Are anticorrelated networks in the brain relevant to schizophrenia?

Effects of escitalopram therapy on effective connectivity among core brain networks in major depressive disorder

BACKGROUND

Patients with major depressive disorder (MDD) have abnormal functional interaction among large-scale brain networks, indicated by aberrant effective connectivity of the default mode network (DMN), salience network (SN), and dorsal attention network (DAN). However, it remains unclear whether antidepressants can normalize the altered effective connectivity in MDD.

METHODS

In this study, we collected resting-state functional magnetic resonance imaging data from 46 unmedicated patients with MDD at baseline and after 12 weeks of escitalopram treatment. We also collected data from 58 healthy controls (HCs) at the same time point with the same interval. Using spectral dynamic causal modeling and parametric empirical Bayes, we examined group differences, time effect and their interaction on the casual interactions among the regions of interest in the three networks.

RESULTS

Compared with HCs, patients with MDD showed increased positive (excitatory) connections within the DMN, decreased positive connections within the SN and DAN, decreased absolute value of negative (inhibitory) connectivity from the SN and DAN to the DMN, and decreased positive connections between the DAN and the SN. Furthermore, we found that six connections related to the DAN showed decreased group differences in effective connectivity between MDD and HCs during follow-up compared to the baseline.

CONCLUSIONS

Our findings suggest that escitalopram therapy can partly improve the disrupted effective connectivity among high-order brain functional networks in MDD. These findings deepened our understanding of the neural basis of antidepressants' effect on brain function in patients with MDD.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Clustering of antipsychotic-naïve patients with schizophrenia based on functional connectivity from resting-state electroencephalography

Schizophrenia is associated with aberrations in the Default Mode Network (DMN), but the clinical implications remain unclear. We applied data-driven, unsupervised machine learning based on resting-state electroencephalography (rsEEG) functional connectivity within the DMN to cluster antipsychotic-naïve patients with first-episode schizophrenia. The identified clusters were investigated with respect to psychopathological profile and cognitive deficits. Thirty-seven antipsychotic-naïve, first-episode patients with schizophrenia (mean age 24.4 (5.4); 59.5% males) and 97 matched healthy controls (mean age 24.0 (5.1); 52.6% males) underwent assessments of rsEEG, psychopathology, and cognition. Source-localized, frequency-dependent functional connectivity was estimated using Phase Lag Index (PLI). The DMN-PLI was factorized for each frequency band using principal component analysis. Clusters of patients were identified using a Gaussian mixture model and neurocognitive and psychopathological profiles of identified clusters were explored. We identified two clusters of patients based on the theta band (4-8 Hz), and two clusters based on the beta band (12-30 Hz). Baseline psychopathology could predict theta clusters with an accuracy of 69.4% (p = 0.003), primarily driven by negative symptoms. Five a priori selected cognitive functions conjointly predicted the beta clusters with an accuracy of 63.6% (p = 0.034). The two beta clusters displayed higher and lower DMN connectivity, respectively, compared to healthy controls. In conclusion, the functional connectivity within the DMN provides a novel, data-driven means to stratify patients into clinically relevant clusters. The results support the notion of biological subgroups in schizophrenia and endorse the application of data-driven methods to recognize pathophysiological patterns at earliest stage of this syndrome.

Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis

INTRODUCTION

High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders.

METHODS

Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R.

RESULTS

Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition.

CONCLUSION

These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.

Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease

Background: Alzheimer's disease (AD) is the most common age-related dementia that promotes a decline in memory, thinking, and social skills. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent work has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this work has primarily used static functional connectivity (sFC) from resting-state functional magnetic resonance imaging. Recently, dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations. Methods: Group independent component analysis was applied to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of AD symptomology. We estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states, and then estimated a hidden Markov model and the occupancy rate for each subject. Then, we investigated the link between CCN dFC features and AD progression. Also, we investigated the link between sFC and AD progression and compared its results with dFC results. Results: Progression of AD symptoms was associated with increases in connectivity within the middle frontal gyrus. Also, the very mild AD (vmAD) showed less connectivity within the inferior parietal lobule (in both sFC and dFC) and between this region and the rest of CCN (in dFC analysis). Also, we found that within-middle frontal gyrus connectivity increases with AD progression in both sFC and dFC results. Finally, comparing with vmAD, we found that the normal brain spends significantly more time in a state with lower within-middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity in this disease. Conclusion: Our results suggest that AD progress not only alters the CCN connectivity strength but also changes the temporal properties in this brain network. This suggests the temporal and spatial pattern of CCN as a biomarker that differentiates different stages of AD.

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

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

Association of default-mode network neurotransmitters and inter-network functional connectivity in first episode psychosis

Multiple psychiatric disorders are characterized by a failure to suppress default-mode network (DMN) activity during tasks and by weaker anti-correlations between DMN and other brain networks at rest. However, the cellular and molecular mechanisms underlying this phenomenon are poorly understood. At the cellular level, neuronal activity is regulated by multiple neurochemical processes including cycling of glutamate and GABA, the major excitatory and inhibitory neurotransmitters in brain. By combining functional MRI and magnetic resonance spectroscopy techniques, it has been shown that the neurotransmitter concentrations in DMN modulate not only functional activity during cognitive tasks, but also the functional connectivity between DMN and other brain networks such as frontoparietal executive control network (CN) at rest in the healthy brain. In the current study, we extend previous research to first episode psychosis (FEP) patients and their relatives. We detected higher glutamate (Glu) levels in the medial prefrontal cortex (MPFC) in FEP compared to healthy controls without a significant difference in GABA. We also observed a significantly lower functional anti-correlated connectivity between critical nodes within the DMN (MPFC) and CN (DLPFC) in FEP. Furthermore, the relationship between MPFC Glu and GABA concentrations and the functional anti-correlation that is seen in healthy people was absent in FEP patients. These findings imply that both the DMN Glu level and the interaction between DMN and CN are affected by the illness, as is the association between neurochemistry and functional connectivity. A better understanding of this observation could provide opportunities for developing novel treatment strategies for psychosis.

