Schizophrenia and the brain's control network: aberrant within- and between-network connectivity of the frontoparietal network in schizophrenia

Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy

Modified electroconvulsive therapy (MECT) has been widely applied to help treat schizophrenia patients who are treatment-resistant to pharmaceutical therapy. Although the technique is increasingly prevalent, the underlying neural mechanisms have not been well clarified. We conducted a longitudinal study to investigate the alteration of global functional connectivity density (gFCD) in schizophrenia patients undergoing MECT using resting state fMRI (functional magnetic resonance imaging). Two groups of schizophrenia inpatients were recruited. One group received a four-week MECT together with antipsychotic drugs (ECT+Drug, n=21); the other group only received antipsychotic drugs (Drug, n=21). Both groups were compared to a sample of healthy controls (HC, n=23). fMRI scans were obtained from the schizophrenia patients twice at baseline (t₁) and after 4-week treatment (t₂), and from healthy controls at baseline. gFCD was computed using resting state fMRI. Repeated ANCOVA showed a significant interaction effect of group×time in the schizophrenia patients in left precuneus (Pcu), ventral medial prefrontal cortex (vMPFC), and dorsal medial prefrontal cortex (dMPFC) (GRF-corrected P<0.05), which are mainly located within the default mode network (DMN). Post-hoc analysis revealed that compared with baseline (t₁), an increased gFCD was found in the ECT+Drug group in the dMPFC (t=3.87, p=0.00095), vMPFC (t=3.95, p=0.00079) and left Pcu (t=3.33, p=0.0034), but no significant effect was identified in the Drug group. The results suggested that increased global functional connectivity density within the DMN might be one important neural mechanism of MECT in schizophrenia.

Blocking NMDAR Disrupts Spike Timing and Decouples Monkey Prefrontal Circuits: Implications for Activity-Dependent Disconnection in Schizophrenia

We employed multi-electrode array recording to evaluate the influence of NMDA receptors (NMDAR) on spike-timing dynamics in prefrontal networks of monkeys as they performed a cognitive control task measuring specific deficits in schizophrenia. Systemic, periodic administration of an NMDAR antagonist (phencyclidine) reduced the prevalence and strength of synchronous (0-lag) spike correlation in simultaneously recorded neuron pairs. We employed transfer entropy analysis to measure effective connectivity between prefrontal neurons at lags consistent with monosynaptic interactions and found that effective connectivity was persistently reduced following exposure to the NMDAR antagonist. These results suggest that a disruption of spike timing and effective connectivity might be interrelated factors in pathogenesis, supporting an activity-dependent disconnection theory of schizophrenia. In this theory, disruption of NMDAR synaptic function leads to dysregulated timing of action potentials in prefrontal networks, accelerating synaptic disconnection through a spike-timing-dependent mechanism.

Increased sensorimotor network connectivity associated with clozapine eligibility in people with schizophrenia

Schizophrenia is a heterogeneous disorder that exhibits variable responsiveness to treatment between individuals. Here we conducted a resting-state functional magnetic resonance imaging (rs-fMRI) study to determine whether resistance to first-line antipsychotics is reflected in resting-state connectivity. rs-fMRI data were collected from 15 people who had failed to respond to first-line antipsychotics (clozapine-eligible) and 10 first-line treatment responders (FLR). Image pre-processing and analysis were performed using FMRIB's software library (FSL). Data was decomposed into spatial and temporal components using independent components analysis. Connectivity within each independent component was compared between groups using t-tests and the Bonferroni correction for multiple comparisons. Gender was added as a covariate. Clozapine-eligible individuals exhibited enhanced functional connectivity within the sensorimotor network compared with FLR. Those eligible for clozapine showed additional connectivity with the precuneus compared with FLR. No other comparisons reached statistical significance and no effect of gender was observed. These data reveal differences in functional connectivity between FLR and those eligible for clozapine and suggest that greater connectivity between the SMN and precuneus may be indicative of treatment resistance in people with schizophrenia.

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine learning algorithms can be used to distinguish between the two disorders. Using a linear support vector machine, we identify features that are most diagnostic for each disorder and successfully use them to classify an independent cohort of subjects. We find both common and divergent connectivity differences largely in the default mode network as well as in salience, and motor networks. Using divergent connectivity differences, we are able to distinguish autistic subjects from those with schizophrenia. Understanding the common and divergent connectivity changes associated with these disorders may provide a framework for understanding their shared cognitive deficits.

Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity

Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).

