Default Mode Network In Schizophrenia Research Articles

Resting state hyperconnectivity of the default mode network in schizophrenia and clinical high-risk state for psychosis.

Disrupted functional connectivity (FC) of the default mode network (DMN) may have a pathophysiological role in schizophrenia. However, functional magnetic resonance imaging (fMRI) of the DMN in schizophrenia patients has shown inconsistent results. It also remains unclear whether individuals with at-risk mental state (ARMS) have an altered DMN connectivity and whether it is related to clinical characteristics. This fMRI study examined resting-state FCs of the DMN and its relevance to clinical/cognitive variables in 41 schizophrenia patients, 31 ARMS individuals, and 65 healthy controls. Compared with controls, schizophrenia patients had significantly increased FCs within the DMN and between the DMN and diverse cortical areas, whereas ARMS patients had increased FCs only between the DMN and occipital cortex. FC of the lateral parietal cortex with superior temporal gyrus was positively correlated with negative symptoms in schizophrenia, whereas FC of that with interparietal sulcus was negatively correlated with general cognitive impairment in ARMS. Our findings suggest that increased FCs between the DMN and visual network commonly seen in schizophrenia and ARMS subjects may reflect a network-level disturbance representing a general vulnerability to psychosis. In addition, FC changes related to the lateral parietal cortex may underpin clinical characteristics of ARMS and schizophrenia subjects.

Hyperactivity of the default mode network in schizophrenia and free energy: A dialogue between Freudian theory of psychosis and neuroscience.

The economic conceptualization of Freudian metapsychology, based on an energetics model of the psyche's workings, offers remarkable commonalities with some recent discoveries in neuroscience, notably in the field of neuroenergetics. The pattern of cerebral activity at resting state and the identification of a default mode network (DMN), a network of areas whose activity is detectable at baseline conditions by neuroimaging techniques, offers a promising field of research in the dialogue between psychoanalysis and neuroscience. In this article we study one significant clinical application of this interdisciplinary dialogue by looking at the role of the DMN in the psychopathology of schizophrenia. Anomalies in the functioning of the DMN have been observed in schizophrenia. Studies have evidenced the existence of hyperactivity in this network in schizophrenia patients, particularly among those for whom a positive symptomatology is dominant. These data are particularly interesting when considered from the perspective of the psychoanalytic understanding of the positive symptoms of psychosis, most notably the Freudian hypothesis of delusions as an "attempt at recovery." Combining the data from research in neuroimaging of schizophrenia patients with the Freudian hypothesis, we propose considering the hyperactivity of the DMN as a consequence of a process of massive reassociation of traces occurring in schizophrenia. This is a process that may constitute an attempt at minimizing the excess of free energy present in psychosis. Modern models of active inference and the free energy principle (FEP) may shed some light on these processes.

Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study.

Background:Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain.Methods:We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set.Results:Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the “2-back versus 0-back” contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%.Limitations:We used a limited n-back paradigm that precluded the examination of higher working-memory loads.Conclusion:Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.

Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

Multiple neuroimaging studies have examined the relationship between default mode network (DMN) dysconnectivity and schizophrenia symptom severity, and some studies have linked aberrant dynamic functional connectivity (dFC) with schizophrenia (SZ). Nevertheless, the relationship between aberrant DMN dFC and schizophrenia symptom severity has not been well-characterized. In this study, we (1) apply a data-driven approach to partition DMN dFC into five states in a search for abnormal activity and (2) explore the relationship between that abnormal activity and symptom severity.

Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity.

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

Functional disconnection between subsystems of the default mode network in schizophrenia.

A dysfunctional default mode network (DMN) has been reported in patients with schizophrenia. However, the stability of the deficits has not been determined across different stages of the disorder. We examined the functional connectivity of the DMN subsystems of 125 patients with first-episode schizophrenia (FES) or recurrent schizophrenia (RES), compared to that of 82 healthy controls. We tested the robustness of the findings in an independent cohort of 158 patients and 39 healthy controls. We performed resting-state functional connectivity analysis, and examined the strength of the connections within and between the three subsystems of the DMN (core, dorsal medial prefrontal cortex [dMPFC], and medial temporal lobe [MTL]). We also analyzed the connectivity correlations to symptoms and illness duration. We found reduced connectivity strength between the core and MTL subsystems in schizophrenia patients compared to controls, with no differences between the FES and RES patient groups; these findings were validated in the second sample. Schizophrenia patients also showed a significant reduction in connectivity within the MTL and between the dMPFC-MTL subsystems, similarly between FES and RES groups. The connectivity strength within the core subsystem was negatively correlated with clinical symptoms in schizophrenia. There was no significant correlation between the DMN subsystem connectivity and illness duration. DMN subsystem connectivity deficits are present in schizophrenia, and the homochronicity of their appearance indicates the trait-like nature of these alterations. The DMN deficit may be useful for early diagnosis, and MTL dysfunction may be a crucial mechanism underlying schizophrenia.

