). Conclusions: These results indicate that the disrupted controlling mechanism of SN over the other two neural networks may be a candidate neuroimaging phenotype in schizophrenia.

Aberrant brain dynamics in individuals with clinical high risk of psychosis

Background

Resting-state network (RSN) functional connectivity analyses have profoundly influenced our understanding of the pathophysiology of psychoses and their clinical high risk (CHR) states. However, conventional RSN analyses address the static nature of large-scale brain networks. In contrast, novel methodological approaches aim to assess the momentum state and temporal dynamics of brain network interactions.

Methods

Fifty CHR individuals and 33 healthy controls (HC) completed a resting-state functional MRI scan. We performed an Energy Landscape analysis, a data-driven method using the pairwise maximum entropy model, to describe large-scale brain network dynamics such as duration and frequency of, and transition between, different brain states. We compared those measures between CHR and HC, and examined the association between neuropsychological measures and neural dynamics in CHR.

Results

Our main finding is a significantly increased duration, frequency, and higher transition rates to an infrequent brain state with coactivation of the salience, limbic, default mode and somatomotor RSNs in CHR as compared to HC. Transition of brain dynamics from this brain state was significantly correlated with processing speed in CHR.

Conclusion

In CHR, temporal brain dynamics are attracted to an infrequent brain state, reflecting more frequent and longer occurrence of aberrant interactions of default mode, salience, and limbic networks. Concurrently, more frequent and longer occurrence of the brain state is associated with core cognitive dysfunctions, predictors of future onset of full-blown psychosis.

Frontostriatal circuitry and the tryptophan kynurenine pathway in major psychiatric disorders

RATIONALE

An imbalance of the tryptophan kynurenine pathway (KP) commonly occurs in psychiatric disorders, though the neurocognitive and network-level effects of this aberration are unclear.

OBJECTIVES

In this study, we examined the connection between dysfunction in the frontostriatal brain circuits, imbalances in the tryptophan kynurenine pathway (KP), and neurocognition in major psychiatric disorders.

METHODS

Forty first-episode medication-naive patients with schizophrenia (SCZ), fifty patients with bipolar disorder (BD), fifty patients with major depressive disorder (MDD), and forty-two healthy controls underwent resting-state functional magnetic resonance imaging. Plasma levels of KP metabolites were measured, and neurocognitive function was evaluated. Frontostriatal connectivity and KP metabolites were compared between groups while controlling for demographic and clinical characteristics. Canonical correlation analyses were conducted to explore multidimensional relationships between frontostriatal circuits-KP and KP-cognitive features.

RESULTS

Patient groups shared hypoconnectivity between bilateral ventrolateral prefrontal cortex (vlPFC) and left insula, with disorder-specific dysconnectivity in SCZ related to PFC, left dorsal striatum hypoconnectivity. The BD group had higher anthranilic acid and lower xanthurenic acid levels than the other groups. KP metabolites and ratios related to disrupted frontostriatal dysconnectivity in a transdiagnostic manner. The SCZ group and MDD group separately had high-dimensional associations between KP metabolites and cognitive measures.

CONCLUSIONS

The findings suggest that KP may influence cognitive performance across psychiatric conditions via frontostriatal dysfunction.

Increased noise relates to abnormal excitation-inhibition balance in schizophrenia: a combined empirical and computational study

Electroencephalography studies link sensory processing issues in schizophrenia to increased noise level-noise here is background spontaneous activity-as measured by the signal-to-noise ratio. The mechanism, however, of such increased noise is unknown. We investigate if this relates to changes in cortical excitation-inhibition balance, which has been observed to be atypical in schizophrenia, by combining electroencephalography and computational modeling. Our electroencephalography task results, for which the local field potentials can be used as a proxy, show lower signal-to-noise ratio due to higher noise in schizophrenia. Both electroencephalography rest and task states exhibit higher levels of excitation in the functional excitation-inhibition (as a proxy of excitation-inhibition balance). This suggests a relationship between increased noise and atypical excitation in schizophrenia, which was addressed by using computational modeling. A Leaky Integrate-and-Fire model was used to simulate the effects of varying degrees of noise on excitation-inhibition balance, local field potential, NMDA current, and . Results show a noise-related increase in the local field potential, excitation in excitation-inhibition balance, pyramidal NMDA current, and spike rate. Mutual information and mediation analysis were used to explore a cross-level relationship, showing that the cortical local field potential plays a key role in transferring the effect of noise to the cellular population level of NMDA.

Functional Alterations of the Basal Ganglia Are Associated with Voluntary Activation of the Core Stabilizing Muscles in Patients with Chronic Low Back Pain: A Cross-Sectional Study

Purpose

Deficits in voluntary activation of the core stabilizing muscles are consistently observed in patients with chronic low back pain (CLBP); however, the underlying neural mechanism remains unclear. This cross-sectional study aimed at testing the hypothesis that the impaired voluntary activation of core stabilizing muscles is associated with structural and functional alterations in the basal ganglia, thalamus, and cortex in patients with CLBP.

Methods

We obtained structural and resting-state functional magnetic resonance imaging (rs-fMRI) data from 53 patients with CLBP and 67 healthy controls and estimated the alterations in grey matter volume (GMV) and functional and effective connectivity (EC) of regions with altered GMV via whole brain analysis. The voluntary activation of the multifidus (MF) and transversus abdominis (TrA) was evaluated by ultrasound imaging in these patients.

Results

Compared with the HCs, they displayed a significant decrease in GMV in the bilateral thalamus and caudate nucleus, a significant increase in GMV in the left middle frontal gyrus, and increased resting-state functional connectivity between the right caudate nucleus and the bilateral precuneus (voxel-level p < 0.005, Gaussian random field-corrected p < 0.05). The patients also showed increased EC from the right caudate nucleus to the bilateral precuneus, which was significantly correlated with voluntary activation of the bilateral MF and TrA (all p < 0.050).

Conclusions

Grey matter alterations may be confined to regions responsible for perception, motor control, and emotion regulation in patients with CLBP. The interrupted EC from the basal ganglia to the default mode network might be involved in the impairment of voluntary activation of the core stabilizing muscles.