Comparison of changes in oxygenated hemoglobin during the tree-drawing task between patients with schizophrenia and healthy controls

BACKGROUND

Tree-drawing test is used as a projective psychological test that expresses the abnormal internal experience in patients with schizophrenia (SZ). Despite the widely accepted view that the cognitive function is involved in characteristic tree-drawing in patients with SZ, no study has psychophysiologically examined it. The present study aimed to investigate the involvement of cognitive function during tree-drawing in patients with SZ. For that purpose, we evaluated the brain function in patients with SZ during a tree-drawing task by using near-infrared spectroscopy (NIRS) and compared them with those in healthy controls.

PATIENTS AND METHODS

The subjects were 28 healthy controls and 28 patients with SZ. Changes in the oxygenated hemoglobin ([oxy-Hb]) concentration in both the groups during the task of drawing a tree imagined freely (free-drawing task) and the task of copying an illustration of a tree (copying task) were measured by using NIRS.

RESULTS

Because of the difference between the task conditions, [oxy-Hb] levels in controls during the free-drawing task were higher than that during the copying task at the bilateral frontal pole regions and left inferior frontal region. Because of the difference between the groups, [oxy-Hb] levels at the left middle frontal region, bilateral inferior frontal regions, bilateral inferior parietal regions, and left superior temporal region during the free-drawing task in patients were lower than that in controls.

CONCLUSION

[oxy-Hb] during the tree-drawing task in patients with SZ was lower than that in healthy controls. Our results suggest that brain dysfunction in patients with SZ might be associated with their tree-drawing.

Implications of Information Theory for Computational Modeling of Schizophrenia

Information theory provides a formal framework within which information processing and its disorders can be described. However, information theory has rarely been applied to modeling aspects of the cognitive neuroscience of schizophrenia. The goal of this article is to highlight the benefits of an approach based on information theory, including its recent extensions, for understanding several disrupted neural goal functions as well as related cognitive and symptomatic phenomena in schizophrenia. We begin by demonstrating that foundational concepts from information theory—such as Shannon information, entropy, data compression, block coding, and strategies to increase the signal-to-noise ratio—can be used to provide novel understandings of cognitive impairments in schizophrenia and metrics to evaluate their integrity. We then describe more recent developments in information theory, including the concepts of infomax, coherent infomax, and coding with synergy, to demonstrate how these can be used to develop computational models of schizophrenia-related failures in the tuning of sensory neurons, gain control, perceptual organization, thought organization, selective attention, context processing, predictive coding, and cognitive control. Throughout, we demonstrate how disordered mechanisms may explain both perceptual/cognitive changes and symptom emergence in schizophrenia. Finally, we demonstrate that there is consistency between some information-theoretic concepts and recent discoveries in neurobiology, especially involving the existence of distinct sites for the accumulation of driving input and contextual information prior to their interaction. This convergence can be used to guide future theory, experiment, and treatment development.

Changes in extra-striatal functional connectivity in patients with schizophrenia in a psychotic episode

BACKGROUND

In patients with schizophrenia in a psychotic episode, intra-striatal intrinsic connectivity is increased in the putamen but not ventral striatum. Furthermore, multimodal changes have been observed in the anterior insula that interact extensively with the putamen.

AIMS

We hypothesised that during psychosis, putamen extra-striatal functional connectivity is altered with both the anterior insula and areas normally connected with the ventral striatum (i.e. altered functional connectivity distinctiveness of putamen and ventral striatum).

METHOD

We acquired resting-state functional magnetic resonance images from 21 patients with schizophrenia in a psychotic episode and 42 controls.

RESULTS

Patients had decreased functional connectivity: the putamen with right anterior insula and dorsal prefrontal cortex, the ventral striatum with left anterior insula. Decreased functional connectivity between putamen and right anterior insula was specifically associated with patients' hallucinations. Functional connectivity distinctiveness was impaired only for the putamen.

CONCLUSIONS

Results indicate aberrant extra-striatal connectivity during psychosis and a relationship between reduced putamen-right anterior insula connectivity and hallucinations. Data suggest that altered intrinsic connectivity links striatal and insular pathophysiology in psychosis.