Effective Connectivity Between the Orbitofrontal Cortex and the Precuneus Differentiates Major Psychiatric Disorders: Results from a Transdiagnostic Spectral DCM Study

BACKGROUND & OBJECTIVE

We have previously identified aberrant connectivity of the left precuneus, ventrolateral prefrontal cortex, anterior cingulate cortex, and anterior insula in patients with either a paranoid (schizophrenia), or a depressive syndrome (both unipolar and bipolar). In the current study, we attempted to replicate and expand these findings by including a healthy control sample and separating the patients in a depressive episode into two groups: unipolar and bipolar depression. We hypothesized that the connections between those major nodes of the resting state networks would demonstrate different patterns in the three patient groups compared to the healthy subjects.

METHODS

Resting-state functional MRI was performed on a sample of 101 participants, of which 26 patients with schizophrenia (current psychotic episodes), 24 subjects with Bipolar Disorder (BD), 33 with Major Depressive Disorder (MDD) (both BD and MDD patients were in a current depressive episode), and 21 healthy controls. Spectral Dynamic Causal Modeling was used to calculate the coupling values between eight regions of interest, including the anterior precuneus (PRC), anterior hippocampus, anterior insula, angular gyrus, lateral Orbitofrontal Cortex (OFC), middle frontal gyrus, planum temporale, and anterior thalamus.

RESULTS & CONCLUSION

We identified disturbed effective connectivity from the left lateral orbitofrontal cortex to the left anterior precuneus that differed significantly between unipolar depression, where the influence was inhibitory, and bipolar depression, where the effect was excitatory. A logistic regression analysis correctly classified 75% of patients with unipolar and bipolar depression based solely on the coupling values of this connection. In addition, patients with schizophrenia demonstrated negative effective connectivity from the anterior PRC to the lateral OFC, which distinguished them from healthy controls and patients with major depression. Future studies with unmedicated patients will be needed to establish the replicability of our findings.

Abnormalities in visual cognition and associated impaired interactions between visual and attentional networks in schizophrenia and brief psychotic disorder

The extent and nature of cognitive impairment in brief psychotic disorder remains unclear, being rarely studied unlike schizophrenia. The present study hence sought to directly compare the visual cognitive dysfunction and its associated brain networks in brief psychotic disorder and schizophrenia. Data from picture completion (a complex visual task) and whole-brain functional connectome from resting-state fMRI were acquired from a sample of clinically stable patients with an established psychotic disorder (twenty with brief psychotic disorder, twenty with schizophrenia) and twenty-nine healthy controls. Group differences and the inter-relationships in task performances and brain networks were tested. Picture completion task deficits were found in brief psychotic disorder compared with healthy controls, though the deficits were less than schizophrenia. Task performance also correlated with severity of psychotic symptoms in patients. The task performance was inversely correlated with the functional connectivity between peripheral visual and attentional networks (dorsal attention and salience ventral attention), with increased functional connectivity in brief psychotic disorder compared with healthy controls and in schizophrenia compared with brief psychotic disorder. Present findings showed pronounced visual cognitive impairments in brief psychotic disorder that were worse in schizophrenia, underpinned by abnormal interactions between higher-order attentional and lower-order visual processing networks.

A neural mechanism underlying predictive visual motion processing in patients with schizophrenia

Psychotic symptoms may be traced back to sensory sensitivity. Thereby, visual motion (VM) processing particularly has been suggested to be impaired in schizophrenia (SCZ). In healthy brains, VM underlies predictive processing within hierarchically structured systems. However, less is known about predictive VM processing in SCZ. Therefore, we performed fMRI during a VM paradigm with three conditions of varying predictability, i.e., Predictable-, Random-, and Arbitrary motion. The study sample comprised 17 SCZ patients and 23 healthy controls. We calculated general linear model (GLM) analysis to assess group differences in VM processing across motion conditions. Here, we identified significantly lower activity in right temporoparietal junction (TPJ) for SCZ patients. Therefore, right TPJ was set as seed for connectivity analyses. For patients, across conditions we identified increased connections to higher regions, namely medial prefrontal cortex, or paracingulate gyrus. Healthy subjects activated sensory regions as area V5, or superior parietal lobule. Reduced TPJ activity may reflect both a failure in the bottom-up flow of visual information and a decrease of signal processing as consequence of increased top-down input from frontal areas. In sum, these altered neural patterns provide a framework for future studies focusing on predictive VM processing to identify potential biomarkers of psychosis.

Kinesthesia and Temporal Experience: On the 'Knitting and Unknitting' Process of Bodily Subjectivity in Schizophrenia

This paper proposes a phenomenological hypothesis that psychosis entails a disturbance of the two-fold process of the indication function of kinesthesia and the presentification function of touch that affects the constitution of bodily subjectivity. Recent functional connectivity studies showed that the increased synchrony between the right anterior insula and the default mode network are associated with psychosis. This association is proposed to be correlated with the disrupted dynamics between the pre-reflective and reflective temporal experience in psychotic patients. The paper first examines the dynamic nature of kinesthesia and the influence touch and vision exert on it, and then the reciprocal influence with temporal experience focusing on the body's cyclic sense of temporality and its impact on physiology and phenomenology. Affectivity and self-affection are considered in their basic bodily expressions mainly through the concepts of responsivity and receptivity. The overall constitutive processes referred to throughout the article are proposed as a roadmap to develop body-based therapeutic work.

Potential Locations for Non-Invasive Brain Stimulation in Treating Schizophrenia: A Resting-State Functional Connectivity Analysis

Introduction: Non-invasive brain stimulation (NIBS) techniques have been widely used for the purpose of improving clinical symptoms of schizophrenia. However, the ambiguous stimulation targets may limit the efficacy of NIBS for schizophrenia. Exploring effective stimulation targets may improve the clinical efficacy of NIBS in schizophrenia.

Methods: We first conducted a neurosynth-based meta-analysis of 715 functional magnetic resonance imaging studies to identify schizophrenia-related brain regions as regions of interest. Then, we performed the resting-state functional connectivity analysis in 32 patients with first-episode schizophrenia to find brain surface regions correlated with the regions of interest in three pipelines. Finally, the 10–20 system coordinates corresponding to the brain surface regions were considered as potential targets for NIBS.