Cannabidiol attenuates insular activity during motivational salience processing in patients with early psychosis

BACKGROUND

The mechanisms underlying the antipsychotic potential of cannabidiol (CBD) remain unclear but growing evidence indicates that dysfunction in the insula, a key brain region involved in the processing of motivationally salient stimuli, may have a role in the pathophysiology of psychosis. Here, we investigate whether the antipsychotic mechanisms of CBD are underpinned by their effects on insular activation, known to be involved in salience processing.

METHODS

A within-subject, crossover, double-blind, placebo-controlled investigation of 19 healthy controls and 15 participants with early psychosis was conducted. Administration of a single dose of CBD was compared with placebo in psychosis participants while performing the monetary incentive delay task, an fMRI paradigm. Anticipation of reward and loss were used to contrast motivationally salient stimuli against a neutral control condition.

RESULTS

No group differences in brain activation between psychosis patients compared with healthy controls were observed. Attenuation of insula activation was observed following CBD, compared to placebo. Sensitivity analyses controlling for current cannabis use history did not affect the main results.

CONCLUSION

Our findings are in accordance with existing evidence suggesting that CBD modulates brain regions involved in salience processing. Whether such effects underlie the putative antipsychotic effects of CBD remains to be investigated.

The organization of frontostriatal brain wiring in non-affective early psychosis compared with healthy subjects using a novel diffusion imaging fiber cluster analysis

BACKGROUND

Alterations in brain connectivity may underlie neuropsychiatric conditions such as schizophrenia. We here assessed the degree of convergence of frontostriatal fiber projections in 56 young adult healthy controls (HCs) and 108 matched Early Psychosis-Non-Affective patients (EP-NAs) using our novel fiber cluster analysis of whole brain diffusion magnetic resonance imaging tractography.

METHODS

Using whole brain tractography and our fiber clustering methodology on harmonized diffusion magnetic resonance imaging data from the Human Connectome Project for Early Psychosis we identified 17 white matter fiber clusters that connect frontal cortex (FCtx) and caudate (Cd) per hemisphere in each group. To quantify the degree of convergence and, hence, topographical relationship of these fiber clusters, we measured the inter-cluster mean distances between the endpoints of the fiber clusters at the level of the FCtx and of the Cd, respectively.

RESULTS

We found (1) in both groups, bilaterally, a non-linear relationship, yielding convex curves, between FCtx and Cd distances for FCtx-Cd connecting fiber clusters, driven by a cluster projecting from inferior frontal gyrus; however, in the right hemisphere, the convex curve was more flattened in EP-NAs; (2) that cluster pairs in the right (p = 0.03), but not left (p = 0.13), hemisphere were significantly more convergent in HCs vs EP-NAs; (3) in both groups, bilaterally, similar clusters projected significantly convergently to the Cd; and, (4) a significant group by fiber cluster pair interaction for 2 right hemisphere fiber clusters (numbers 5, 11; p = .00023; p = .00023) originating in selective PFC subregions.

CONCLUSIONS

In both groups, we found the FCtx-Cd wiring pattern deviated from a strictly topographic relationship and that similar clusters projected significantly more convergently to the Cd. Interestingly, we also found a significantly more convergent pattern of connectivity in HCs in the right hemisphere and that 2 clusters from PFC subregions in the right hemisphere significantly differed in their pattern of connectivity between groups.

Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder

BACKGROUND

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD).

OBJECTIVE

This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis.

METHODS

The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information.

RESULTS

With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum.

CONCLUSIONS

This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

The role of the salience network in cognitive and affective deficits

Analysis and interpretation of studies on cognitive and affective dysregulation often draw upon the network paradigm, especially the Triple Network Model, which consists of the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). DMN activity is primarily dominant during cognitive leisure and self-monitoring processes. The FPN peaks during task involvement and cognitive exertion. Meanwhile, the SN serves as a dynamic "switch" between the DMN and FPN, in line with salience and cognitive demand. In the cognitive and affective domains, dysfunctions involving SN activity are connected to a broad spectrum of deficits and maladaptive behavioral patterns in a variety of clinical disorders, such as depression, insomnia, narcissism, PTSD (in the case of SN hyperactivity), chronic pain, and anxiety, high degrees of neuroticism, schizophrenia, epilepsy, autism, and neurodegenerative illnesses, bipolar disorder (in the case of SN hypoactivity). We discuss behavioral and neurological data from various research domains and present an integrated perspective indicating that these conditions can be associated with a widespread disruption in predictive coding at multiple hierarchical levels. We delineate the fundamental ideas of the brain network paradigm and contrast them with the conventional modular method in the first section of this article. Following this, we outline the interaction model of the key functional brain networks and highlight recent studies coupling SN-related dysfunctions with cognitive and affective impairments.

The role of the anterior insular cortex in self-monitoring: A novel study protocol with electrical stimulation mapping and functional magnetic resonance imaging

Becoming aware of one's own states is a fundamental aspect for self-monitoring, allowing us to adjust our beliefs of the world to the changing context. Previous evidence points out to the key role of the anterior insular cortex (aIC) in evaluating the consequences of our own actions, especially whenever an error has occurred. In the present study, we propose a new multimodal protocol combining electrical stimulation mapping (ESM) and functional magnetic resonance imaging (fMRI) to explore the functional role of the aIC for self-monitoring in patients undergoing awake brain surgery. Our results using a modified version of the Stroop task tackling metacognitive abilities revealed new direct evidence of the involvement of the aIC in monitoring our performance, showing increased difficulties in detecting action-outcome mismatches when stimulating a cortical site located at the most posterior part of the aIC as well as significant BOLD activations at this region during outcome incongruences for self-made actions. Based on these preliminary results, we highlight the importance of assessing the aIC's functioning during tumor resection involving this region to evaluate metacognitive awareness of the self in patients undergoing awake brain surgery. In a similar vein, a better understanding of the aIC's role during self-monitoring may help shed light on action/outcome processing abnormalities reported in several neuropsychiatric disorders such as schizophrenia, anosognosia for hemiplegia or major depression.

Neuroimaging in schizophrenia: A review article

In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.