Transdiagnostic and Illness-Specific Functional Dysconnectivity Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

BackgroundMental disorders are typically defined as distinct diagnostic entities, but similar patterns of clinical and cognitive impairments are frequently found across diagnostic groups. We investigated whether these transdiagnostic deficits result from common neural substrates across disorders or various illness-specific mechanisms, or a combination of both. MethodsFunctional magnetic resonance imaging data were collected from clinically stable patients with major depressive disorder (n = 53), bipolar disorder (n = 78), or schizophrenia (n = 100) and matched healthy control subjects (n = 109) using a single scanner. Group comparisons were conducted to identify transdiagnostic and illness-specific features, and possible confounding effects of medication were considered. A multivariate approach with cross-validation was used to associate dysconnectivity features with shared cognitive deficits. ResultsTransdiagnostic dysconnectivities were identified within somatomotor (Cohen’s d = 0.50–0.58) and salience (Cohen’s d = 0.52–0.58) networks and between subcortical-limbic (Cohen’s d = 0.55–0.69) and subcortical-dorsal attention (Cohen’s d = 0.56–0.61) networks. The executive control network was found to be illness-specifically disconnected from the prefrontal-limbic-pallidal circuit in major depressive disorder (Cohen’s d = 0.57–0.58), prefronto-striato-parietal circuit in bipolar disorder (Cohen’s d = 0.48–0.53), and default mode network in schizophrenia (Cohen’s d = 0.47–0.56). Working memory deficits were associated with a linear combination of 11 transdiagnostic and 5 illness-specific dysconnectivities (r = .322, p= 9.7 × 10−4, n = 340). The associations of the identified dysconnectivities with medication dosage were nonsignificant. ConclusionsDisconnectivity in the somatomotor network was a common transdiagnostic profile, while there were illness-specific patterns in different parts of the prefrontal cortex for different disorders. These findings suggest that prominent psychiatric disorders share common impairments, possibly linked to perception and motor output, as well as unique dysconnectivity profiles that hypothetically mediate the more distinctive features of the disorder-specific psychopathology.

Stronger default mode network connectivity is associated with poorer clinical insight in youth at ultra high-risk for psychotic disorders

Impaired clinical insight (CI) is a common symptom of psychotic disorders and a promising treatment target. However, to date, our understanding of how variability in CI is tied to underlying brain dysfunction in the clinical high-risk period is limited. Developing a stronger conception of this link will be a vital first step for efforts to determine if CI can serve as a useful prognostic indicator. The current study investigated whether variability in CI is related to major brain networks in adolescents and young adults at ultra high-risk (UHR) of developing psychosis. Thirty-five UHR youth were administered structured clinical interviews as well as an assessment for CI and underwent resting-state magnetic resonance imaging scans. Functional connectivity was calculated in the default mode network (DMN) and fronto-parietal network (FPN), two major networks that are dysfunctional in psychosis and are hypothesized to affect insight. Greater DMN connectivity between the posterior cingulate/precuneus and ventromedial prefrontal cortex (DMN) was related to poorer CI (R2=0.399). There were no significant relationships between insight and the FPN. This is the first study to relate a major brain network to clinical insight before the onset of psychosis. Findings are consistent with evidence if a hyperconnected DMN in schizophrenia and UHR, and similar to a previous study of insight and connectivity in schizophrenia. Results suggest that a strongly connected DMN may be related to poor self-awareness of subthreshold psychotic symptoms in UHR adolescents and young adults.

A Review of the Functional and Anatomical Default Mode Network in Schizophrenia.

Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network (DMN), since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.

Network dynamics during the different stages of hallucinations in schizophrenia.