Results: We identified several potential targets of NIBS, including the bilateral dorsal lateral prefrontal cortex, supplementary motor area, bilateral inferior parietal lobule, temporal pole, medial prefrontal cortex, precuneus, superior and middle temporal gyrus, and superior and middle occipital gyrus. Notably, the 10-20 system location of the bilateral dorsal lateral prefrontal cortex was posterior to F3 (F4), not F3 (F4).

Conclusion: Conclusively, our findings suggested that the stimulation locations corresponding to these potential targets might help clinicians optimize the application of NIBS therapy in individuals with schizophrenia.

Differential aberrant connectivity of precuneus and anterior insula may underpin the diagnosis of schizophrenia and mood disorders

BACKGROUND

Over the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has concentrated on brain networks such as the default mode network (DMN), the salience network (SN), and the central executive network (CEN), allowing for a better understanding of cognitive deficits observed in mental disorders, as well as other characteristic psychopathological phenomena such as thought and behavior disorganization.

AIM

To investigate differential patterns of effective connectivity across distributed brain networks involved in schizophrenia (SCH) and mood disorders.

METHODS

The sample comprised 58 patients with either paranoid syndrome in the context of SCH (n = 26) or depressive syndrome (Ds) (n = 32), in the context of major depressive disorder or bipolar disorder. The methods used include rs-fMRI and subsequent dynamic causal modeling to determine the direction and strength of connections to and from various nodes in the DMN, SN and CEN.

RESULTS

A significant excitatory connection from the dorsal anterior cingulate cortex to the anterior insula (aI) was observed in the SCH patient group, whereas inhibitory connections from the precuneus to the ventrolateral prefrontal cortex and from the aI to the precuneus were observed in the Ds group.

CONCLUSION

The results delineate specific patterns associated with SCH and Ds and offer a better explanation of the underlying mechanisms of these disorders, and inform differential diagnosis and precise treatment targeting.

Resting-state functional connectivity predictors of treatment response in schizophrenia - A systematic review and meta-analysis

We aimed to systematically synthesize and quantify the utility of pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI) in predicting antipsychotic response in schizophrenia. We searched the PubMed/MEDLINE database for studies that examined the magnitude of association between baseline rs-fMRI assessment and subsequent response to antipsychotic treatment in persons with schizophrenia. We also performed meta-analyses for quantifying the magnitude and accuracy of predicting response defined continuously and categorically. Data from 22 datasets examining 1280 individuals identified striatal and default mode network functional segregation and integration metrics as consistent determinants of treatment response. The pooled correlation coefficient for predicting improvement in total symptoms measured continuously was ~0.47 (12 datasets; 95% CI: 0.35 to 0.59). The pooled odds ratio of predicting categorically defined treatment response was 12.66 (nine datasets; 95% CI: 7.91-20.29), with 81% sensitivity and 76% specificity. rs-fMRI holds promise as a predictive biomarker of antipsychotic treatment response in schizophrenia. Future efforts need to focus on refining feature characterization to improve prediction accuracy, validate prediction models, and evaluate their implementation in clinical practice.

Pharmaco-Magnetic Resonance as a Tool for Monitoring the Medication-Related Effects in the Brain May Provide Potential Biomarkers for Psychotic Disorders

The neurodegenerative and neurodevelopmental hypotheses represent the basic etiological framework for the origin of schizophrenia. Additionally, the dopamine hypothesis, adopted more than two decades ago, has repeatedly asserted the position of dopamine as a pathobiochemical substrate through the action of psychostimulants and neuroleptics on the mesolimbic and mesocortical systems, giving insight into the origin of positive and negative schizophrenic symptoms. Meanwhile, cognitive impairments in schizophrenia remain incompletely understood but are thought to be present during all stages of the disease, as well as in the prodromal, interictal and residual phases. On the other hand, observations on the effects of NMDA antagonists, such as ketamine and phencyclidine, reveal that hypoglutamatergic neurotransmission causes not only positive and negative but also cognitive schizophrenic symptoms. This review aims to summarize the different hypotheses about the origin of psychoses and to identify the optimal neuroimaging method that can serve to unite them in an integral etiological framework. We systematically searched Google scholar (with no concern to the date published) to identify studies investigating the etiology of schizophrenia, with a focus on impaired central neurotransmission. The complex interaction between the dopamine and glutamate neurotransmitter systems provides the long-needed etiological concept, which combines the neurodegenerative hypothesis with the hypothesis of impaired neurodevelopment in schizophrenia. Pharmaco-magnetic resonance imaging is a neuroimaging method that can provide a translation of scientific knowledge about the neural networks and the disruptions in and between different brain regions, into clinically applicable and effective therapeutic results in the management of severe psychotic disorders.

Triple network hypothesis-related disrupted connections in schizophrenia: A spectral dynamic causal modeling analysis with functional magnetic resonance imaging

OBJECTIVE

The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients.

METHODS

We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS).

RESULTS

We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS.

CONCLUSIONS

Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.

Bioenergetics and abnormal functional connectivity in psychotic disorders

Psychotic Disorders such as schizophrenia (SZ) and bipolar disorder (BD) are characterized by abnormal functional connectivity (FC) within neural networks such as the default mode network (DMN), as well as attenuated anticorrelation between DMN and task-positive networks (TPN). Bioenergetic processes are critical for synaptic connectivity and are also abnormal in psychotic disorders. We therefore examined the association between brain energy metabolism and FC in psychotic disorders. ³¹P magnetization transfer spectroscopy from medial prefrontal cortex (MPFC) and whole-brain fMRI data were collected from demographically matched groups of SZ, BD, and healthy control (HC) subjects. The creatine kinase (CK) reaction flux calculated from spectroscopy was used as an index of regional energy production rate. FC maps were generated with MPFC as the seed region. Compared to HC, SZ showed significantly lower CK flux, while both BD and SZ patients showed decreased anticorrelation between MPFC and TPN. CK flux was significantly correlated with FC between MPFC and other DMN nodes in HC. This positive correlation was reduced modestly in BD and strongly in SZ. CK flux was negatively correlated with the anticorrelation between MPFC and TPN in HC, but this relationship was not observed in BD or SZ. These results indicate that MPFC energy metabolism rates are associated with stronger FC within networks and stronger anticorrelation between networks in HC. However, this association is decreased in SZ and BD, where bioenergetic and FC abnormalities are evident. This pattern may suggest that impairment in energy production in psychotic disorders underlies the impaired neural connectivity.