Stimulating learning: A functional MRI and behavioral investigation of the effects of transcranial direct current stimulation on stochastic learning in schizophrenia

Transcranial direct current stimulation (tDCS) of the medial prefrontal cortex (mPFC) is under clinical investigation as a treatment for cognitive deficits. We investigate the effects of tDCS over the mPFC on performance SSLT in individuals with schizophrenia, and the underlying neurophysiological effect in regions associated with learning values and stimulus-outcome relationships. In this parallel-design double-blind pilot study, 49 individuals with schizophrenia, of whom 28 completed a fMRI, were randomized into active or sham tDCS stimulation groups. Subjects participated in 4 days of SSLT training (days 1, 2, 14, 56) with tDCS applied at day-1, and during a concurrent MRI scan at day-14. The SSLT demonstrated a significant mean difference in performance in the tDCS treatment group: at day-2 and at day-56. Active tDCS was associated with increased insular activity, and reduced amygdala activation. tDCS may offer an important novel approach to modulating brain networks to ameliorate cognitive deficits in schizophrenia, with this study being the first to show a longer-term effect on SSLT.

State-like changes in the salience network correlate with delusion severity in first-episode psychosis patients

BACKGROUND AND HYPOTHESIS

Delusions are characteristic of psychotic disorders; however, the brain correlates of delusions remain poorly known. Imaging studies on delusions typically compare images across individuals. Related confounding of inter-individual differences beyond delusions may be avoided by comparing delusional and non-delusional states within individuals.

STUDY DESIGN

We studied correlations of delusions using intra-subject correlation (intra-SC) and inter-subject correlation of functional magnetic resonance imaging (fMRI) signal time series, obtained during a movie stimulus at baseline and follow-up. We included 27 control subjects and 24 first-episode psychosis patients, who were free of delusions at follow-up, to calculate intra-SC between fMRI signals obtained during the two time points. In addition, we studied changes in functional connectivity at baseline and during the one-year follow-up using regions where delusion severity correlated with intra-SC as seeds.

RESULTS

The intra-SC correlated negatively with the baseline delusion severity in the bilateral anterior insula. In addition, we observed a subthreshold cluster in the anterior cingulate. These three regions constitute the cortical salience network (SN). Functional connectivity between the bilateral insula and the precuneus was weaker in the patients at baseline than in patients at follow-up or in control subjects at any time point.

CONCLUSIONS

The results suggest that intra-SC is a powerful tool to study brain correlates of symptoms and highlight the role of the SN and internetwork dysconnectivity between the SN and the default mode network in delusions.

Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia

Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.

A longitudinal investigation of GABA, glutamate, and glutamine across the insula during antipsychotic treatment of first-episode schizophrenia

Individuals with first-episode schizophrenia (FES) typically present with acute psychotic symptoms. Though antipsychotic drugs are the mainstay for treatment, the neurobiology underlying successful treatment remains largely elusive. Recent evidence from functional connectivity studies highlights the insula as a key structure in the neural mechanism of response. However, molecular contributions to response across insular regions remain largely unknown. We used 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to measure glutamate (Glu), Glutamine (Gln), and GABA from anterior and posterior regions of the insula across antipsychotic treatment. A total of 36 participants were examined, including 15 individuals with FES and moderate to severe psychosis who were scanned at two time points, while starting and after 6 weeks of antipsychotic treatment. Symptoms were carefully monitored across the study period to characterize treatment response. GABA, Glu, and Gln levels were calculated relative to creatine in anterior and posterior insular regions, bilaterally. In relation to psychotic symptom reduction, we observed a significant increase in Glu across all insular regions with (p < 0.001), but no corresponding changes in Gln or GABA. In group analyses, the FES cohort showed lower levels of Glu (p < 0.001) and GABA (p = 0.02) at baseline. Finally, in exploratory analyses, treatment remitters demonstrated a normalization of lower insular Glu levels across treatment, unlike non-remitters. Overall, these findings contribute to our understating of molecular changes associated with antipsychotic response and demonstrate abnormalities specific to the insula in FES.

Childhood adversity and psychotic disorders: Epidemiological evidence, theoretical models and clinical considerations

While genetic factors play a critical role in the risk for schizophrenia and other psychotic disorders, increasing evidence points to the role of childhood adversity as one of several environmental factors that can significantly impact the development, manifestations and outcome of these disorders. This paper reviews the epidemiological evidence linking childhood adversity and psychotic disorders and explores various theoretical models that seek to explain the connection. We discuss neurobiological parallels between the impact of childhood trauma and psychosis on the brain and then explore the impact of childhood adversity on different domains of clinical presentation. Finally, implications for prevention and treatment are considered, both on individual and structural levels.

A comparative neuroimaging perspective of olfaction and higher-order olfactory processing: on health and disease

Olfactory dysfunction is often the earliest indicator of disease in a range of neurological and psychiatric disorders. One tempting working hypothesis is that pathological changes in the peripheral olfactory system where the body is exposed to many adverse environmental stressors may have a causal role for the brain alteration. Whether and how the peripheral pathology spreads to more central brain regions may be effectively studied in rodent models, and there is successful precedence in experimental models for Parkinson's disease. It is of interest to study whether a similar mechanism may underlie the pathology of psychiatric illnesses, such as schizophrenia. However, direct comparison between rodent models and humans includes challenges under light of comparative neuroanatomy and experimental methodologies used in these two distinct species. We believe that neuroimaging modality that has been the main methodology of human brain studies may be a useful viewpoint to address and fill the knowledge gap between rodents and humans in this scientific question. Accordingly, in the present review article, we focus on brain imaging studies associated with olfaction in healthy humans and patients with neurological and psychiatric disorders, and if available those in rodents. We organize this review article at three levels: 1) olfactory bulb (OB) and peripheral structures of the olfactory system, 2) primary olfactory cortical and subcortical regions, and 3) associated higher-order cortical regions. This research area is still underdeveloped, and we acknowledge that further validation with independent cohorts may be needed for many studies presented here, in particular those with human subjects. Nevertheless, whether and how peripheral olfactory disturbance impacts brain function is becoming even a hotter topic in the ongoing COVID-19 pandemic, given the risk of long-term changes of mental status associated with olfactory infection of SARS-CoV-2. Together, in this review article, we introduce this underdeveloped but important research area focusing on its implications in neurological and psychiatric disorders, with several pioneered publications.

Impairments in the Default Mode and Executive Networks in Methamphetamine Users During Short-Term Abstinence

Purpose

Methamphetamine use may cause severe neurotoxicity and cognitive impairment, leading to addiction, overdose, and high rates of relapse. However, few studies have systematically focused on functional impairments detected by neuroimaging in methamphetamine abstainers (MAs) during short-term abstinence. This study aimed to investigate effective connectivity, resting-state networks, and internetwork functional connectivity in MA brains to improve clinical treatment.

