Links among resting-state default-mode network, salience network, and symptomatology in schizophrenia

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Long-term adaptation of prefrontal circuits in a mouse model of NMDAR hypofunction

Pharmacological approaches to induce N-methyl-d-aspartate receptor (NMDAR) hypofunction have been intensively used to understand the aetiology and pathophysiology of schizophrenia. Yet, the precise cellular and molecular mechanisms that relate to brain network dysfunction remain largely unknown. Here, we used a set of complementary approaches to assess the functional network abnormalities present in male mice that underwent a 7-day subchronic phencyclidine (PCP 10 mg/kg, subcutaneously, once daily) treatment. Our data revealed that pharmacological intervention with PCP affected cognitive performance and auditory evoked gamma oscillations in the prefrontal cortex (PFC) mimicking endophenotypes of some schizophrenia patients. We further assessed PFC cellular function and identified altered neuronal intrinsic membrane properties, reduced parvalbumin (PV) immunostaining and diminished inhibition onto L5 PFC pyramidal cells. A decrease in the strength of optogenetically-evoked glutamatergic current at the ventral hippocampus to PFC synapse was also demonstrated, along with a weaker shunt of excitatory transmission by local PFC interneurons. On a macrocircuit level, functional ultrasound measurements indicated compromised functional connectivity within several brain regions particularly involving PFC and frontostriatal circuits. Herein, we reproduced a panel of schizophrenia endophenotypes induced by subchronic PCP application in mice. We further recapitulated electrophysiological signatures associated with schizophrenia and provided an anatomical reference to critical elements in the brain circuitry. Together, our findings contribute to a better understanding of the physiological underpinnings of deficits induced by subchronic NMDAR antagonist regimes and provide a test system for characterization of pharmacological compounds.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and Their Links to Genetic Risk

BACKGROUND

Schizophrenia research reveals sex differences in incidence, symptoms, genetic risk factors, and brain function. However, a knowledge gap remains regarding sex-specific schizophrenia alterations in brain function. Schizophrenia is considered a dysconnectivity syndrome, but the dynamic integration and segregation of brain networks are poorly understood. Recent advances in resting-state functional magnetic resonance imaging allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. Nevertheless, estimating time-resolved networks remains challenging due to low signal-to-noise ratio, limited short-time information, and uncertain network identification.

METHODS

We adapted a reference-informed network estimation technique to capture time-resolved networks and their dynamic spatial integration and segregation for 193 individuals with schizophrenia and 315 control participants. We focused on time-resolved spatial functional network connectivity, an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to genomic data.

RESULTS

Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spatial functional network connectivity exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and is correlated with genetic risk for schizophrenia. This dysfunction is reflected in regions with weak functional connectivity to corresponding networks.

CONCLUSIONS

Our method can effectively capture spatially dynamic networks, detect nuanced schizophrenia effects including sex-specific ones, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the clinical potential of dynamic spatial dependence and weak connectivity.

Towards New Methodology for Cross-Validation of Clinical Evaluation Scales and Functional MRI in Psychiatry

Objective biomarkers have been a critical challenge for the field of psychiatry, where diagnostic, prognostic, and theranostic assessments are still based on subjective narratives. Psychopathology operates with idiographic knowledge and subjective evaluations incorporated into clinical assessment inventories, but is considered to be a medical discipline and, as such, uses medical intervention methods (e.g., pharmacological, ECT; rTMS; tDCS) and, therefore, is supposed to operate with the language and methods of nomothetic networks. The idiographic assessments are provisionally "quantified" into "structured clinical scales" to in some way resemble nomothetic measures. Instead of fostering data merging and integration, this approach further encapsulates the clinical psychiatric methods, as all other biological tests (molecular, neuroimaging) are performed separately, only after the clinical assessment has provided diagnosis. Translational cross-validation of clinical assessment instruments and fMRI is an attempt to address the gap. The aim of this approach is to investigate whether there exist common and specific neural circuits, which underpin differential item responses to clinical self-rating scales during fMRI sessions in patients suffering from the two main spectra of mental disorders: schizophrenia and major depression. The current status of this research program and future implications to promote the development of psychiatry as a medical discipline are discussed.

A systematic review of structural and functional magnetic resonance imaging studies on the neurobiology of depressive symptoms in schizophrenia spectrum disorders

Depressive symptoms in Schizophrenia Spectrum Disorders (SSDs) negatively impact suicidality, prognosis, and quality of life. Despite this, efficacious treatments are limited, largely because the neural mechanisms underlying depressive symptoms in SSDs remain poorly understood. We conducted a systematic review to provide an overview of studies that investigated the neural correlates of depressive symptoms in SSDs using neuroimaging techniques. We searched MEDLINE, PsycINFO, EMBASE, Web of Science, and Cochrane Library databases from inception through June 19, 2023. Specifically, we focused on structural and functional magnetic resonance imaging (MRI), encompassing: (1) T1-weighted imaging measuring brain morphology; (2) diffusion-weighted imaging assessing white matter integrity; or (3) T2*-weighted imaging measures of brain function. Our search yielded 33 articles; 14 structural MRI studies, 18 functional (f)MRI studies, and 1 multimodal fMRI/MRI study. Reviewed studies indicate potential commonalities in the neurobiology of depressive symptoms between SSDs and major depressive disorders, particularly in subcortical and frontal brain regions, though confidence in this interpretation is limited. The review underscores a notable knowledge gap in our understanding of the neurobiology of depression in SSDs, marked by inconsistent approaches and few studies examining imaging metrics of depressive symptoms. Inconsistencies across studies' findings emphasize the necessity for more direct and comprehensive research focusing on the neurobiology of depression in SSDs. Future studies should go beyond "total score" depression metrics and adopt more nuanced assessment approaches considering distinct subdomains. This could reveal unique neurobiological profiles and inform investigations of targeted treatments for depression in SSDs.

Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study

BACKGROUND

Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive.

METHODS

A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance.

RESULTS

After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment.

CONCLUSIONS

The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.

Striatal Functional Hypoconnectivity in Patients With Schizophrenia Suffering From Negative Symptoms, Longitudinal Findings

BACKGROUND

Negative symptoms in schizophrenia (SZ), such as apathy and diminished expression, have limited treatments and significantly impact daily life. Our study focuses on the functional division of the striatum: limbic-motivation and reward, associative-cognition, and sensorimotor-sensory and motor processing, aiming to identify potential biomarkers for negative symptoms.