Hallucinations Under Psychedelics and in the Schizophrenia Spectrum: An Interdisciplinary and Multiscale Comparison

The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research.

Distinct striatum pathways connected to salience network predict symptoms improvement and resilient functioning in schizophrenia following risperidone monotherapy

Abnormal interactions between the striatum and salience network (SN) are considered as etiological and treatment-sensitive marker in schizophrenia. However, whether alterations in the intrinsic dynamics as reflected by resting-state functional connectivity (RSFC) between the striatum and salience network may predict treatment response to the widely used antipsychotic treatment strategies (risperidone, monotherapy) has not been examined systematically. To this end, treatment-naive first-episode schizophrenia patients (n = 41) underwent task-free resting-state fMRI assessment before (baseline) and after 8 weeks of risperidone monotherapy (n = 38). Intrinsic connectivity between striatal sub-regions and core salience processing nodes were examined and compared to carefully matched healthy controls (HC) to determine disorder-specific and treatment-predictive neural markers. Findings demonstrate hypo-connectivity of both ventral and dorsal striatal-SN pathways in patients at baseline. Importantly, specifically the dorsal striatal pathway at baseline could predict negative symptoms improvement in patients; while ventral striatal pathways could predict positive symptoms improvement. Together, results indicate that distinct striatal-SN pathways represent specific treatment-success markers for the effects of risperidone, suggesting that alterations in dorsal versus ventral striatal network markers may represent brain-based markers for specific symptomatologic improvements following risperidone mono-therapy.

The Modulatory Effect of Cerebrovascular Burden in Response to Cognitive Stimulation in Healthy Ageing and Mild Cognitive Impairment

Background

Cerebrovascular burden is a common pathology in mild cognitive impairment (MCI) and Alzheimer's disease (AD), with an additive impact on cognitive functioning. Despite being proposed as a potential moderator of cholinesterase inhibiting drug therapy, there is a paucity of evidence investigating the impact of cerebrovascular pathology on responsiveness to cognitive interventions.

Method

The current study uses neuropsychological, neurostructural, and functional connectivity indices to characterise response to a cognitive stimulation paradigm in 25 healthy ageing and 22 MCI participants, to examine the hypothesised detrimental effects of concurrent vascular pathology.

Results

In both healthy ageing and MCI, increased levels of vascular pathology limited the potential for a neuroplastic response to cognitive stimulation. In healthy ageing, participants with lower levels of vascular burden had greater functional connectivity response in the target posterior default mode network. Those with low levels of vascular pathology in the MCI cohort had increased functional connectivity of the right insula and claustrum within the salience network. Burden did not, however, predict cognitive or neuroanatomical changes.

Conclusions

The current research evidences the modulatory effect of cerebrovascular pathology in interventions aimed at re-establishing network connectivity to prevent cognitive deterioration and delay the transition to the dementia stage of AD. Examination of co-occurring vascular pathology may improve precision in targeting treatment to MCI candidates who may respond optimally to such cognitive interventions.

Common and distinct changes of default mode and salience network in schizophrenia and major depression

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Data-driven approaches for identifying links between brain structure and function in health and disease

Brain imaging technology provides a powerful tool to visualize the living human brain, provide insights into disease mechanisms, and potentially provide a tool to assist clinical decision-making. The brain has a very specific structural substrate providing a foundation for functional information; however, most studies ignore the very interesting and complex relationships between brain structure and brain function. While a variety of approaches have been used to study how brain structure informs function, the study of such relationships in living humans in most cases is limited to noninvasive approaches at the macroscopic scale. The use of data-driven approaches to link structure and function provides a tool which is especially important at the macroscopic scale at which we can study the human brain. This paper reviews data-driven approaches, with a focus on independent component analysis approaches, which leverage higher order statistics to link together macroscopic structural and functional MRI data. Such approaches provide the benefit of allowing us to identify links which do not necessarily correspond spatially (eg, structural changes in one region related to functional changes in other regions). They also provide a "network level" perspective on the data, by enabling us to identify sets of brain regions that covary together. This also opens up the ability to evaluate both within and between network relationships. A variety of examples are presented, including several showing the potential of such approaches to inform us about mental illness, particularly about schizophrenia.

Alterations of Intrinsic Connectivity Networks in Antipsychotic-Naïve First-Episode Schizophrenia

BACKGROUND

The investigation of large-scale intrinsic connectivity networks in antipsychotic-naïve first-episode schizophrenia increases our understanding of system-level cerebral dysfunction in schizophrenia while enabling control of confounding effects of medication and disease progression. Reports on functional connectivity in antipsychotic-naïve patients have been mixed and the relation between network alterations, psychopathology and cognition is unclear.

METHODS

A total number of 47 patients with first-episode schizophrenia who had never received antipsychotic medication and 47 healthy controls were scanned with functional magnetic resonance imaging under resting conditions. Main outcome measures were differences in functional connectivity between groups and the relationship between network alterations, psychopathology and cognition.

RESULTS

Altered connectivity was found between right central executive network (CEN) and right ventral attention network (VAN) (patients > controls, P = .001), left CEN and left VAN (P = .002), and between posterior default mode network and auditory network (P = .006). Association between network connectivity and clinical characteristics was found as interactions between the effects of group and sustained attention (P = .005) and between group and processing speed (P = .007) on the connectivity between right CEN and right VAN.

CONCLUSIONS

Our findings suggest that the early phase of schizophrenia is characterized by increased connectivity between fronto-parietal networks suggested to be involved in the control of cognitive and sensory functions. Moreover, the present study suggests that the problem of not disengaging the VAN leads to difficulties with attention and possibly subjective awareness.

Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Cognitive impairment is a feature of many psychiatric diseases, including schizophrenia. Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive performance in individuals with schizophrenia and healthy controls. A supervised learning strategy is used to guide three-way multimodal magnetic resonance imaging (MRI) fusion in two independent cohorts including both healthy individuals and individuals with schizophrenia using multiple cognitive domain scores. Results highlight the salience network (gray matter, GM), corpus callosum (fractional anisotropy, FA), central executive and default-mode networks (fractional amplitude of low-frequency fluctuation, fALFF) as modality-specific biomarkers of generalized cognition. FALFF features are found to be more sensitive to cognitive domain differences, while the salience network in GM and corpus callosum in FA are highly consistent and predictive of multiple cognitive domains. These modality-specific brain regions define-in three separate cohorts-promising co-varying multimodal signatures that can be used as predictors of multi-domain cognition.