Methods

Twenty MAs and 27 age- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging. The amplitude of low-frequency fluctuations and Granger causality were analyzed to investigate disrupted brain regions and effective connectivity, respectively. Independent component analysis and functional network connectivity were used to identify resting-state networks and internetwork functional connectivity, respectively.

Results

Compared with healthy controls, MAs demonstrated abnormal amplitudes of low-frequency fluctuations in the bilateral precuneus, left posterior cingulate cortex (PCC), left middle frontal gyrus (MFG), left superior parietal lobule, left supplementary motor area (SMA), and left inferior parietal lobule (IPL). Moreover, MAs showed decreased effective connectivity from the left PCC to the left precuneus, increased effective connectivity from the left precuneus to the left MFG and from the right precuneus to the left SMA, and altered functional connectivity within the default mode network (DMN), frontoparietal network, sensorimotor network, ventral attention network, cerebellar network, and visual network. Importantly, hyperconnectivity between the DMN and ventral attention network and hypoconnectivity between the DMN and cerebellar network as well as the DMN and frontoparietal network were demonstrated in MAs.

Conclusion

Our study implies that in short-term methamphetamine abstinence, disruptions to the DMN and executive network may a play key role, providing new insights for early rehabilitation.

Anterior insula as a gatekeeper of executive control

Executive control is a complex high-level cognitive function that relies on distributed brain circuitry. We propose that the anterior insular cortex plays an under-appreciated role in executive processes, acting as a gatekeeper to other brain regions and networks by virtue of primacy of action and effective connectivity. The flexible functional profile of the anterior insular subdivision renders it a key hub within the broader midcingulo-insular 'salience network', allowing it to orchestrate and drive activity of other major functional brain networks including the medial frontoparietal 'default mode network' and lateral frontoparietal 'central executive network'. The microanatomy and large-scale connectivity of the insular cortex positions it to play a critical role in triaging and integrating internal and external multisensory stimuli in the service of initiating higher-order control functions. Multiple lines of evidence scaffold the novel hypothesis that, as a key hub for integration and a lever of network switching, the anterior insula serves as a critical gatekeeper to executive control.

Evaluation of gray matter reduction in patients with typhoon-related posttraumatic stress disorder using causal network analysis of structural MRI

BACKGROUND

The structural changes recent-onset posttraumatic stress disorder (PTSD) subjects were rarely investigated. This study was to compare temporal and causal relationships of structural changes in recent-onset PTSD with trauma-exposed control (TEC) subjects and non-TEC subjects.

METHODS

T1-weighted magnetic resonance images of 27 PTSD, 33 TEC and 30 age- and sex-matched healthy control (HC) subjects were studied. The causal network of structural covariance was used to evaluate the causal relationships of structural changes in PTSD patients.

RESULTS

Volumes of bilateral hippocampal and left lingual gyrus were significantly smaller in PTSD patients and TEC subjects than HC subjects. As symptom scores increase, reduction in gray matter volume began in the hippocampus and progressed to the frontal lobe, then to the temporal and occipital cortices (p < 0.05, false discovery rate corrected). The hippocampus might be the primary hub of the directional network and demonstrated positive causal effects on the frontal, temporal and occipital regions (p < 0.05, false discovery rate corrected). The frontal regions, which were identified to be transitional points, projected causal effects to the occipital lobe and temporal regions and received causal effects from the hippocampus (p < 0.05, false discovery rate corrected).

CONCLUSIONS

The results offer evidence of localized abnormalities in the bilateral hippocampus and remote abnormalities in multiple temporal and frontal regions in typhoon-exposed PTSD patients.

Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks

The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the individual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.

Progressive changes in descriptive discourse in First Episode Schizophrenia: a longitudinal computational semantics study

Computational semantics, a branch of computational linguistics, involves automated meaning analysis that relies on how words occur together in natural language. This offers a promising tool to study schizophrenia. At present, we do not know if these word-level choices in speech are sensitive to the illness stage (i.e., acute untreated vs. stable established state), track cognitive deficits in major domains (e.g., cognitive control, processing speed) or relate to established dimensions of formal thought disorder. In this study, we collected samples of descriptive discourse in patients experiencing an untreated first episode of schizophrenia and healthy control subjects (246 samples of 1-minute speech; n = 82, FES = 46, HC = 36) and used a co-occurrence based vector embedding of words to quantify semantic similarity in speech. We obtained six-month follow-up data in a subsample (99 speech samples, n = 33, FES = 20, HC = 13). At baseline, semantic similarity was evidently higher in patients compared to healthy individuals, especially when social functioning was impaired; but this was not related to the severity of clinically ascertained thought disorder in patients. Across the study sample, higher semantic similarity at baseline was related to poorer Stroop performance and processing speed. Over time, while semantic similarity was stable in healthy subjects, it increased in patients, especially when they had an increasing burden of negative symptoms. Disruptions in word-level choices made by patients with schizophrenia during short 1-min descriptions are sensitive to interindividual differences in cognitive and social functioning at first presentation and persist over the early course of the illness.

Anxiety and cognitive-related effects of Δ 9-tetrahydrocannabinol (THC) are differentially mediated through distinct GSK-3 vs. Akt-mTOR pathways in the nucleus accumbens of male rats

RATIONALE

Δ⁹-tetrahydrocannabinol (THC) is the primary psychoactive compound in cannabis and is responsible for cannabis-related neuropsychiatric side effects, including abnormal affective processing, cognitive and sensory filtering deficits and memory impairments. A critical neural region linked to the psychotropic effects of THC is the nucleus accumbens shell (NASh), an integrative mesocorticolimbic structure that sends and receives inputs from multiple brain areas known to be dysregulated in various disorders, including schizophrenia and anxiety-related disorders. Considerable evidence demonstrates functional differences between posterior vs. anterior NASh sub-regions in the processing of affective and cognitive behaviours influenced by THC. Nevertheless, the neuroanatomical regions and local molecular pathways responsible for these psychotropic effects are not currently understood.