STUDY DESIGN

This longitudinal, 2-center resting-state-fMRI (rsfMRI) study examines striatal seeds-to-whole-brain functional connectivity. We examined connectivity aberrations in patients with schizophrenia (PwSZ), focusing on stable group differences across 2-time points using intra-class-correlation and associated these with negative symptoms and measures of cognition. Additionally, in PwSZ, we used negative symptoms to predict striatal connectivity aberrations at the baseline and used the striatal aberration to predict symptoms 9 months later.

STUDY RESULTS

A total of 143 participants (77 PwSZ, 66 controls) from 2 centers (Berlin/Geneva) participated. We found sensorimotor-striatum and associative-striatum hypoconnectivity. We identified 4 stable hypoconnectivity findings over 3 months, revealing striatal-fronto-parietal-cerebellar hypoconnectivity in PwSZ. From those findings, we found hypoconnectivity in the bilateral associative striatum with the bilateral paracingulate-gyrus and the anterior cingulate cortex in PwSZ. Additionally, hypoconnectivity between the associative striatum and the superior frontal gyrus was associated with lower cognition scores in PwSZ, and weaker sensorimotor striatum connectivity with the superior parietal lobule correlated negatively with diminished expression and could predict symptom severity 9 months later.

CONCLUSIONS

Importantly, patterns of weaker sensorimotor striatum and superior parietal lobule connectivity fulfilled the biomarker criteria: clinical significance, reflecting underlying pathophysiology, and stability across time and centers.

Identifying covariate-related subnetworks for whole-brain connectome analysis

Whole-brain connectome data characterize the connections among distributed neural populations as a set of edges in a large network, and neuroscience research aims to systematically investigate associations between brain connectome and clinical or experimental conditions as covariates. A covariate is often related to a number of edges connecting multiple brain areas in an organized structure. However, in practice, neither the covariate-related edges nor the structure is known. Therefore, the understanding of underlying neural mechanisms relies on statistical methods that are capable of simultaneously identifying covariate-related connections and recognizing their network topological structures. The task can be challenging because of false-positive noise and almost infinite possibilities of edges combining into subnetworks. To address these challenges, we propose a new statistical approach to handle multivariate edge variables as outcomes and output covariate-related subnetworks. We first study the graph properties of covariate-related subnetworks from a graph and combinatorics perspective and accordingly bridge the inference for individual connectome edges and covariate-related subnetworks. Next, we develop efficient algorithms to exact covariate-related subnetworks from the whole-brain connectome data with an $\ell_0$ norm penalty. We validate the proposed methods based on an extensive simulation study, and we benchmark our performance against existing methods. Using our proposed method, we analyze two separate resting-state functional magnetic resonance imaging data sets for schizophrenia research and obtain highly replicable disease-related subnetworks.

Higher-order functional brain networks and anterior cingulate glutamate + glutamine (Glx) in antipsychotic-naïve first episode psychosis patients

Human connectome studies have provided abundant data consistent with the hypothesis that functional dysconnectivity is predominant in psychosis spectrum disorders. Converging lines of evidence also suggest an interaction between dorsal anterior cingulate cortex (dACC) cortical glutamate with higher-order functional brain networks (FC) such as the default mode (DMN), dorsal attention (DAN), and executive control networks (ECN) in healthy controls (HC) and this mechanism may be impaired in psychosis. Data from 70 antipsychotic-medication naïve first-episode psychosis (FEP) and 52 HC were analyzed. 3T Proton magnetic resonance spectroscopy (1H-MRS) data were acquired from a voxel in the dACC and assessed correlations (positive FC) and anticorrelations (negative FC) of the DMN, DAN, and ECN. We then performed regressions to assess associations between glutamate + glutamine (Glx) with positive and negative FC of these same networks and compared them between groups. We found alterations in positive and negative FC in all networks (HC > FEP). A relationship between dACC Glx and positive and negative FC was found in both groups, but when comparing these relationships between groups, we found contrasting associations between these variables in FEP patients compared to HC. We demonstrated that both positive and negative FC in three higher-order resting state networks are already altered in antipsychotic-naïve FEP, underscoring the importance of also considering anticorrelations for optimal characterization of large-scale functional brain networks as these represent biological processes as well. Our data also adds to the growing body of evidence supporting the role of dACC cortical Glx as a mechanism underlying alterations in functional brain network connectivity. Overall, the implications for these findings are imperative as this particular mechanism may differ in untreated or chronic psychotic patients; therefore, understanding this mechanism prior to treatment could better inform clinicians.Clinical trial registration: Trajectories of Treatment Response as Window into the Heterogeneity of Psychosis: A Longitudinal Multimodal Imaging Study, NCT03442101 . Glutamate, Brain Connectivity and Duration of Untreated Psychosis (DUP), NCT02034253 .

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

Objective

To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.

Methods

We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.

Results

Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.

Conclusion

This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Capturing functional connectomics using Riemannian partial least squares

For neurological disorders and diseases, functional and anatomical connectomes of the human brain can be used to better inform targeted interventions and treatment strategies. Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique that captures spatio-temporal brain function through change in blood-oxygen-level-dependent (BOLD) signals over time. FMRI can be used to study the functional connectome through the functional connectivity matrix; that is, Pearson's correlation matrix between time series from the regions of interest of an fMRI image. One approach to analysing functional connectivity is using partial least squares (PLS), a multivariate regression technique designed for high-dimensional predictor data. However, analysing functional connectivity with PLS ignores a key property of the functional connectivity matrix; namely, these matrices are positive definite. To account for this, we introduce a generalisation of PLS to Riemannian manifolds, called R-PLS, and apply it to symmetric positive definite matrices with the affine invariant geometry. We apply R-PLS to two functional imaging datasets: COBRE, which investigates functional differences between schizophrenic patients and healthy controls, and; ABIDE, which compares people with autism spectrum disorder and neurotypical controls. Using the variable importance in the projection statistic on the results of R-PLS, we identify key functional connections in each dataset that are well represented in the literature. Given the generality of R-PLS, this method has the potential to investigate new functional connectomes in the brain, and with future application to structural data can open up further avenues of research in multi-modal imaging analysis.