How do abnormalities in the brain's spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology

Schizophrenia is a complex neuropsychiatric disorder with a variety of symptoms that include sensorimotor, affective, cognitive, and social changes. The exact neuronal mechanisms underlying these symptoms remain unclear though. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's spontaneous activity, otherwise known as its resting state activity. While various spatial and temporal abnormalities have been observed in spontaneous activity in schizophrenia, their meaning and significance for the different psychopathological symptoms in schizophrenia, are yet to be defined. The first aim in this paper is to provide an overview of recent findings concerning changes in the spatial (e.g., functional connectivity) and temporal (e.g., couplings between different frequency fluctuations) properties of spontaneous activity in schizophrenia. The second aim is to link these spatiotemporal changes to the various psychopathological symptoms of schizophrenia, with a specific focus on basic symptoms, formal thought disorder, and ego-disturbances. Based on the various findings described, we postulate that the spatiotemporal changes on the neuronal level of the brain's spontaneous activity transform into corresponding spatiotemporal changes on the psychological level which, in turn, leads to the different kinds of psychopathological symptoms. We consequently suggest a spatiotemporal rather than cognitive or sensory approach to the condition, amounting to what we describe as "Spatiotemporal Psychopathology".

Thalamic Functional Connectivity in Mild Traumatic Brain Injury: Longitudinal Associations With Patient-Reported Outcomes and Neuropsychological Tests

OBJECTIVES

(1) To examine differences in patient-reported outcomes, neuropsychological tests, and thalamic functional connectivity (FC) between patients with mild traumatic brain injury (mTBI) and individuals without mTBI and (2) to determine longitudinal associations between changes in these measures.

DESIGN

Prospective observational case-control study.

SETTING

Academic medical center.

PARTICIPANTS

A sample (N=24) of 13 patients with mTBI (mean age, 39.3±14.0y; 4 women [31%]) and 11 age- and sex-matched controls without mTBI (mean age, 37.6±13.3y; 4 women [36%]).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Resting state FC (3T magnetic resonance imaging scanner) was examined between the thalamus and the default mode network, dorsal attention network, and frontoparietal control network. Patient-reported outcomes included pain (Brief Pain Inventory), depressive symptoms (Patient Health Questionnaire-9), posttraumatic stress disorder ([PTSD] Checklist - Civilian Version), and postconcussive symptoms (Rivermead Post-Concussion Symptoms Questionnaire). Neuropsychological tests included the Delis-Kaplan Executive Function System Tower test, Trails B, and Hotel Task. Assessments occurred at 6 weeks and 4 months after hospitalization in patients with mTBI and at a single visit for controls.

RESULTS

Student t tests found increased pain, depressive symptoms, PTSD symptoms, and postconcussive symptoms; decreased performance on Trails B; increased FC between the thalamus and the default mode network; and decreased FC between the thalamus and the dorsal attention network and between the thalamus and the frontoparietal control network in patients with mTBI as compared with controls. The Spearman correlation coefficient indicated that increased FC between the thalamus and the dorsal attention network from baseline to 4 months was associated with decreased pain and postconcussive symptoms (corrected P<.05).

CONCLUSIONS

Findings suggest that alterations in thalamic FC occur after mTBI, and improvements in pain and postconcussive symptoms are correlated with normalization of thalamic FC over time.

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

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

Cognition and resting-state functional connectivity in schizophrenia

Individuals with schizophrenia consistently display deficits in a multitude of cognitive domains, but the neurobiological source of these cognitive impairments remains unclear. By analyzing the functional connectivity of resting-state functional magnetic resonance imaging (rs-fcMRI) data in clinical populations like schizophrenia, research groups have begun elucidating abnormalities in the intrinsic communication between specific brain regions, and assessing relationships between these abnormalities and cognitive performance in schizophrenia. Here we review studies that have reported analysis of these brain-behavior relationships. Through this systematic review we found that patients with schizophrenia display abnormalities within and between regions comprising (1) the cortico-cerebellar-striatal-thalamic loop and (2) task-positive and task-negative cortical networks. Importantly, we did not observe unique relationships between specific functional connectivity abnormalities and distinct cognitive domains, suggesting that the observed functional systems may underlie mechanisms that are shared across cognitive abilities, the disturbance of which could contribute to the "generalized" cognitive deficit found in schizophrenia. We also note several areas of methodological change that we believe will strengthen this literature.

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

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

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

Objective

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

Material and methods

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

Results

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

Conclusions

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

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We found widespread functional dysconnectivity in unmedicated patients with schizophrenia.

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Large scale functional networks appear differentially affected in the disorder.