OBJECTIVES

The objectives of this study were to characterize the effects of intra-accumbens THC in the anterior vs. posterior regions of the NASh during emotional memory formation, sensorimotor gating and anxiety-related behaviours.

METHODS

We performed an integrative series of translational behavioural pharmacological studies examining anxiety, sensorimotor gating and fear-related associative memory formation combined with regionally specific molecular signalling analyses in male Sprague Dawley rats.

RESULTS

We report that THC in the posterior NASh causes distortions in emotional salience attribution, impaired sensory filtering and memory retention and heightened anxiety, through a glycogen-synthase-kinase-3 (GSK-3)-β-catenin dependent signalling pathway. In contrast, THC in the anterior NASh produces anxiolytic effects via modulation of protein kinase B (Akt) phosphorylation states.

CONCLUSIONS

These findings reveal critical new insights into the neuroanatomical and molecular mechanisms associated with the differential neuropsychiatric side effects of THC in dissociable nucleus accumbens sub-regions.

Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD, schizophrenia, and schizoaffective disorder) overlap in symptomatology, risk factors, genetics, and other biological measures. Based on previous findings, it remains unclear what transdiagnostic regional gray matter volume (GMV) alterations exist across these disorders, and with which factors they are associated. GMV (3-T magnetic resonance imaging) was compared between healthy controls (HC; n = 110), DSM-IV-TR diagnosed MDD (n = 110), BD (n = 110), and SSD patients (n = 110), matched for age and sex. We applied a conjunction analysis to identify shared GMV alterations across the disorders. To identify potential origins of identified GMV clusters, we associated them with early and current risk and protective factors, psychopathology, and neuropsychology, applying multiple regression models. Common to all diagnoses (vs. HC), we identified GMV reductions in the left hippocampus. This cluster was associated with the neuropsychology factor working memory/executive functioning, stressful life events, and with global assessment of functioning. Differential effects between groups were present in the left and right frontal operculae and left insula, with volume variances across groups highly overlapping. Our study is the first with a large, matched, transdiagnostic sample to yield shared GMV alterations in the left hippocampus across major mental disorders. The hippocampus is a major network hub, orchestrating a range of mental functions. Our findings underscore the need for a novel stratification of mental disorders, other than categorical diagnoses.

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

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

Resting-state network topology characterizing callous-unemotional traits in adolescence

BACKGROUND

Callous-unemotional (CU) traits, a youth antisocial phenotype, are hypothesized to associate with aberrant connectivity (dis-integration) across the salience (SAL), default mode (DMN), and frontoparietal (FPN) networks. However, CU traits have a heterogeneous presentation and previous research has not modeled individual heterogeneity in resting-state connectivity amongst adolescents with CU traits. The present study models individual-specific network maps and examines topological features of individual and subgroup maps in relation to CU traits.

METHODS

Participants aged 13-17 (n = 84, male = 55%, female = 45%) completed resting-state functional connectivity and the inventory of callous-unemotional traits as part of the Nathan Klein Rockland study. A sparse network approach (GIMME) was used to derive individual-level and subgroup maps of all participants. We then examined heterogeneous network features, including positive and negative connection density, associated with CU traits.

RESULTS

Higher rates of CU traits increased probability of inclusion in one subgroup, which had the highest mean level of CU traits. Analysis of network features reveals less density (positive and negative) within the FPN and greater density between DMN-FPN associated with CU traits.

DISCUSSION

Findings indicate heterogeneous person-specific connections and some subgroup connections amongst adolescents associate with CU traits. Higher CU traits associate with lower density in the FPN, which has been associated with attention and inhibition, and higher density between the DMN-FPN, which have been linked with cognitive control, social working memory, and empathy. Our findings suggest less efficiency in FPN function which, when considered mechanistically, could result in difficulty suppressing DMN when task positive networks are engaged. This is an area for further exploration but could explain cognitive and socio-affective impairments in CU traits.

Is There a Glutathione Centered Redox Dysregulation Subtype of Schizophrenia?

Schizophrenia continues to be an illness with poor outcome. Most mechanistic changes occur many years before the first episode of schizophrenia; these are not reversible after the illness onset. A developmental mechanism that is still modifiable in adult life may center on intracortical glutathione (GSH). A large body of pre-clinical data has suggested the possibility of notable GSH-deficit in a subgroup of patients with schizophrenia. Nevertheless, studies of intracortical GSH are not conclusive in this regard. In this review, we highlight the recent ultra-high field magnetic resonance spectroscopic studies linking GSH to critical outcome measures across various stages of schizophrenia. We discuss the methodological steps required to conclusively establish or refute the persistence of GSH-deficit subtype and clarify the role of the central antioxidant system in disrupting the brain structure and connectivity in the early stages of schizophrenia. We propose in-vivo GSH quantification for patient selection in forthcoming antioxidant trials in psychosis. This review offers directions for a promising non-dopaminergic early intervention approach in schizophrenia.

N-methyl-d-aspartate receptor antagonism modulates P300 event-related potentials and associated activity in salience and central executive networks

Impairments in auditory information processing in schizophrenia as indexed electrophysiologically by P300 deficits during novelty (P3a) and target (P3b) processing are linked to N -methyl- D -aspartate receptor (NMDAR) dysfunction. This study in 14 healthy volunteers examined the effects of a subanesthetic dose of the NMDAR antagonist ketamine on P300 and their relationship to psychomimetic symptoms and cortical source activity (with eLORETA). Ketamine reduced early (e- P3a) and late (l-P3a) novelty P300 at sensor (scalp)-level and at source-level in the salience network. Increases in dissociation symptoms were negatively correlated with ketamine-induced P3b changes, at sensor-level and source-level, in both salience and central executive networks. These P3a alterations during novelty processing, and the symptom-related P3b changes during target processing support a model of NMDAR hypofunction underlying disrupted auditory attention in schizophrenia.

Altered directed connectivity during processing of predictive stimuli in psychiatric patient populations

OBJECTIVES

The study investigated the role of top-down versus bottom-up connectivity, during the processing of predictive information, in three different psychiatric disorders.

METHODS

Electroencephalography (EEG) was recorded during the performance of a task, which evaluates the ability to use predictive information in order to facilitate predictable versus random target detection. We evaluated EEG event-related directed connectivity, in patients with schizophrenia (SZ), major depressive disorder (MDD), and autism spectrum disorder (ASD), compared with healthy age-matched controls. Directed connectivity was evaluated using phase transfer entropy.