Alterations in brain connectivity patterns in schizophrenia patients with auditory verbal hallucinations during low frequency repetitive transcranial magnetic stimulation

OBJECTIVE

Auditory verbal hallucinations (AVH) are a characteristic symptom of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has been demonstrated to alleviate the severity of AVH, its exact neurophysiological mechanisms remain unclear. This study aimed to elucidate the alterations in brain connectivity patterns in schizophrenia patients with AVH after low frequency rTMS. Furthermore, the relationship between these alterations and clinical outcomes was examined, thereby identifying potential biomarkers for rTMS treatment efficacy.

METHODS

A total of 30 schizophrenia patients with AVH and 33 healthy controls were recruited. The patients received 1 Hz rTMS applied to the left temporoparietal junction region over 15 days. Resting-state functional magnetic resonance imaging scans were conducted for all participants. Subsequently, degree centrality (DC) and seed-based functional connectivity (FC) analyses were employed to identify specific alterations in brain connectivity patterns after rTMS treatment.

RESULTS

At baseline, patients exhibited divergent DC patterns in the frontal, occipital, and limbic lobes compared to healthy controls. In addition, prior to treatment, patients demonstrated altered FC from the superior frontal gyrus seeds that linked to the frontal, temporal, and somatosensory regions. Following rTMS treatment, these abnormalities were notably reversed, correlating with improved clinical outcomes.

CONCLUSIONS

These findings demonstrate that schizophrenia patients with AVH exhibited atypical interactions within the frontal and temporal lobes. These alterations might be crucial biomarkers for predicting the efficacy of low frequency rTMS.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk

Background

Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects.

Methods

We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data.

Results

Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks.

Conclusions

Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

Clinical anatomy of the precuneus and pathogenesis of the schizophrenia

Recent evidence has shown that the precuneus plays a role in the pathogenesis of schizophrenia. The precuneus is a structure of the parietal lobe's medial and posterior cortex, representing a central hub involved in multimodal integration processes. Although neglected for several years, the precuneus is highly complex and crucial for multimodal integration. It has extensive connections with different cerebral areas and is an interface between external stimuli and internal representations. In human evolution, the precuneus has increased in size and complexity, allowing the development of higher cognitive functions, such as visual-spatial ability, mental imagery, episodic memory, and other tasks involved in emotional processing and mentalization. This paper reviews the functions of the precuneus and discusses them concerning the psychopathological aspects of schizophrenia. The different neuronal circuits, such as the default mode network (DMN), in which the precuneus is involved and its alterations in the structure (grey matter) and the disconnection of pathways (white matter) are described.

Resting-state fMRI functional connectivity and clinical correlates in Afro-descendants with schizophrenia and bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) exhibited altered activation in several brain areas, including the prefrontal and temporal cortex; however, a less explored topic is how brain connectivity and functional disturbances occur in non-Caucasian samples of SCZ and BD. Individuals with SCZ (n=20), BD (n=21), and healthy controls (HC, n=21) from indigenous and African ethnicity were submitted to clinical screening and functional assessments. Mood, compulsive and psychotic symptoms were also correlated to network dysfunction in each group. Two distinct networks' subcomponents demonstrated significant lower global efficiency (GE) in SCZ versus HC, corresponding to left posterior dorsal attention and medial left ventral attention (VA) networks. Lower GE was found in BD versus controls in four subcomponents, including the left medial and right VA. Higher compulsion scores correlated in BD with lower GE in the left VA, whereas increased report of alcohol abuse was associated with higher GE in left default mode network. Although preliminary, differences in the activation of specific networks, notably the left hemisphere, in SCZ versus controls, and lower activation in VA areas, in BD versus controls. Results highlight default mode and salient network as relevant for the emotional processing of SCZ and BD of indigenous and black ethnicity. Abstract: schizophrenia, bipolar disorder, functional neuroimaging, ethnicity, default network.

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.

Connectivity alterations of mesostriatal pathways in first episode psychosis

BACKGROUND AND HYPOTHESIS

Pathogenic understanding of the psychotic disorders converges on regulation of dopaminergic signaling in mesostriatocortical pathways. Functional connectivity of the mesostriatal pathways may inform us of the neuronal networks involved.

STUDY DESIGN

This longitudinal study of first episode psychosis (FEP) (49 patients, 43 controls) employed seed-based functional connectivity analyses of fMRI data collected during a naturalistic movie stimulus.

STUDY RESULTS

We identified hypoconnectivity of the dorsal striatum with the midbrain, associated with antipsychotic medication dose in FEP, in comparison with the healthy control group. The midbrain regions that showed hypoconnectivity with the dorsal striatum also showed hypoconnectivity with cerebellar regions suggested to be involved in regulation of the mesostriatocortical dopaminergic pathways. None of the baseline hypoconnectivity detected was seen at follow-up.

CONCLUSIONS

These findings extend earlier resting state findings on mesostriatal connectivity in psychotic disorders and highlight the potential for cerebellar regulation of the mesostriatocortical pathways as a target of treatment trials.

Impact of low-frequency repetitive transcranial magnetic stimulation on functional network connectivity in schizophrenia patients with auditory verbal hallucinations

Auditory verbal hallucinations (AVH) are a key symptom of schizophrenia. Low-frequency repetitive transcranial magnetic stimulation (rTMS) has shown potential in the treatment of AVH. However, the underlying neural mechanismof rTMS in the treatment of AVH remains largely unknown. In this study, we used a static and dynamic functional network connectivity approach to investigate the connectivity changes among the brain functional networks in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The static functional network connectivity (sFNC) analysis revealed that patients at baseline had significantly decreased connectivity between the default mode network (DMN) and language network (LAN), and within the executive control network (ECN) as well as within the auditory network (AUD) compared to controls. However, the abnormal network connectivity patterns were normalized or restored after rTMS treatment in patients, instead of increased connectivity between the ECN and LAN, as well as within the AUD. Moreover, the dynamic functional network connectivity (dFNC) analysis showed that the patients at baseline spent more time in this state that was characterized by strongly negative connectivity between the ENC and AUD, as well as within the AUD relative to controls. While after rTMS treatment, the patients showed a higher occurrence rate in this state that was characterized by strongly positive connectivity among the LAN, DMN, and ENC, as well as within the ECN. In addition, the altered static and dynamic connectivity properties were associated with reduced severity of clinical symptoms. Both sFNC and dFNC analyses provided complementary information and suggested that low-frequency rTMS treatment could induce intrinsic functional network alternations and contribute to improvements in clinical symptoms in patients with AVH.