Data-driven approaches for identifying links between brain structure and function in health and disease

Brain imaging technology provides a powerful tool to visualize the living human brain, provide insights into disease mechanisms, and potentially provide a tool to assist clinical decision-making. The brain has a very specific structural substrate providing a foundation for functional information; however, most studies ignore the very interesting and complex relationships between brain structure and brain function. While a variety of approaches have been used to study how brain structure informs function, the study of such relationships in living humans in most cases is limited to noninvasive approaches at the macroscopic scale. The use of data-driven approaches to link structure and function provides a tool which is especially important at the macroscopic scale at which we can study the human brain. This paper reviews data-driven approaches, with a focus on independent component analysis approaches, which leverage higher order statistics to link together macroscopic structural and functional MRI data. Such approaches provide the benefit of allowing us to identify links which do not necessarily correspond spatially (eg, structural changes in one region related to functional changes in other regions). They also provide a "network level" perspective on the data, by enabling us to identify sets of brain regions that covary together. This also opens up the ability to evaluate both within and between network relationships. A variety of examples are presented, including several showing the potential of such approaches to inform us about mental illness, particularly about schizophrenia.

Multilocus genetic profile in dopaminergic pathway modulates the striatum and working memory

Dopamine is critical in pathophysiology and therapy of schizophrenia. Many studies have reported altered dopaminergic activity in the dorsal but not ventral striatum in schizophrenia. Based on the largest genome-wide association study of schizophrenia to date, we calculated the polygenic risk score (PGRS) of each subject in a healthy general group, including all variations in the set of functionally related genes involved in dopamine neurotransmitter system. We aimed to test whether the genetic variations in the dopaminergic pathway that have been identified as associated with schizophrenia are related to the function of the striatum and to working memory. We found that a higher PGRS was significantly associated with impairment in working memory. Moreover, resting-state functional connectivity analysis revealed that as the polygenic risk score increased, the connections between left putamen and caudate and the default mode network grew stronger, while the connections with the fronto-parietal network grew weaker. Our findings may shed light on the biological mechanism underlying the “dopamine hypothesis” of schizophrenia and provide some implications regarding the polygenic effects on the dopaminergic activity in the risk for schizophrenia.

The Hierarchical Organization of the Default, Dorsal Attention and Salience Networks in Adolescents and Young Adults

An important characteristic of spontaneous brain activity is the anticorrelation between the core default network (cDN) and the dorsal attention network (DAN) and the salience network (SN). This anticorrelation may constitute a key aspect of functional anatomy and is implicated in several brain disorders. We used dynamic causal modeling to assess the hypothesis that a causal hierarchy underlies this anticorrelation structure, using resting-state fMRI of healthy adolescent and young adults (N = 404). Our analysis revealed an asymmetric effective connectivity, such that the regions in the SN and DAN exerted an inhibitory influence on the cDN regions; whereas the cDN exerted an excitatory influence on the SN and DAN regions. The relative strength of efferent versus afferent connections places the SN at the apex of the hierarchy, suggesting that the SN modulates anticorrelated networks with descending hierarchical connections. In short, this study of directed neuronal coupling reveals a causal hierarchical architecture that generates or orchestrates anticorrelation of brain activity. These new findings shed light on functional integration of intrinsic brain networks at rest and speak to future dynamic causal modeling studies of large-scale networks.

Aberrant spontaneous neural activity and correlation with evoked-brain potentials in first-episode, treatment-naïve patients with deficit and non-deficit schizophrenia

The goals of the study were to analyze spontaneous neural activity between deficit and non-deficit schizophrenia (DS, NDS) using resting-state fMRI, and to investigate the correlation of fMRI with clinical features and evoked brain potentials. The amplitude of low frequency fluctuation (ALFF) was measured in 41 DS participants, 42 NDS participants, and 42 healthy controls. ALFF in the bilateral cerebellum posterior lobe was significantly decreased in patients, while ALFF in the right fusiform gyrus and the bilateral putamen was significantly increased. In schizophrenia patients, ALFF in the right putamen positively correlated with excited/activation on Positive and Negative Syndrome Scale (PANSS-EXC/ACT). In DS patients, ALFF in the right insula was significantly increased than in controls and positively correlated with S2-P50 amplitude of sensory gating P50. ALFF in the left cerebellum posterior lobe negatively correlated with negative symptoms and withdrawn on PANSS (PANSS-NS, PANSS-WIT), ALFF in the right putamen positively correlated with PANSS-WIT. In NDS patients, ALFF in the middle temporal gyrus decreased than in controls and negatively correlated with P3b subcomponent of P300 latency. ALFF in the left cerebellum posterior lobe negatively correlated with PANSS-EXC/ACT. The middle temporal gyrus in NDS or the right insula in DS may show spatiotemporal defects.

Network-Level Dysconnectivity in Drug-Naïve First-Episode Psychosis: Dissociating Transdiagnostic and Diagnosis-Specific Alterations

The neuroimaging literature provides compelling evidence for functional dysconnectivity in people with psychosis. However, it is likely that at least some of the observed alterations represent secondary effects of illness chronicity and/or antipsychotic medication. In addition, the extent to which these alterations are specific to psychosis or represent a transdiagnostic feature of psychiatric illness remains unclear. The aim of this study was therefore to examine the diagnostic specificity of functional dysconnectivity in drug-naïve first-episode psychosis (FEP). We used resting-state functional magnetic resonance imaging and functional connectivity analysis to estimate network-level connectivity in 50 patients with FEP, 50 patients with major depressive disorder (MDD), 50 patients with post-traumatic stress disorder (PTSD), and 122 healthy controls (HCs). The FEP, MDD, and PTSD groups showed reductions in intranetwork connectivity of the default mode network relative to the HC group (p<0.05 corrected); therefore, intranetwork alterations were expressed across the three diagnostic groups. In addition, the FEP group showed heightened internetwork connectivity between the default mode network, particularly the anterior cingulate cortex, and the central executive network relative to the MDD, PTSD, and HC groups (p<0.05 corrected); therefore, internetwork alterations were specific to the FEP. These findings suggest that network-level alterations are present in individuals with a first episode of psychosis who have not been exposed to antipsychotic medication. In addition, they suggest a dissociation between aberrant internetwork connectivity as a distinctive feature of psychosis and aberrant intranetwork connectivity as a transdiagnostic feature of psychiatric illness.