RESULTS

We showed that top-down frontal-parietal connectivity was weaker in SZ (theta and beta bands) and ASD (alpha band) compared to control subjects, during the processing of stimuli consisting of the predictive sequence. In SZ patients, top-down connectivity was also attenuated, during the processing of predictive targets in the beta frequency band. In contrast, compared with controls, MDD patients displayed an increased top-down flow of information, during the processing of predicted targets (alpha band).

CONCLUSIONS

The findings suggest that top-down frontal-parietal connectivity is altered differentially across three major psychiatric disorders, specifically during the processing of predictive stimuli.

SIGNIFICANCE

Altered top-down connectivity may contribute to the specific prediction deficits observed in each of the patient populations.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

[Cognitive control in the research domain criteria system: clinical implications for auditory verbal hallucinations]

Cognitive control (CC) represents one of six constructs within the research domain criteria (RDoC) domain of cognitive systems, which can be examined using different units of analyses (from genetic and molecular mechanisms to neural circuits and self-reports). The CC is defined as the ability to execute top-down control over task-specific processes and to coordinate thought and actions to achieve a specific goal. Within the field of cognitive neuroscience, recent studies provided important findings about central neuronal components of the CC network and the interactions with other relevant functional systems. In the development and maintenance of distinct psychiatrically relevant symptoms, such as auditory verbal hallucinations (AVH) or hearing voices, dysfunctional CC is thought to play an essential transdiagnostic role. This selective literature review addresses the specific and clinically relevant question of the extent to which the RDoC construct of CC has been incorporated into studies investigating the neurobiological mechanisms of AVH. In addition, an overview of the extent to which findings exploring the underlying mechanisms have been transferred into daily clinical routine is provided. Furthermore, future research perspectives and therapeutic approaches are discussed. Based on currently preferred neurobiological models of AVH, nonpharmacological strategies, such as brain stimulation techniques and psychotherapy can be derived. Further research perspectives arise in the field of interventional studies oriented towards the RDoC matrix.

Disrupted pathways from frontal-parietal cortex to basal ganglia and cerebellum in patients with unmedicated obsessive compulsive disorder as observed by whole-brain resting-state effective connectivity analysis - a small sample pilot study

OBJECTIVE

To date, a systematic characterization of abnormalities in resting-state effective connectivity (rsEC) in obsessive-compulsive disorder (OCD) is lacking. The present study aimed to systematically characterize whole-brain rsEC in OCD patients as compared to healthy controls.

METHODS

Using resting-state fMRI data of 50 unmedicated patients with OCD and 50 healthy participants, we constructed whole-brain rsEC networks using Granger causality analysis followed by univariate and multivariate comparisons between patients and controls. Similar analyses were performed for resting-state functional connectivity (rsFC) networks to examine how rsFC and rsEC differentially capture abnormal brain connectivity in OCD.

RESULTS

Univariate comparisons identified 10 rsEC networks that were significantly disrupted in patients, and which were mainly associated with frontal-parietal cortex, basal ganglia, and cerebellum. Conversely, abnormal rsFC networks were widely distributed throughout the whole brain. Multivariate pattern analysis revealed a classification accuracy as high as 80.5% for distinguishing patients from controls using combined whole-brain rsEC and rsFC.

CONCLUSIONS

The results of the present study suggest disrupted communication of information from frontal-parietal cortex to basal ganglia and cerebellum in OCD patients. Using combined whole-brain rsEC and rsFC, multivariate pattern analysis revealed a classification accuracy as high as 80.5% for distinguishing patients from controls. The alterations observed in OCD patients could aid in identifying treatment mechanisms for OCD.

Tracking positive and negative symptom improvement in first-episode schizophrenia treated with risperidone using individual-level functional connectivity

BACKGROUND

To improve the treatment outcomes of patients with schizophrenia, research efforts have focused on identifying brain-based markers of treatment response. Personal characteristics regarding disease-related behaviors likely stem from inter-individual variability in the organization of brain functional systems. This study aimed to track dimension-specific changes in psychotic symptoms following risperidone treatment using individual-level functional connectivity (FC).

METHODS

A reliable cortical parcellation approach that accounts for individual heterogeneity in cortical functional anatomy was used to localize functional regions in a longitudinal cohort, consisting of 42 drug-naive first-episodes schizophrenia (FES) patients at baseline and after 8 weeks of risperidone treatment. FC was calculated in individually specified brain regions and used to predict the baseline severity and improvement of positive and negative symptoms in FES.

RESULTS

Distinct sets of individual-specific FC were separately associated with the positive and negative symptom burden at baseline, which could be used to track the corresponding symptom resolution in FES patients following risperidone treatment. Between-network connections of the fronto-parietal network (FPN) contributed the most to predicting the positive symptom domain. A combination of between-network connections of the default mode network, FPN, and within-network connections of the FPN contributed markedly to the prediction model of negative symptom.

CONCLUSION

This novel study, which accounts for individual brain variation, take a step toward establishing individual-specific theranostic biomarkers in schizophrenia.

Functional brain network dysfunctions in subjects at high-risk for psychosis: A meta-analysis of resting-state functional connectivity

Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p < 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.

Insula sub-regions across the psychosis spectrum: morphology and clinical correlates

The insula is a heterogeneous cortical region, comprised of three cytoarchitecturally distinct sub-regions (agranular, dysgranular, and granular), which traverse the anterior-posterior axis and are differentially involved in affective, cognitive, and somatosensory processing. Smaller insula volume is consistently reported in psychosis-spectrum disorders and is hypothesized to result, in part, from abnormal neurodevelopment. To better understand the regional and diagnostic specificity of insula abnormalities in psychosis, their developmental etiology, and clinical correlates, we characterized insula volume and morphology in a large group of adults with a psychotic disorder (schizophrenia spectrum, psychotic bipolar disorder) and a community-ascertained cohort of psychosis-spectrum youth (age 8-21). Insula volume and morphology (cortical thickness, gyrification, sulcal depth) were quantified from T1-weighted structural brain images using the Computational Anatomy Toolbox (CAT12). Healthy adults (n = 196), people with a psychotic disorder (n = 303), and 1368 individuals from the Philadelphia Neurodevelopmental Cohort (PNC) (381 typically developing (TD), 381 psychosis-spectrum (PS) youth, 606 youth with other psychopathology (OP)), were investigated. Insula volume was significantly reduced in adults with psychotic disorders and psychosis-spectrum youth, following an anterior-posterior gradient across granular sub-regions. Morphological abnormalities were limited to lower gyrification in psychotic disorders, which was specific to schizophrenia and associated with cognitive ability. Insula volume and thickness were associated with cognition, and positive and negative symptoms of psychosis. We conclude that smaller insula volume follows an anterior-posterior gradient in psychosis and confers a broad risk for psychosis-spectrum disorders. Reduced gyrification is specific to schizophrenia and may reflect altered prenatal development that contributes to cognitive impairment.