The Development of Neuroimaging Biomarkers for Cognitive Decline in Sickle Cell Disease

Sickle cell disease (SCD) is complicated by neurologic complications including vasculopathy, hemorrhagic or ischemic overt stroke, silent cerebral infarcts and cognitive dysfunction. Patients with SCD, even in the absence of vasculopathy or stroke, have experience cognitive dysfunction that progresses with age. Transcranial Doppler ultrasound and structural brain MRI are currently used for primary and secondary stroke prevention, but laboratory or imaging biomarkers do not currently exist that are specific to the risk of cognitive dysfunction in patients with SCD. Recent investigations have used advanced MR sequences assessing cerebral hemodynamics, white matter microstructure and functional connectivity to better understand the pathophysiology of cognitive decline in SCD, with the long-term goal of developing neuroimaging biomarkers to be used in risk prediction algorithms and to assess the efficacy of treatment options for patients with SCD.

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.

Application of transcranial Doppler in cerebrovascular diseases

Transcranial Doppler (TCD) is a rapid and non-invasive diagnostic technique that can provide real-time measurements of the relative changes in cerebral blood velocity (CBV). Therefore, TCD is a useful tool in the diagnosis and treatment of clinical cerebrovascular diseases (CVDs). In this review, the basic principles of TCD and its application in CVD were outlined. Specifically, TCD could be applied to evaluate occlusive CVD, assess collateral circulation in patients with ischemic stroke, and monitor cerebral vascular occlusion before and after thrombolysis as well as cerebral vasospasm (VSP) and microembolization signals after aneurysmal subarachnoid hemorrhage (SAH). Moreover, TCD could predict short-term stroke and transient cerebral ischemia in patients with anterior circulation occlusion treated with endovascular therapy and in patients with anterior circulation vascular occlusion. Additionally, TCD not only could monitor blood velocity signals during carotid endarterectomy (CEA) or carotid artery stenting (CAS) but also allowed earlier intervention through early recognition of sickle cell disease (SCD). Presently, TCD is a useful prognostic tool to guide the treatment of CVD. On the one hand, TCD is more commonly applied in clinical research, and on the other hand, TCD has an increasing role in the management of patients. Collectively, we review the principles and clinical application of TCD and propose some new research applications for TCD.

Dorsal striatial hypoconnectivity predicts antipsychotic medication treatment response in first-episode psychosis and unmedicated patients with schizophrenia

INTRODUCTION

The dorsal striatum, comprised of the caudate and putamen, is implicated in the pathophysiology of psychosis spectrum disorders. Given the high concentration of dopamine receptors in the striatum, striatal dopamine imbalance is a likely cause in cortico-striatal dysconnectivity. There is great interest in understanding the relationship between striatal abnormalities in psychosis and antipsychotic treatment response, but few studies have considered differential involvement of the caudate and putamen. This study's goals were twofold. First, identify patterns of dorsal striatal dysconnectivity for the caudate and putamen separately in patients with a psychosis spectrum disorder; second, determine if these dysconnectivity patterns were predictive of treatment response.

METHODS

Using resting state functional connectivity, we evaluated dorsal striatal connectivity using separate bilateral caudate and putamen seed regions in two cohorts of subjects: a cohort of 71 medication-naïve first episode psychosis patients and a cohort of 42 unmedicated patients with schizophrenia (along with matched controls). Patient and control connectivity maps were contrasted for each cohort. After receiving 6 weeks of risperidone treatment, patients' clinical response was calculated. We used regression analyses to determine the relationship between baseline dysconnectivity and treatment response.

RESULTS

This dysconnectivity was also predictive of treatment response in both cohorts.

DISCUSSION

These findings suggest that the caudate may be more of a driving factor than the putamen in early cortico-striatal dysconnectivity.

Wearing a KN95/FFP2 facemask induces subtle yet significant brain functional connectivity modifications restricted to the salience network

Background

The use of facemasks is one of the consequences of the coronavirus disease 2019 (COVID-19) pandemic. We used resting-state functional magnetic resonance imaging (fMRI) to search for subtle changes in brain functional connectivity, expected notably related to the high-level salience network (SN) and default mode network (DMN).

Methods

Prospective crossover design resting 3-T fMRI study with/without wearing a tight FFP2/KN95 facemask, including 23 community-dwelling male healthy controls aged 29.9 ± 6.9 years (mean ± standard deviation). Physiological parameters, respiration frequency, and heart rate were monitored. The data analysis was performed using the CONN toolbox.

Results

Wearing an FFP2/KN95 facemask did not impact respiration or heart rate but resulted in a significant reduction in functional connectivity between the SN as the seed region and the left middle frontal and precentral gyrus. No difference was found when the DMN, sensorimotor, visual, dorsal attention, or language networks were used as seed regions. In the absence of significant changes of physiological parameter respiration and heart rate, and in the absence of changes in lower-level functional networks, we assume that those subtle modifications are cognitive consequence of wearing facemasks.

Conclusions

The effect of wearing a tight FFP2/KN95 facemask in men is limited to high-level functional networks. Using the SN as seed network, we observed subtle yet significant decreases between the SN and the left middle frontal and precentral gyrus. Our observations suggest that wearing a facemask may change the patterns of functional connectivity with the SN known to be involved in communication, social behavior, and self-awareness.

Increased cortical thickness in nodes of the cognitive control and default mode networks in psychosis of epilepsy

OBJECTIVE

To explore the cortical morphological associations of the psychoses of epilepsy.

METHODS

Psychosis of epilepsy (POE) has two main subtypes - postictal psychosis and interictal psychosis. We used automated surface-based analysis of magnetic resonance images to compare cortical thickness, area, and volume across the whole brain between: (i) all patients with POE (n = 23) relative to epilepsy-without psychosis controls (EC; n = 23), (ii) patients with interictal psychosis (n = 10) or postictal psychosis (n = 13) relative to EC, and (iii) patients with postictal psychosis (n = 13) relative to patients with interictal psychosis (n = 10).