Neurometabolic abnormalities in schizophrenia and depression observed with magnetic resonance spectroscopy at 7 T

BACKGROUND

Examining neurometabolic abnormalities in critical brain areas in schizophrenia and major depressive disorder (MDD) may help guide future pharmacological interventions including glutamate-modulating treatments.

AIMS

To measure metabolite concentrations within the anterior cingulate cortex (ACC) and thalamus of people with schizophrenia and people with MDD.

METHODS

Spectra were acquired from 16 volunteers with schizophrenia, 17 with MDD and 18 healthy controls using magnetic resonance spectroscopy on a 7 Tesla scanner.

RESULTS

In the thalamus, there were lower glycine concentrations in the schizophrenia group relative to control (P=0.017) and MDD groups (P=0.012), and higher glutamine concentrations relative to healthy controls (P=0.009). In the thalamus and the ACC, the MDD group had lower myo-inositol concentrations than the control (P=0.014, P=0.009, respectively) and schizophrenia (P=0.004, P=0.002, respectively) groups.

CONCLUSION

These results support the glutamatergic theory of schizophrenia and indicate a potential glycine deficiency in the thalamus. In addition, reduced myo-inositol concentrations in MDD suggest its involvement in the disorder.

DECLARATION OF INTEREST

None.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

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.

Disrupted salience network functional connectivity and white-matter microstructure in persons at risk for psychosis: findings from the LYRIKS study

BACKGROUND

Salience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression.

METHOD

We examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis.

RESULTS

ARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years.

CONCLUSIONS

Our findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.

Altered functional and effective connectivity in anticorrelated intrinsic networks in children with benign childhood epilepsy with centrotemporal spikes

There are 2 intrinsic networks in the human brain: the task positive network (TPN) and task negative network (alternately termed the default mode network, DMN) in which inverse correlations have been observed during resting state and event-related functional magnetic resonance imaging (fMRI). The antagonism between the 2 networks might indicate a dynamic interaction in the brain that is associated with development.To evaluate the alterations in the relations of the 2 networks in children with benign childhood epilepsy with centrotemporal spikes (BECTS), resting state fMRI was performed in 17 patients with BECTS and 17 healthy controls. The functional and effective connectivities of 29 nodes in the TPN and DMN were analyzed. Positive functional connectivity (FC) within the networks and negative FC between the 2 networks were observed in both groups.The patients exhibited increased FC within both networks, particularly in the frontoparietal nodes such as the left superior frontal cortex, and enhanced antagonism between the 2 networks, suggesting abnormal functional integration of the nodes of the 2 networks in the patients. Granger causality analysis revealed a significant difference in the degree of outflow to inflow in the left superior frontal cortex and the left ventral occipital lobe.The alterations observed in the combined functional and effective connectivity analyses might indicate an association of an abnormal ability to integrate information between the DMN and TPN and the epileptic neuropathology of BECTS and provide preliminary evidence supporting the occurrence of abnormal development in children with BECTS.

Abnormal gray matter volume and resting-state functional connectivity in former heroin-dependent individuals abstinent for multiple years

Previous studies have suggested that heroin addiction is associated with structural and functional brain abnormalities. However, it is largely unknown whether these characteristics of brain abnormalities would be persistent or restored after long periods of abstinence. Considering the very high rates of relapse, we hypothesized that there may exist some latent neural vulnerabilities in abstinent heroin users. In this study, structural and resting-state functional magnetic resonance imaging data were collected from 30 former heroin-dependent (FHD) subjects who were drug free for more than 3 years and 30 non-addicted control (CN) volunteers. Voxel-based morphometry was used to identify possible gray matter volume differences between the FHD and CN groups. Alterations in resting-state functional connectivity in FHD were examined using brain areas with gray matter deficits as seed regions. Significantly reduced gray matter volume was observed in FHD in an area surrounding the parieto-occipital sulcus, which included the precuneus and cuneus. Functional connectivity analyses revealed that the FHD subjects showed reduced positive correlation within the default mode network and visual network and decreased negative correlation between the default mode network, visual network and task positive network. Moreover, the altered functional connectivity was correlated with self-reported impulsivity scores in the FHD subjects. Our findings suggest that disruption of large-scale brain systems is present in former heroin users even after multi-year abstinence, which could serve as system-level neural underpinnings for behavioral dysfunctions associated with addiction.

Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models

Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls.

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects.

On the existence of a generalized non-specific task-dependent network

In this paper we suggest the existence of a generalized task-related cortical network that is up-regulated whenever the task to be performed requires the allocation of generalized non-specific cognitive resources, independent of the specifics of the task to be performed. We have labeled this general purpose network, the extrinsic mode network (EMN) as complementary to the default mode network (DMN), such that the EMN is down-regulated during periods of task-absence, when the DMN is up-regulated, and vice versa. We conceptualize the EMN as a cortical network for extrinsic neuronal activity, similar to the DMN as being a cortical network for intrinsic neuronal activity. The EMN has essentially a fronto-temporo-parietal spatial distribution, including the inferior and middle frontal gyri, inferior parietal lobule, supplementary motor area, inferior temporal gyrus. We hypothesize that this network is always active regardless of the cognitive task being performed. We further suggest that failure of network up- and down-regulation dynamics may provide neuronal underpinnings for cognitive impairments seen in many mental disorders, such as, e.g., schizophrenia. We start by describing a common observation in functional imaging, the close overlap in fronto-parietal activations in healthy individuals to tasks that denote very different cognitive processes. We now suggest that this is because the brain utilizes the EMN network as a generalized response to tasks that exceeds a cognitive demand threshold and/or requires the processing of novel information. We further discuss how the EMN is related to the DMN, and how a network for extrinsic activity is related to a network for intrinsic activity. Finally, we discuss whether the EMN and DMN networks interact in a common single brain system, rather than being two separate and independent brain systems.

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations.