The majority of patients with schizophrenia suffer from hallucinations. While the triple-network model, which includes the default mode network (DMN), the central executive network (CEN) and the salience network (SAL), has recently been applied to schizophrenia, how this framework could explain the emergence of hallucinations remains unclear. Therefore, complementary brain regions that have been linked to hallucinations, such as the left hippocampus, should also be considered and added to this model. Accordingly, the present study explored the effective connectivity across these four components (i.e., the quadripartite model) during the different stages of hallucinations. Twenty-five patients with schizophrenia participated in a single session of resting-state functional magnetic resonance imaging to capture hallucinatory experiences. Based on the participants' self-report of the psychosensory experiences that occurred during scanning, hallucinatory experiences were identified and divided into four stages: periods without hallucination ("OFF"), periods with hallucination ("ON"), transition periods between "OFF" and "ON", and the extinction of the hallucinatory experience ("END"). Using stochastic dynamic causal modeling analysis, this study first confirmed that the SAL played a critical and causal role in switching between the CEN and the DMN in schizophrenia. In addition, effective connectivity within the quadripartite model depended on the hallucinatory stage. In particular, "ON" periods were linked to memory-based sensory input from the hippocampus to the SAL, while "END" periods were associated with a takeover of the CEN in favor of a voluntary process. Finally, the pathophysiological and therapeutic implications of these findings are critically discussed. Hum Brain Mapp 37:2571-2586, 2016. © 2016 Wiley Periodicals, Inc.

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

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

Transdiagnostic commonalities and differences in resting state functional connectivity of the default mode network in schizophrenia and major depression.

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.

Increased short-range and long-range functional connectivity in first-episode, medication-naive schizophrenia at rest

ObjectiveSchizophrenia is conceived as a disconnection syndrome and anatomical distance may affect functional connectivity (FC) in schizophrenia patients. However, whether and how anatomical distance affects FC remains unclear in first-episode, medication-naive schizophrenia at rest. MethodsForty-nine schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent resting-state functional magnetic resonance imaging scanning. Regional FC strength was computed for each voxel in the brain, which was further divided into short-range and long-range FC strength. ResultsThe patients exhibited increased short-range positive FC strength in the left superior medial frontal gyrus, and increased long-range positive FC strength in the right angular gyrus and bilateral posterior cingulate cortex (PCC)/precuneus compared with the controls. Further seed-based FC analysis showed that the left superior medial frontal gyrus had increased short-range FC with the right inferior frontal gyrus, while the right angular gyrus and bilateral PCC/precuneus had increased long-range FC with the prefrontal gyrus. No significant correlation was observed between abnormal FC strength and clinical variables in the patient group. ConclusionsThe findings reveal a pattern of increased anatomical distance affecting FC in the patients, with the results of increased short-range positive FC strength in the anterior default-mode network (DMN) and increased long-range positive FC strength in the posterior DMN in schizophrenia, and highlight the importance of the DMN in the neurobiology of schizophrenia.

Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia

The default mode network (DMN) plays an important role in the physiopathology of schizophrenia. Previous studies have suggested that the cerebellum participates in higher-order cognitive networks such as the DMN. However, the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. In this study, we investigated cerebellar functional connectivity differences between 60 patients with schizophrenia and 60 healthy controls from a public resting-state fMRI database. Seed-based correlation analysis was performed by using seeds from the left Crus I, right Crus I and Lobule IX, which have previously been identified as being involved in the DMN. Our results revealed that, compared with the healthy controls, the patients showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions including the middle frontal gyrus, anterior cingulate cortex, and supplementary motor area. Moreover, the positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity observed in the healthy subjects were diminished in the patients. Our findings implicate disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which may provide further evidence for the “cognitive dysmetria” concept of schizophrenia.

Abnormal default-mode network homogeneity in first-episode, drug-naive schizophrenia at rest

Dysconnectivity hypothesis posits that schizophrenia relates to abnormal resting-state connectivity within the default-mode network (DMN) and this aberrant connectivity is considered as contribution of difficulties in self-referential and introspective processing. However, little is known about the alterations of the network homogeneity (NH) of the DMN in schizophrenia. In the present study, we used an automatic NH method to investigate the NH of the DMN in schizophrenia patients at rest. Forty-nine first-episode, drug-naive schizophrenia patients and 50 age-, gender-, and education-matched healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI). An automated NH approach was used to analyze the data. Patients exhibited lower NH than controls in the left medial prefrontal cortex (MPFC) and the right middle temporal gyrus (MTG). Significantly higher NH values in the left posterior cingulate cortex (PCC) and the right cerebellum Crus I were found in the patient group than in the control group. No significant correlation was found between abnormal NH values and Positive and Negative Symptom Scale (PANSS) scores, duration of untreated psychosis (DUP), age or years of education in the patient group. Our findings suggest that abnormal NH of the DMN exists in first-episode, drug-naive schizophrenia and further highlight the importance of the DMN in the pathophysiology of schizophrenia.

P.3.f.015 Abnormal functioning of the default mode network in schizophrenia and unaffected relatives: a study of functional magnetic resonance

P.3.f.015 Abnormal functioning of the default mode network in schizophrenia and unaffected relatives: a study of functional magnetic resonance