RESULTS

POE is characterised by cortical thickening relative to EC, occurring primarily in nodes of the cognitive control network; (rostral anterior cingulate, caudal anterior cingulate, middle frontal gyrus), and the default mode network (posterior cingulate, medial paracentral gyrus, and precuneus). Patients with interictal psychosis displayed cortical thickening in the left hemisphere in occipital and temporal regions relative to EC (lateral occipital cortex, lingual, fusiform, and inferior temporal gyri), which was evident to a lesser extent in postictal psychosis patients. There were no significant differences in cortical thickness, area, or volume between the postictal psychosis and EC groups, or between the postictal psychosis and interictal psychosis groups. However, prior to correction for multiple comparisons, both the interictal psychosis and postictal psychosis groups displayed cortical thickening relative to EC in highly similar regions to those identified in the POE group overall.

SIGNIFICANCE

The results show cortical thickening in POE overall, primarily in nodes of the cognitive control and default mode networks, compared to patients with epilepsy without psychosis. Additional thickening in temporal and occipital neocortex implicated in the dorsal and ventral visual pathways may differentiate interictal psychosis from postictal psychosis. A novel mechanism for cortical thickening in POE is proposed whereby normal synaptic pruning processes are interrupted by seizure onset.

Brain gyrification in bipolar disorder: a systematic review of neuroimaging studies

Bipolar disorder (BD) is a severe mental illness with a strong genetic component. Genetic variations have been involved in the risk of this disorder, including those mediating brain function and neurodevelopment. Early neurodevelopment and neuroprogression processes could be reflected in brain gyrification patterns and help optimize the prediction and diagnosis of such disorders that is often delayed. Previous neuroimaging studies using this measure in patients with bipolar disorder revealed controversial results. This systematic review aimed to summarize available neuroimaging investigations on gyrification in BD compared to healthy controls (HC) and/or other psychiatric groups. Fourteen studies including 733 patients with BD, 585 patients with schizophrenia (SCZ), 90 with schizoaffective disorder (SZA), and 1380 healthy subjects were identified. Overall, a heterogeneous pattern of gyrification emerged between patients with BD and HC. Interestingly, increased gyrification or no differences were also observed in patients with BD compared to those with the schizophrenia-spectrum disorders. Furthermore, relatives of patients with BD showed lower or no differences in gyrification compared to healthy subjects without a family history of affective illness. Differences in the design and in methodological approaches could have contributed to the heterogeneity of the findings. The current review supports an altered brain gyrification pattern that underlies the pathophysiology of BD spanning large anatomical and functional neural networks, associated with altered cognitive functioning, difficulties in processing and affective regulation, and clinical symptoms. Longitudinal studies are needed to test different bipolar phenotypes and pharmacological effects on gyrification.

Aberrant functional connectivity within the salience network is related to cognitive deficits and disorganization in psychosis

In schizophrenia and schizoaffective disorder cognitive deficits are a reliable characteristic predicting a poor functional outcome. It has been theorized that both the default mode network (DMN) and the salience network (SN) play a crucial role in cognitive processes and aberrant functional connectivity within these networks in psychotic patients has been reported. The goal of this study was to reveal potential links between aberrant functional connectivity within these networks and impaired cognitive performance in psychosis. We chose two approaches for cognitive assessment, first the MATRICS Consensus Cognitive Battery (MCCB) combined into a global score and second the disorganization factor derived from a five-factor model of the Positive and Negative Syndrome Scale (PANSS) known to be relevant for cognitive performance. DMN and SN were identified using independent component analysis on resting-state functional magnetic resonance imaging data. We found significantly decreased connectivity within the right supplementary motor area (SMA) and bilateral putamen in patients with psychosis (n = 70; 27F/43M) compared to healthy controls (n = 72; 28F/44M). Within patients, linear regression analysis revealed that aberrant SMA connectivity was associated with impaired global cognition, while dysfunctional bilateral putamen connectivity predicted disorganization. There were no significant changes in connectivity within the DMN. Results support the hypothesis that SN dysfunctional connectivity is important in the pathobiology of cognitive deficits in psychosis. For the first time we were able to show the involvement of dysfunctional SMA connectivity in this context. We interpret the decreased SN connectivity as evidence of reduced functionality in recruiting brain areas necessary for cognitive processing.

Resting-state functional connectivity of salience network in schizophrenia and depression

To explore the salience network (SN) functional alterations in schizophrenia and depression, resting-state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with schizophrenia (SCH), 28 patients with depression (DEP) and 30 healthy controls (HC) were obtained. The SN was derived from data-driven group independent component analysis (gICA). ANCOVA and post hoc tests were performed to discover the FC differences of SN between groups. The ANCOVA demonstrated a significant group effect in FC with right inferior and middle temporal gyrus (ITG and MTG), left caudate, and right precentral gyrus. Post-hoc analyses revealed an opposite altered FC pattern between SN and right ITG and MTG for both patient groups. The DEP group showed a reduced FC between SN and right ITG and MTG compared with HC whereas the SCH group showed an increased FC. In addition, the SCH group showed decreased FC between SN and left caudate, and enhanced FC between SN and right precentral gyrus compared to the other two groups. Our findings suggest distinct FC of SN in schizophrenia and depression, supporting that the resting-state FC pattern of SN may be a transdiagnostic difference between depression and schizophrenia and may play a critical role in the pathogenesis of these two disorders.

Characteristics of EEG Microstate Sequences During Propofol-Induced Alterations of Brain Consciousness States

Monitoring the consciousness states of patients and ensuring the appropriate depth of anesthesia (DOA) is critical for the safe implementation of surgery. In this study, a high-density electroencephalogram (EEG) combined with blood drug concentration and behavioral response indicators was used to monitor propofol-induced sedation and evaluate the alterations in consciousness states. Microstate analysis, which can reflect the semi-stable state of the sub-second activation of the brain functional network, can be used to assess the brain's consciousness states. In this research, the EEG microstate sequences were constructed to compare the characteristics of corresponding sequences. Compared with the baseline (BS) state, the microstate sequences in the moderate sedation (MD) state exhibited higher complexity indexes of the multiscale sample entropy. With respect to the transition probability (TP) of microstates, most microstates tended to be converted into microstate C in the BS state. In contrast, they tended to be converted into microstate F in the MD state. The significant difference between the expected TP and observed TP could lead to the conclusion that hidden layers were present when there were changes in the consciousness states. According to the hidden Markov model, the accuracy of distinguishing the BS and MD states was 80.16%. The characteristics of microstate sequence revealed the variations in the brain states caused by alterations in consciousness states during anesthesia from a new perspective and presented a new idea for monitoring the DOA.