Structural abnormalities in schizophrenia: further evidence on the key role of the anterior cingulate cortex

OBJECTIVE

The present study examined whole-brain structural abnormalities in schizophrenia, with a special focus on the anterior and posterior cingulate cortex (ACC, PCC) as this is an understudied issue in schizophrenia.

METHOD

Whole-brain voxel-based morphometry analyses of gray matter (GM) and white matter (WM) were performed to detect volumetric differences between 14 patients with schizophrenia and 14 healthy controls matched for age, sex, educational level and parents' educational level. We examined within-group GM and WM correlations and completed the analysis with measurements of sulci in medial cortical areas.

RESULTS

Compared with the healthy controls, the schizophrenic patients showed significant decreases in GM volumes in the ACC and PCC, and in neighboring WM regions such as the corpus callosum and the fimbriae of the fornix. Moreover, the patient group also displayed a negative correlation between volumes of GM and WM in the ACC. Finally, the patients showed significantly reduced volumes in the right cingulate sulci and left inferior frontal sulci.

CONCLUSION

Our results replicate typical brain-structural abnormalities with new findings in the medial prefrontal cortex, suggested to be a key region in this disorder.

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

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

Resting state activity and the "stream of consciousness" in schizophrenia--neurophenomenal hypotheses

Schizophrenia is a multifaceted disorder with various symptoms including auditory hallucinations, egodisturbances, passivity phenomena, and delusions. Recent neurobiological approaches have focused on, especially, the abnormal contents of consciousness, the "substantive parts" as James said, to associate them with the neural mechanisms related to sensory, motor, and cognitive functions, and the brain's underlying stimulus-induced or task-evoked activity. This leaves open, however, the neural mechanisms that provide the temporal linkage or glue between the various contents, the transitive parts that makes possible the "stream of consciousness." Interestingly, schizophrenic patients seem to suffer from abnormalities specifically in the "transitive parts" when they experience contents as temporally disconnected or fragmented which in phenomenological psychiatry has been described as "temporal fragmentation." The aim of this article is to develop so-called neurophenomenal hypothesis about the direct relationship between phenomenal features of the "stream of consciousness," the "transitive parts," and the specific neuronal mechanisms in schizophrenia as based on healthy subjects. Rather than emphasizing stimulus-induced and task-evoked activity and sensory and lateral prefrontal cortical regions as in neurocognitive approaches with their focus on the "substantive parts," the focus shifts here to the brain's intrinsic activity, its resting state activity, which may account for the temporal linkage or glue between the contents of consciousness, the transitive parts.

Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis

The task-positive network (TPN) is anticorrelated with activity in the default mode network (DMN), and possibly reflects competition between the processing of external and internal information, while the salience network (SN) is pivotal in regulating TPN and DMN activity. Because abnormal functional connectivity in these networks has been related to schizophrenia, we tested whether alterations are also evident in subjects at risk for psychosis. Resting-state functional magnetic resonance imaging was tested in 28 subjects with basic symptoms reporting subjective cognitive-perceptive symptoms; 19 with attenuated or brief, limited psychotic symptoms; and 29 matched healthy controls. We characterized spatial differences in connectivity patterns, as well as internetwork connectivity. Right anterior insula (rAI) was selected as seed region for identifying the SN; medioprefrontal cortex (MPFC) for the DMN and TPN. The 3 groups differed in connectivity patterns between the MPFC and right dorsolateral prefrontal cortex (rDLPFC), and between the rAI and posterior cingulate cortex (PCC). In particular, the typically observed antagonistic relationship in MPFC-rDLPFC, rAI-PCC, and internetwork connectivity of DMN-TPN was absent in both at-risk groups. Notably, those connectivity patterns were associated with symptoms related to reality distortions, whereas enhanced connectivity strengths of MPFC-rDLPFC and TPN-DMN were related to poor performance in cognitive functions. We propose that the loss of a TPN-DMN anticorrelation, accompanied by an aberrant spatial extent in the DMN, TPN, and SN in the psychosis risk state, reflects the confusion of internally and externally focused states and disturbance of cognition, as seen in psychotic disorders.

How art changes your brain: differential effects of visual art production and cognitive art evaluation on functional brain connectivity

Visual art represents a powerful resource for mental and physical well-being. However, little is known about the underlying effects at a neural level. A critical question is whether visual art production and cognitive art evaluation may have different effects on the functional interplay of the brain's default mode network (DMN). We used fMRI to investigate the DMN of a non-clinical sample of 28 post-retirement adults (63.71 years ±3.52 SD) before (T0) and after (T1) weekly participation in two different 10-week-long art interventions. Participants were randomly assigned to groups stratified by gender and age. In the visual art production group 14 participants actively produced art in an art class. In the cognitive art evaluation group 14 participants cognitively evaluated artwork at a museum. The DMN of both groups was identified by using a seed voxel correlation analysis (SCA) in the posterior cingulated cortex (PCC/preCUN). An analysis of covariance (ANCOVA) was employed to relate fMRI data to psychological resilience which was measured with the brief German counterpart of the Resilience Scale (RS-11). We observed that the visual art production group showed greater spatial improvement in functional connectivity of PCC/preCUN to the frontal and parietal cortices from T0 to T1 than the cognitive art evaluation group. Moreover, the functional connectivity in the visual art production group was related to psychological resilience (i.e., stress resistance) at T1. Our findings are the first to demonstrate the neural effects of visual art production on psychological resilience in adulthood.

Aberrant dependence of default mode/central executive network interactions on anterior insular salience network activity in schizophrenia

In schizophrenia, consistent structural and functional changes have been demonstrated for the insula including aberrant salience processing, which is critical for psychosis. Interactions within and across default mode and central executive network (DMN, CEN) are impaired in schizophrenia. The question arises whether these 2 types of changes are related. Recently, the anterior insula has been demonstrated to control DMN/CEN interactions. We hypothesized that aberrant insula and DMN/CEN activity in schizophrenia is associated with an impaired dependence of DMN/CEN interactions on anterior insular salience network (SN) activity. Eighteen patients with schizophrenia during psychosis and 20 healthy controls were studied by resting-state-fMRI and psychometric examination. High-model-order independent component analysis of fMRI data revealed spatiotemporal patterns of synchronized ongoing blood-oxygenation-level-dependent (BOLD) activity including SN, DMN, and CEN. Scores of functional and time-lagged connectivity across networks' time courses were calculated. Connectivity scores and spatial network maps were compared between groups and related with patients' hallucination and delusion severity. Spatial BOLD-synchronicity was altered in patients' SN, DMN, and CEN, including decreased activity in the right anterior insula (rAI). Patients' functional connectivity between DMN and CEN was increased and related with hallucinations severity. Importantly, patients' time-lagged connectivity between SN and DMN/CEN was reduced, and decreased rAI activity of the SN was associated with both hallucinations and increased functional connectivity between DMN and CEN. Data provide evidence for an aberrant dependence of DMN/CEN interactions on anterior insular SN activity, linking impaired insula, DMN, CEN activity, and psychosis in schizophrenia.