Systematic Review of the Neural Effect of Electroconvulsive Therapy in Patients with Schizophrenia: Hippocampus and Insula as the Key Regions of Modulation

OBJECTIVE

Electroconvulsive therapy (ECT) has been the most potent treatment option for treatment-resistant schizophrenia (TRS). However, the underlying neural mechanisms of ECT in schizophrenia remain largely unclear. This paper examines studies that investigated structural and functional changes after ECT in patients with schizophrenia.

METHODS

We carried out a systematic review with following terms: 'ECT', 'schizophrenia', and the terms of various neuroimaging modalities.

RESULTS

Among the 325 records available from the initial search in May 2020, 17 studies were included. Cerebral blood flow in the frontal, temporal, and striatal structures was shown to be modulated (n=3), although the results were divergent. Magnetic resonance spectroscopy (MRS) studies suggested that the ratio of N-acetyl-aspartate/creatinine was increased in the left prefrontal cortex (PFC; n=2) and left thalamus (n=1). The hippocampus and insula (n=6, respectively) were the most common regions of structural/functional modulation, which also showed symptom associations. Functional connectivity of the default mode network (DMN; n=5), PFC (n=4), and thalamostriatal system (n=2) were also commonly modulated.

CONCLUSION

Despite proven effectiveness, there has been a dearth of studies investigating the neurobiological mechanisms underlying ECT. There is preliminary evidence of structural and functional modulation of the hippocampus and insula, functional changes in the DMN, PFC, and thalamostriatal system after ECT in patients with schizophrenia. We discuss the rationale and implications of these findings and the potential mechanism of action of ECT. More studies evaluating the mechanisms of ECT are needed, which could provide a unique window into what leads to treatment response in the otherwise refractory TRS population.

Neuroimaging Biomarkers in Schizophrenia

Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.

Glutamate connectivity associations converge upon the salience network in schizophrenia and healthy controls

Alterations in cortical inter-areal functional connectivity, and aberrant glutamatergic signalling are implicated in the pathophysiology of schizophrenia but the relationship between the two is unclear. We used multimodal imaging to identify areas of convergence between the two systems. Two separate cohorts were examined, comprising 195 participants in total. All participants received resting state functional MRI to characterise functional brain networks and proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate concentrations in the frontal cortex. Study A investigated the relationship between frontal cortex glutamate concentrations and network connectivity in individuals with schizophrenia and healthy controls. Study B also used 1H-MRS, and scanned individuals with schizophrenia and healthy controls before and after a challenge with the glutamatergic modulator riluzole, to investigate the relationship between changes in glutamate concentrations and changes in network connectivity. In both studies the network based statistic was used to probe associations between glutamate and connectivity, and glutamate associated networks were then characterised in terms of their overlap with canonical functional networks. Study A involved 76 individuals with schizophrenia and 82 controls, and identified a functional network negatively associated with glutamate concentrations that was concentrated within the salience network (p < 0.05) and did not differ significantly between patients and controls (p > 0.85). Study B involved 19 individuals with schizophrenia and 17 controls and found that increases in glutamate concentrations induced by riluzole were linked to increases in connectivity localised to the salience network (p < 0.05), and the relationship did not differ between patients and controls (p > 0.4). Frontal cortex glutamate concentrations are associated with inter-areal functional connectivity of a network that localises to the salience network. Changes in network connectivity in response to glutamate modulation show an opposite effect compared to the relationship observed at baseline, which may complicate pharmacological attempts to simultaneously correct glutamatergic and connectivity aberrations.

Predicting individual variability in task-evoked brain activity in schizophrenia

What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting‐state functional connectivity and brain activity during the well‐validated N‐back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine‐learning approach we were able to use resting‐state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task‐evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money.

Anterior insula regulates brain network transitions that gate conscious access

Conscious access to sensory information is likely gated at an intermediate site between primary sensory and transmodal association cortices, but the structure responsible remains unknown. We perform functional neuroimaging to determine the neural correlates of conscious access using a volitional mental imagery task, a report paradigm not confounded by motor behavior. Titrating propofol to loss of behavioral responsiveness in healthy volunteers creates dysfunction of the anterior insular cortex (AIC) in association with an impairment of dynamic transitions of default-mode and dorsal attention networks. Candidate subcortical regions mediating sensory gating or arousal (thalamus, basal forebrain) fail to show this association. The gating role of the AIC is consistent with findings in awake participants, whose conscious access is predicted by pre-stimulus AIC activity near perceptual threshold. These data support the hypothesis that AIC, situated at an intermediate position of the cortical hierarchy, regulates brain network transitions that gate conscious access.

In a human neuroimaging study, Huang et al. manipulate the level and content of consciousness using independent experimental protocols to demonstrate that the anterior insula, situated between unimodal and transmodal cortical areas along the brain’s functional hierarchy, serves as a gate for conscious access of sensory information.