Modular-Level Functional Connectome Alterations in Individuals With Hallucinations Across the Psychosis Continuum

Functional connectome alterations, including modular network organization, have been related to the experience of hallucinations. It remains to be determined whether individuals with hallucinations across the psychosis continuum exhibit similar alterations in modular brain network organization. This study assessed functional connectivity matrices of 465 individuals with and without hallucinations, including patients with schizophrenia and bipolar disorder, nonclinical individuals with hallucinations, and healthy controls. Modular brain network organization was examined at different scales of network resolution, including (1) global modularity measured as Qmax and Normalised Mutual Information (NMI) scores, and (2) within- and between-module connectivity. Global modular organization was not significantly altered across groups. However, alterations in within- and between-module connectivity were observed for higher-order cognitive (e.g., central-executive salience, memory, default mode), and sensory modules in patients with schizophrenia and nonclinical individuals with hallucinations relative to controls. Dissimilar patterns of altered within- and between-module connectivity were found bipolar disorder patients with hallucinations relative to controls, including the visual, default mode, and memory network, while connectivity patterns between visual, salience, and cognitive control modules were unaltered. Bipolar disorder patients without hallucinations did not show significant alterations relative to controls. This study provides evidence for alterations in the modular organization of the functional connectome in individuals prone to hallucinations, with schizophrenia patients and nonclinical individuals showing similar alterations in sensory and higher-order cognitive modules. Other higher-order cognitive modules were found to relate to hallucinations in bipolar disorder patients, suggesting differential neural mechanisms may underlie hallucinations across the psychosis continuum.

Cerebellar Coordination of Neuronal Communication in Cerebral Cortex

Cognitive processes involve precisely coordinated neuronal communications between multiple cerebral cortical structures in a task specific manner. Rich new evidence now implicates the cerebellum in cognitive functions. There is general agreement that cerebellar cognitive function involves interactions between the cerebellum and cerebral cortical association areas. Traditional views assume reciprocal interactions between one cerebellar and one cerebral cortical site, via closed-loop connections. We offer evidence supporting a new perspective that assigns the cerebellum the role of a coordinator of communication. We propose that the cerebellum participates in cognitive function by modulating the coherence of neuronal oscillations to optimize communications between multiple cortical structures in a task specific manner.

Rationale and study design of a trial to assess rTMS add-on value for the amelioration of negative symptoms of schizophrenia (RADOVAN)

Background

Methods

Discussion

Trial registration number

Data dissemination

Aberrant striatal coupling with default mode and central executive network relates to self-reported avolition and anhedonia in schizophrenia

BACKGROUND

Avolition and anhedonia are common symptoms in schizophrenia and are related to poor long-term prognosis. There is evidence for aberrant cortico-striatal function and connectivity as neural substrate of avolition and anhedonia. However, it remains unclear how both relate to shared or distinct striatal coupling with large-scale intrinsic networks. Using resting state functional magnetic resonance imaging (rs-fMRI) this study investigated the association of large-scale cortico-striatal functional connectivity with self-reported and clinician-rated avolition and anhedonia in subjects with schizophrenia.

METHODS

Seventeen subjects with schizophrenia (SZ) and 28 healthy controls (HC) underwent rs-fMRI. Using Independent Component Analysis (ICA), we assessed Independent Components (ICs) reflecting intrinsic connectivity networks (ICNs), intra intrinsic functional connectivity within the ICs (intra-iFC), and intrinsic functional connectivity between different ICs (inter-iFC). Avolition and anhedonia were assessed using the Self Evaluation Scale for Negative Symptoms and the Brief Negative Symptom Scale.

RESULTS

ICA revealed three striatal components and six cortical ICNs. Both self-rated avolition and anhedonia correlated with increased inter-iFC between the caudate and posterior Default Mode Network (pDMN) and between the caudate and Central Executive Network (CEN). In contrast, clinician-rated avolition and anhedonia were not correlated with cortico-striatal connectivity. Group comparison revealed trend-wise decreased inter-iFC between the caudate and Salience Network (SN) in schizophrenia patients compared to HC.

DISCUSSION

Self-rated, but not clinician-rated, avolition and anhedonia was associated with aberrant striatal coupling with the default mode and the central executive network. These findings suggest that self-reported and clinician-rated scores might capture different aspects of motivational and hedonic deficits in schizophrenia and therefore relate to different cortico-striatal functional abnormalities.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Resting-State Networks Associated with Behavioral and Self-Reported Measures of Persecutory Ideation in Psychosis

Persecutory ideations are self-referential delusions of being the target of malevolence despite a lack of evidence. Wisner et al. (2021) found that reduced connectivity between the left frontoparietal (lFP) network and parts of the orbitofrontal cortex (OFC) correlated with increased persecutory behaviors among psychotic patients performing in an economic social decision-making task that can measure the anticipation of a partner’s spiteful behavior. If this pattern could be observed in the resting state, it would suggest a functional-structural prior predisposing individuals to persecutory ideation. Forty-four patients in the early course of a psychotic disorder provided data for resting-state functional connectivity magnetic resonance imaging across nine brain networks that included the FP network and a similar OFC region. As predicted, we found a significant and negative correlation between the lFP–OFC at rest and the level of suspicious mistrust on the decision-making task using a within-group correlational design. Additionally, self-reported persecutory ideation correlated significantly with the connectivity between the right frontoparietal (rFP) network and the OFC. We extended the previous finding of reduced connectivity between the lFP network and the OFC in psychosis patients to the resting state, and observed a possible hemispheric difference, such that greater rFP–OFC connectivity predicted elevated self-reported persecutory ideation, suggesting potential differences between the lFP and rFP roles in persecutory social interactions.

Distinct neural networks associated with obsession and delusion: a connectome-wide association study

BACKGROUND

Obsession and delusion are theoretically distinct from each other in terms of reality testing. Despite such phenomenological distinction, no extant studies have examined the identification of common and distinct neural correlates of obsession and delusion by employing biologically grounded methods. Here, we investigated dimensional effects of obsession and delusion spanning across the traditional diagnostic boundaries reflected upon the resting-state functional connectivity (RSFC) using connectome-wide association studies (CWAS).