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

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

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

Cognitive correlates of frontoparietal network connectivity 'at rest' in individuals with differential risk for psychotic disorder

Altered frontoparietal network functional connectivity (FPN-fc) has been associated with neurocognitive dysfunction in individuals with (risk for) psychotic disorder. Cannabis use is associated with cognitive and FPN-fc alterations in healthy individuals, but it is not known whether cannabis exposure moderates the FPN-fc-cognition association. We studied FPN-fc in relation to psychosis risk, as well as the moderating effects of psychosis risk and cannabis use on the association between FPN-fc and (social) cognition. This was done by collecting resting-state fMRI scans and (social) cognitive test results from 63 patients with psychotic disorder, 73 unaffected siblings and 59 controls. Dorsolateral prefrontal cortex (DLPFC) seed-based correlation analyses were used to estimate FPN-fc group differences. Additionally, group×FPN-fc and cannabis×FPN-fc interactions in models of cognition were assessed with regression models. Results showed that DLPFC-fc with the left precuneus, right inferior parietal lobule, right middle temporal gyrus (MTG), inferior frontal gyrus (IFG) regions and right insula was decreased in patients compared to controls. Siblings had reduced DLPFC-fc with the right MTG, left middle frontal gyrus, right superior frontal gyrus, IFG regions, and right insula compared to controls, with an intermediate position between patients and controls for DLPFC-IFG/MTG and insula-fc. There were no significant FPN-fc×group or FPN-fc×cannabis interactions in models of cognition. Reduced DLPFC-insula-fc was associated with worse social cognition in the total sample. In conclusion, besides patient- and sibling-specific FPN-fc alterations, there was evidence for trait-related alterations. FPN-fc-cognition associations were not conditional on familial liability or cannabis use. Lower FPN-fc was associated with lower emotion processing in the total group.

Mirror neuron deficit in schizophrenia: Evidence from repetition suppression

BACKGROUND

Schizophrenia is associated with impaired cognition, especially cognition in social contexts. The mirror neuron system (MNS) serves as an important neuronal basis for social cognitive skills; however, previous investigations on the integrity of MNS function in schizophrenia remain approximate.

METHODS

We employed a repetition suppression paradigm that allows for measuring neuronal responses to gesture observation and gesture execution. Cross-modal repetition suppression, i.e., adaptation between observe/execute and execute/observe conditions, was defined as the decisive experimental condition characterizing the unique sensori-motor properties of mirror neurons. Event-related potentials (ERPs) were assessed in 15 schizophrenia patients and 15 matched controls.

RESULTS

We isolated an ERP signature of specific adaptation effects to identical hand gestures. Of critical importance, this ERP signature indicated intact intra-modal adaptive pattern, i.e., observe/observe and execute/execute, of comparable magnitude between groups, but deficient cross-modal adaptation, i.e., observe/execute and execute/observe, in schizophrenia patients.

CONCLUSION

Our data provide robust evidence that pure perception and execution of hand gestures are relatively intact in schizophrenia. In contrast, visuo-motor transformation processes mediated by the MNS seem to be specifically disturbed in schizophrenia. These results unambiguously demonstrate MNS deficits in schizophrenia and extend our understanding of the neuronal bases of social dysfunction in this disorder.

Altered functional connectivity of the cingulate subregions in schizophrenia

Schizophrenia patients have shown altered resting-state functional connectivity (rsFC) of the cingulate cortex; however, it is unknown whether rsFCs of the cingulate subregions are differentially affected in this disorder. We aimed to clarify the issue by comparing rsFCs of each cingulate subregion between healthy controls and schizophrenia patients. A total of 102 healthy controls and 94 schizophrenia patients underwent resting-state functional magnetic resonance imaging with a sensitivity-encoded spiral-in imaging sequence to reduce susceptibility-induced signal loss and distortion. The cingulate cortex was divided into nine subregions, including the subgenual anterior cingulate cortex (ACC), areas 24 and 32 of the pregenual ACC, areas 24 and 32 of the anterior mid-cingulate cortex (aMCC), posterior MCC (pMCC), dorsal (dPCC) and ventral (vPCC) posterior cingulate cortex (PCC) and retrosplenial cortex (RSC). The rsFCs of each cingulate subregion were compared between the two groups and the atrophy effect was considered. Results with and without global signal regression were reported. Most cingulate subregions exhibited decreased rsFCs in schizophrenia after global signal regression (GSR). Without GSR, only increased rsFC was found in schizophrenia, which primarily restricted to the aMCC, PCC and RSC. Some of these increased rsFCs were also significant after GSR. These findings suggest that GSR can greatly affect between-group differences in rsFCs and the consistently increased rsFCs may challenge the functional disconnection hypothesis of schizophrenia.