Disruption of functional connectivity among subcortical arousal system and cortical networks in temporal lobe epilepsy

Growing evidence has demonstrated widespread brain network alterations in temporal lobe epilepsy (TLE). However, the relatively accurate portrait of the subcortical-cortical relationship for impaired consciousness in TLE remains unclear. We proposed that consciousness-impairing seizures may invade subcortical arousal system and corresponding cortical regions, resulting in functional abnormalities and information flow disturbances between subcortical and cortical networks. We performed resting-state fMRI in 26 patients with TLE and 30 matched healthy controls. All included patients were diagnosed with impaired awareness during focal temporal lobe seizures. Functional connectivity density was adopted to determine whether local or distant network alterations occurred in TLE, and Granger causality analysis (GCA) was utilized to assess the direction and magnitude of causal influence among these altered brain networks further. Patients showed increased local functional connectivity in several arousal structures, such as the midbrain, thalamus, and cortical regions including bilateral prefrontal cortex (PFC), left superior temporal pole, left posterior insula, and cerebellum (P < 0.05, FDR corrected). GCA analysis revealed that the casual effects among these regions in patients were significantly sparser than those in controls (P < 0.05, uncorrected), including decreased excitatory and inhibitory effects among the midbrain, thalamus and PFC, and decreased inhibitory effect from the cerebellum to PFC. These findings suggested that consciousness-impairing seizures in TLE are associated with functional alterations and disruption of information process between the subcortical arousal system and cortical network. Understanding the functional networks and innervation pathway involved in TLE can provide insights into the mechanism underlying seizure-related loss of consciousness.

Abnormal Thalamocortical Circuit in Adolescents With Early-Onset Schizophrenia

OBJECTIVE

Thalamic circuit imbalance characterized by increased sensorimotor-thalamic connectivity and decreased prefrontal-thalamic connectivity has been consistently observed in adult-onset schizophrenia (AOS), although it is unclear whether this pattern is also a feature of early-onset schizophrenia (EOS). If this is the case, thalamic circuit imbalance can be considered as a core mechanistic defect in schizophrenia, unconfounded by the age of onset.

METHOD

A total of 116 adolescents with EOS (63 drug-naive EOS) and 55 matched healthy controls (HC) were recruited and underwent resting-state functional magnetic resonance imaging scans. To define the specific location of the thalamic subregions in thalamocortical circuit, 16 atlas-based thalamic subdivisions were used in functional connectivity analysis.

RESULTS

The EOS group showed increased sensorimotor-thalamic connectivity and decreased prefrontal-cerebello-thalamic connectivity, consistent with AOS. Sensorimotor-thalamic hyperconnectivity was more prominent than prefrontal-thalamic hypoconnectivity, which was circumscribed to the medial prefrontal cortex (mPFC), in EOS. Of note, the EOS group specifically exhibited strengthened thalamic connectivity with the salience network (SN). In addition, the EOS showed a more prominent disruption of the lateral thalamic nuclear connectivity.

CONCLUSION

Thalamic dysconnectivity observed in the EOS extends the observations from adult patients. Sensorimotor-thalamic hyperconnectivity is critical for the expression of schizophrenia phenotype irrespective of the age of onset, raising the possibility of aberrant but accelerated functional network maturation in EOS. The specific thalamocortical dysconnectivity involving the SN and mPFC may underlie the distinctive features of multi-modal hallucinations and heightened emotional valence of psychosis seen in EOS.

Brain features of nearly drug-naïve female monozygotic twins with first-episode schizophrenia and the classification accuracy of brain feature patterns: A pilot study

BACKGROUND

Data on differences in brain features between monozygotic (MZ) twins with and without schizophrenia are scarce.

METHODS

We compared brain features of female MZ twins with and without first-episode schizophrenia and healthy controls (n = 20 each). Voxel-based morphometry and tract-based spatial statistics were used to analyze differences in brain structure. Whole-brain effective connectivity (EC) and functional connectivity (FC) networks were constructed using resting-state functional magnetic resonance imaging (rs-fMRI) data.

RESULTS

Female twins with schizophrenia exhibited abnormal gray matter volume (GMV) in the basal ganglia and prefrontal and parietal cortices, impairments in the arcuate fasciculus, and significant disruptions (primarily decreases) in nine EC networks. They exhibited rs-EC alterations involving the limbic areas and subcortex. Combined rs-EC and rs-FC data distinguished twins with first-episode schizophrenia with high accuracy. Combined consideration of structural and functional features enabled the distinction of female MZ twins with schizophrenia from those without schizophrenia and healthy controls with 100% accuracy.

CONCLUSIONS

Female MZ twins with schizophrenia exhibited increased GMV, white matter impairment, and disruptions in EC and FC networks. The combination of rs-EC + rs-FC data could distinguish female twins with schizophrenia from twins without schizophrenia and healthy controls with 97.4% accuracy, and the addition of structural brain features yielded a 100% accuracy rate. These findings may provide pivotal insight for further study of the mechanisms underlying schizophrenia.

Dorsolateral prefrontal circuit effective connectivity mediates the relationship between white matter structure and PASAT-3 performance in multiple sclerosis

Three decades ago a series of parallel circuits were described involving the frontal cortex and deep grey matter structures, with putative roles in control of motor and oculomotor function, cognition, behaviour and emotion. The circuit comprising the dorsolateral prefrontal cortex, caudate, globus pallidus and thalamus has a putative role in regulating executive functions. The aim of this study is to investigate effective connectivity (EC) of the dorsolateral-prefrontal circuit and its association with PASAT-3 performance in people with multiple sclerosis(MS). We use Granger causality analysis of resting-state functional MRI from 52 people with MS and 36 healthy people to infer that reduced EC in the afferent limb of the dorsolateral prefrontal circuit occurs in the people with MS with cognitive dysfunction (left: p = .006; right: p = .029), with bilateral EC reductions in this circuit resulting in more severe cognitive dysfunction than unilateral reductions alone (p = .002). We show that reduced EC in the afferent limb of the dorsolateral prefrontal circuit mediates the relationship between cognitive performance and macrostrucutral and microstructural alterations of white matter tracts in components of the circuit. Specificity is shown by the absence of any relationship between cognition and EC in the analogous and anatomically proximal motor circuit. We demonstrate good stability of the EC measures in people with MS over an interval averaging 8-months. Key positive and negative results are replicated in an independent cohort of people with MS. Our findings identify the dorsolateral prefrontal circuit as a potential target for therapeutic strategies aimed at improving cognition in people with MS.

Conceptual disorganization and redistribution of resting-state cortical hubs in untreated first-episode psychosis: A 7T study

Network-level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype that predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs). We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs, and characterized the patterns of network connectivity in the 2 groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity. Compared to HCs, reduced centrality of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased centrality of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. This cluster was strongly correlated with CD scores but not with other symptom scores. Our observations are congruent with previous findings of reduced but not increased centrality. We observed increased centrality of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer. These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. Longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.