METHODS

Our study sample comprised of 96 patients with obsessive-compulsive disorder, 75 patients with schizophrenia, and 65 healthy controls. A connectome-wide analysis was conducted to examine the relationship between obsession and delusion severity and RFSC using multivariate distance-based matrix regression.

RESULTS

Obsession was associated with the supplementary motor area, precentral gyrus, and superior parietal lobule, while delusion was associated with the precuneus. Follow-up seed-based RSFC and modularity analyses revealed that obsession was related to aberrant inter-network connectivity strength. Additional inter-network analyses demonstrated the association between obsession severity and inter-network connectivity between the frontoparietal control network and the dorsal attention network.

CONCLUSIONS

Our CWAS study based on the Research Domain Criteria (RDoC) provides novel evidence for the circuit-level functional dysconnectivity associated with obsession and delusion severity across diagnostic boundaries. Further refinement and accumulation of biomarkers from studies embedded within the RDoC framework would provide useful information in treating individuals who have some obsession or delusion symptoms but cannot be identified by the category of clinical symptoms alone.

Functional connectome-wide associations of schizophrenia polygenic risk

Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.

Audiovisual working memory and association with resting-state regional homogeneity

Multisensory processing is a prevalent research issue. However, multisensory working memory research has received inadequate attention. The present study aimed to investigate the behavioral performance of an audiovisual working memory task and its association with resting-state functional magnetic resonance imaging (fMRI) regional homogeneity (ReHo). A total of 128 healthy participants were enrolled in this study. The participants completed a modified Sternberg working memory task using complex auditory and visual objects as materials involved in different encoding conditions, including semantically congruent audiovisual, semantically incongruent audiovisual, and single modality of auditory or visual object encoding. Two subgroups received resting-state fMRI scans according to their behavioral performances. The results showed that the semantically congruent audiovisual object encoding sped up the later unisensory memory recognition in this task. Moreover, the high behavioral performance (response time, RT) group showed increased ReHo in the executive control network (ECN) and decreased ReHo in the default mode network (DMN) and saline network (SN). In addition, resting-state ReHo values in the ECN nodes (e.g., middle frontal gyrus and superior frontal gyrus) was correlated with RT. These findings suggested that semantically congruent audiovisual processing in working memory was superior to unisensory memory recognition and may be involved in the different functional networks such as ECN.

Altered cortico-striatal functional connectivity in people with high levels of schizotypy: A longitudinal resting-state study

PURPOSE OF THE RESEARCH

Cortico-striatal functional connectivity has been implicated in the neuropathology of schizophrenia. However, the longitudinal relationship between the cortico-striatal connectivity and schizotypy remains unknown. We examined the resting-state fMRI connectivity in 27 individuals with a high level of schizotypy and 20 individuals with a low level of schizotypy at baseline and 18 months later. Correlations between changes in cortico-striatal connectivity and changes in schizotypy scores over time were examined.

PRINCIPAL RESULTS

We found both increased and decreased cortico-striatal connectivity in individuals with a high level of schizotypy at baseline. Over time, these individuals showed improvement in both the negative and positive schizotypal domains. Changes in striatal-insula connectivity were positively correlated with changes in positive schizotypy from baseline to follow-up.

MAJOR CONCLUSIONS

Our results suggested impaired cortico-striatal connectivity in individuals with a high level of schizotypy. The dysconnectivity mainly involves the dorsal striatum. The connectivity between the dorsal striatum and the insula may be a putative marker for temporal changes in positive schizotypy.

Anhedonia Relates to the Altered Global and Local Grey Matter Network Properties in Schizophrenia

Anhedonia is one of the major negative symptoms in schizophrenia and defined as the loss of hedonic experience to various stimuli in real life. Although structural magnetic resonance imaging has provided a deeper understanding of anhedonia-related abnormalities in schizophrenia, network analysis of the grey matter focusing on this symptom is lacking. In this study, single-subject grey matter networks were constructed in 123 patients with schizophrenia and 160 healthy controls. The small-world property of the grey matter network and its correlations with the level of physical and social anhedonia were evaluated using graph theory analysis. In the global scale whole-brain analysis, the patients showed reduced small-world property of the grey matter network. The local-scale analysis further revealed reduced small-world property in the default mode network, salience/ventral attention network, and visual network. The regional-level analysis showed an altered relationship between the small-world properties and the social anhedonia scale scores in the cerebellar lobule in patients with schizophrenia. These results indicate that anhedonia in schizophrenia may be related to abnormalities in the grey matter network at both the global whole-brain scale and local-regional scale.

A new era for executive function research: On the transition from centralized to distributed executive functioning

"Executive functions" (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.

Temporal Dynamics in Degree Centrality of Brain Functional Connectome in First-Episode Schizophrenia with Different Short-Term Treatment Responses: A Longitudinal Study

PURPOSE

This study investigated temporal dynamics in degree centrality (DC) of the brain functional connectome in first-episode schizophrenia with different short-term treatment responses.

METHODS

A total of 127 first-episode patients (FEPs) with schizophrenia and 133 healthy controls (HCs) were recruited in this study. All subjects underwent resting-state functional magnetic resonance imaging. FEPs were scanned at baseline (pretreatment) and at follow-up (posttreatment), while HCs were scanned only at baseline. The patients were exposed to naturalistic antipsychotic treatment for 12 weeks, and classified as schizophrenia responders (SRs) or nonresponders (NRs). Voxel-wise dynamic DC analyses were conducted among the SRs (n=75), NRs (n=52), and HCs (n=133) to assess temporal variability in functional connectivity across the entire neuronal network.

RESULTS

The SRs and NRs showed dissimilar dynamic DC at baseline, with differences mainly involving the temporal lobe. Different DC alteration was observed in the left fusiform gyrus, right fusiform gyrus, left middle cingulate cortex, and left superior parietal gyrus in the SRs and NRs pre- and posttreatment. SRs group and NRs presented opposite changing patterns of dynamic DC in particular regions of the brain.

CONCLUSION

These findings indicate that dynamic DC abnormalities exist in unmedicated patients with schizophrenia. The NRs differed from the SRs in dynamic DC not only at baseline but in the characteristics of changes before and after treatment as well. Our study may contribute to understanding pathophysiology in schizophrenia with different treatment responses.