How is our self altered in psychiatric disorders? A neurophenomenal approach to psychopathological symptoms

The self is central in our experience and has often been assumed to be necessary for any kind of consciousness in philosophy. Recent investigations in neuroscience demonstrate a particular set of regions such as the cortical midline regions to be associated with the processing of stimuli specifically related to the self as distinguished from those remaining unrelated to the self. Furthermore, findings show a close overlap between self-related activity and high levels of resting state activity in especially anterior midline regions. Interestingly, recent findings in psychiatric disorders such as depression and schizophrenia show resting state abnormalities in exactly these regions, that is in the cortical midline structures. Based on phenomenal and neural observations, I here suggest a neurophenomenal approach that directly links neuronal and phenomenal features (without sandwiching cognitive or sensorimotor functions) to psychopathological symptoms of self in depression and schizophrenia.

Working memory in schizotypal personality disorder: fMRI activation and deactivation differences

BACKGROUND

Schizotypal personality disorder (SPD) is considered a schizophrenia spectrum disorder, sharing with schizophrenia cognitive, neuropsychological, epidemiological, and biological characteristics. Working memory may be one area of shared deficit, although to date, this is only the second study to investigate working memory in SPD using fMRI.

METHODS

In a block-design fMRI study, fifteen antipsychotic-naïve SPD and sixteen healthy control subjects performed blocks of a 2back visual working memory task and 0back continuous performance task while undergoing whole-brain fMRI at 3T. Whole-brain analyses were performed for the 0back>rest (fixation baseline) and the 2back>0back contrasts (isolating the working memory component from the visual perception and attention component). Parameter estimates were extracted to determine whether observed differences were due to task-induced activation and/or deactivation.

RESULTS

Activation differences emerged between the two groups, without differences in task performance. In the 0back task, SPD showed decreased task-induced activation of the left postcentral gyrus. In the 2back>0back contrast, HC showed greater task-induced activation of the left posterior cingulate gyrus, superior temporal gyrus, insula, and middle frontal gyrus. These differences were due to SPD subjects' decreased task-induced activation in the left posterior cingulate gyrus, and task-induced deactivation in the remaining regions.

CONCLUSIONS

These findings suggest that compared to HC subjects, individuals with SPD may achieve comparable working memory performance. However, differences emerge at the level of functional neural activation, attributable to different task-induced activation and deactivation patterns. Such differential recruitment of neural resources may be beneficial, contributing to SPD subjects' ability to perform these tasks comparably to HC subjects.

Temporally distinct cognitive effects following acute administration of ketamine and phencyclidine in the rat

Non-competitive N-methyl-D-aspartate receptor (NMDAR) antagonists such as phencyclidine (PCP) and ketamine are commonly and interchangeably used to model aspects of schizophrenia in animals. We compared here the effects of acute administration of these compounds over a range of pre-treatment times in tests of instrumental responding (VI 30s response schedule), simple reaction time (SRT) and cognitive flexibility (reversal learning and attentional set shifting digging task) in rats. At standard pre-treatment times (15-30 min), both ketamine and PCP produced overall response suppression in VI 30 and increased reaction times in SRT suggesting that any concomitant cognitive performance deficits are likely to be confounded by motor and/or motivational changes. However, the use of extended pre-treatment times produced deficits in cognitive flexibility measured up to 4h after drug administration in the absence of motor/motivational impairment. Generally, PCP increased impulsive responding in the SRT indicating a possible loss of inhibitory response control that may have contributed to deficits observed in reversal learning and attentional set-shifting. In contrast to PCP, ketamine did not have the same effect on impulsive responding, and possibly as a consequence produced more subtle cognitive deficits in attentional set-shifting. In summary, acute treatment with NMDAR antagonists can produce cognitive deficits in rodents that are relevant to schizophrenia, provided that motor and/or motivational effects are allowed to dissipate. The use of longer pre-treatment times than commonly employed might be advantageous. Also, ketamine, which is more frequently used in clinical settings, did not produce as extensive cognitive deficits as PCP.

Myelin and axon abnormalities in schizophrenia measured with magnetic resonance imaging techniques

BACKGROUND

In schizophrenia (SZ), disturbances in integration of activity among brain regions seem to be as important as abnormal activity of any single region. Brain regions are connected through white matter (WM) tracts, and diffusion tensor imaging has provided compelling evidence for WM abnormalities in SZ. However, diffusion tensor imaging alone cannot currently pinpoint the biological basis of these abnormalities.

METHODS

In this study, we combined a myelin-specific and an axon-specific magnetic resonance imaging approach to examine potentially distinct abnormalities of WM components in SZ. Magnetization transfer ratio (MTR) provides information on myelin content, whereas diffusion tensor spectroscopy provides information on metabolite diffusion within axons. We collected data from a 1 × 3 × 3 cm voxel within the right prefrontal cortex WM at 4 Tesla and studied 23 patients with SZ and 22 age- and sex-matched healthy control participants.

RESULTS

The MTR was significantly reduced in SZ, suggesting reduced myelin content. By contrast, the apparent diffusion coefficient of N-acetylaspartate (NAA) was significantly elevated, suggesting intra-axonal abnormalities. Greater abnormality of both MTR and the apparent diffusion coefficient of NAA correlated with more adverse outcomes in the patient group.

CONCLUSIONS

The results suggest that WM abnormalities in SZ include both abnormal myelination and abnormal NAA diffusion within axons. These processes might be associated with abnormal signal transduction and abnormal information processing in SZ.