Enhanced functional connectivity between insular subregions correlates with the efficacy of music and instruction-guided relaxation in depression

Music and instruction-guided relaxation (MIGR) is a complementary therapeutic tool used in the treatment of the major depressive disorder (MDD). However, the neural mechanism that underlies the effect of MIGR on MDD patients is not known. Twenty-three right-handed MDD patients and 23 age-, sex-, handedness-, and educational level-matched healthy controls were enrolled. Resting-state functional MRI data were acquired from patients before and after MIGR and from healthy controls. The relationships between insular subregion-based functional connectivity and Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale (HAM-A), Automatic Thoughts Questionnaire, and Ruminative Responses Scale scores were examined. One-way analysis of variance exhibited significant differences among the three groups in functional connectivity between the left dorsal anterior insula (dAI) and left superior medial frontal gyrus (SMFG), left dAI and left precuneus, left posterior insula and left gyrus rectus, right ventral anterior insula (vAI) and left posterior cingulate cortex (PCC), right vAI and right inferior frontal gyrus (R-IFG). Further comparisons in regions of interest showed that MDD patients before MIGR showed decreased functional connectivity between the left dAI and left SMFG, left dAI and left precuneus, left posterior insula, and left gyrus rectus, right vAI and left PCC, right vAI and R-IFG relative to those in healthy controls. The strength of functional connectivity between the right dAI and left putamen also exhibited a negative correlation with the HAM-A score in MDD cases before MIGR. MIGR may result in enhanced functional connectivity in insular subregions, thereby potentially increasing the regulatory influence of cognitive reappraisal.

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.

Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives

BACKGROUND

Dysfunction of the corticostriatal network has been implicated in the pathophysiology of schizophrenia, but findings are inconsistent within and across imaging modalities. We used multimodal neuroimaging to analyze functional and structural connectivity in the corticostriatal network in people with schizophrenia and unaffected first-degree relatives.

METHODS

We collected resting-state functional magnetic resonance imaging and diffusion tensor imaging scans from people with schizophrenia (n = 47), relatives (n = 30) and controls (n = 49). We compared seed-based functional and structural connectivity across groups within striatal subdivisions defined a priori.

RESULTS

Compared with controls, people with schizophrenia had altered connectivity between the subdivisions and brain regions in the frontal and temporal cortices and thalamus; relatives showed different connectivity between the subdivisions and the right anterior cingulate cortex (ACC) and the left precuneus. Post-hoc t tests revealed that people with schizophrenia had decreased functional connectivity in the ventral loop (ventral striatum-right ACC) and dorsal loop (executive striatum-right ACC and sensorimotor striatum-right ACC), accompanied by decreased structural connectivity; relatives had reduced functional connectivity in the ventral loop and the dorsal loop (right executive striatum-right ACC) and no significant difference in structural connectivity compared with the other groups. Functional connectivity among people with schizophrenia in the bilateral ventral striatum-right ACC was correlated with positive symptom severity.

LIMITATIONS

The number of relatives included was moderate. Striatal subdivisions were defined based on a relatively low threshold, and structural connectivity was measured based on fractional anisotropy alone.

CONCLUSION

Our findings provide insight into the role of hypoconnectivity of the ventral corticostriatal system in people with schizophrenia.

Neural Substrates of Brand Love: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

Brand love is a critical concept for building a relationship between brands and consumers because falling in love with a brand can lead to strong brand loyalty. Despite the importance of marketing strategies, however, the underlying neural mechanisms of brand love remain unclear. The present study used an activation likelihood estimation meta-analysis method to investigate the neural correlates of brand love and compared it with those of maternal and romantic love. In total, 47 experiments investigating brand, maternal, and romantic love were examined, and the neural systems involved for the three loves were compared and contrasted. Results revealed that the putamen and insula were commonly activated in the three loves. Moreover, activated brain regions in brand love were detected in the dorsal striatum. Activated regions for maternal love were detected in the cortical area and globus pallidus and were associated with pair bonds, empathy, and altruism. Finally, those for romantic love were detected in the hedonic, strong passionate, and intimate-related regions, such as the nucleus accumbens and ventral tegmental area. Thus, the common regions of brain activation between brand and romantic love were in the dorsal striatum. Meanwhile, no common activated regions were observed between brand and maternal love except for the regions shared among the three love types. Although brand love shared little with the two interpersonal (maternal and romantic) loves and relatively resembled aspects of romantic rather than maternal love, our results demonstrated that brand love may have intrinsically different dispositions from the two interpersonal loves.

Decreased functional connectivity within the salience network after two-week morning bright light exposure in individuals with sleep disturbances: a preliminary randomized controlled trial

BACKGROUND

Bright light (BL) exposure is a safe non-pharmacological intervention for sleep disturbances. However, the functional brain correlates underlying the effects of bright light exposure need to be further clarified. As alterations in the salience network were reported in individuals with sleep disturbances, we have investigated whether bright light exposure may improve sleep quality by altering functional connectivity in this network.

METHODS

In the current study, 30 individuals with sleep disturbances were randomly assigned to one of the two interventions for two weeks: (1) 1 h of bright light (10,000 lux) exposure (BL-exposed group) and (2) 1 h of dim light (<300 lux) exposure (DL-exposed group). Sleep characteristics and functional connectivity in the salience network were assessed by sleep diary and resting-state functional magnetic resonance imaging, respectively, as outcome measures at before and after the intervention.

RESULTS

After two weeks of the intervention, the BL-exposed group showed greater improvement with respect to sleep efficiency (t = 2.27, p = 0.03) and sleep latency (t = -2.40, p = 0.03) as compared to the DL-exposed group. In addition, functional connectivity decreased in the cluster that encompasses the right anterior insular and the frontal opercular regions in the salience network (uncorrected p < 0.001, cluster size>100 mm³) in the BL-exposed group. Decreased functional connectivity in the cluster was associated with decreased sleep latency in the BL-exposed group (β = 0.54, p = 0.01).

CONCLUSIONS

Our results suggest that bright light exposure may improve sleep quality in individuals with sleep disturbances by modulating functional connectivity in the salience network.

CLINICAL TRIAL REGISTRATION

https://cris.nih.go.kr/cris; KCT0002607.

Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.