Ketamine-Induced Modulation of the Thalamo-Cortical Network in Healthy Volunteers As a Model for Schizophrenia

BACKGROUND

Schizophrenia has been associated with disturbances of thalamic functioning. In light of recent evidence suggesting a significant impact of the glutamatergic system on key symptoms of schizophrenia, we assessed whether modulation of the glutamatergic system via blockage of the N-methyl-D-aspartate (NMDA)-receptor might lead to changes of thalamic functional connectivity.

METHODS

Based on the ketamine model of psychosis, we investigated changes in cortico-thalamic functional connectivity by intravenous ketamine challenge during a 55-minute resting-state scan. Thirty healthy volunteers were measured with pharmacological functional magnetic resonance imaging using a double-blind, randomized, placebo-controlled, crossover design.

RESULTS

Functional connectivity analysis revealed significant ketamine-specific changes within the thalamus hub network, more precisely, an increase of cortico-thalamic connectivity of the somatosensory and temporal cortex.

CONCLUSIONS

Our results indicate that changes of thalamic functioning as described for schizophrenia can be partly mimicked by NMDA-receptor blockage. This adds substantial knowledge about the neurobiological mechanisms underlying the profound changes of perception and behavior during the application of NMDA-receptor antagonists.

The selective impairment of resting-state functional connectivity of the lateral subregion of the frontal pole in schizophrenia

OBJECTIVE

Although extensive resting-state functional connectivity (rsFC) changes have been reported in schizophrenia, rsFC changes of the frontal pole (FP) remain unclear. The FP contains several subregions with different connection patterns; however, it is unknown whether the FP subregions are differentially affected in schizophrenia. To explore this possibility, we compared rsFC differences of the FP subregions between schizophrenia patients and healthy controls.

METHOD

One hundred healthy controls and 91 patients with schizophrenia underwent resting-state functional MRI with a sensitivity-encoded spiral-in (SENSE-SPIRAL) imaging sequence to reduced susceptibility-induced signal loss and distortion. The FP was subdivided into the orbital (FPo), medial (FPm), and lateral (FPl) subregions. Mean fMRI time series were extracted for each FP subregion and entered into a seed-based rsFC analysis.

RESULTS

The FP subregions exhibited differential rsFC patterns in both healthy controls and schizophrenia patients. Direct comparison between groups revealed reduced rsFCs between the bilateral FPl and several cognitive-related regions, including the dorsolateral prefrontal cortex, medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex/precuneus, temporal cortex and inferior parietal lobule in schizophrenia. Although the FPl exhibited obvious atrophy, rsFC changes were unrelated to volumetric atrophy in the FPl, to duration of illness, and to antipsychotic medication dosage. No significant differences were observed in the rsFCs of other FP subregions.

CONCLUSION

These findings suggest a selective (the lateral subregion) functional disconnection of the FP subregions in schizophrenia.

Antipsychotic treatment and functional connectivity of the striatum in first-episode schizophrenia

IMPORTANCE

Previous evidence has implicated corticostriatal abnormalities in the pathophysiology of psychosis. Although the striatum is the primary target of all efficacious antipsychotics, the relationship between its functional connectivity and symptomatic reduction remains unknown.

OBJECTIVE

To explore the longitudinal effect of treatment with second-generation antipsychotics on functional connectivity of the striatum during the resting state in patients experiencing a first episode of psychosis.

DESIGN, SETTING, AND PARTICIPANTS

This prospective controlled study took place at a clinical research center and included 24 patients with first-episode psychosis and 24 healthy participants matched for age, sex, education, and handedness. Medications were administered in a double-blind randomized manner.

INTERVENTIONS

Patients were scanned at baseline and after 12 weeks of treatment with either risperidone or aripiprazole. Their symptoms were evaluated with the Brief Psychiatric Rating Scale at baseline and follow-up. Healthy participants were scanned twice within a 12-week interval.

MAIN OUTCOMES AND MEASURES

Functional connectivity of striatal regions was examined via functional magnetic resonance imaging using a seed-based approach. Changes in functional connectivity of these seeds were compared with reductions in ratings of psychotic symptoms.

RESULTS

Patients had a median exposure of 1 day to antipsychotic medication prior to being scanned (mean [SD] = 4.5 [6.1]). Eleven patients were treated with aripiprazole and 13 patients were treated with risperidone. As psychosis improved, we observed an increase in functional connectivity between striatal seed regions and the anterior cingulate, dorsolateral prefrontal cortex, and limbic regions such as the hippocampus and anterior insula (P < .05, corrected for multiple comparisons). Conversely, a negative relationship was observed between reduction in psychosis and functional connectivity of striatal regions with structures within the parietal lobe (P < .05, corrected for multiple comparisons).

CONCLUSIONS AND RELEVANCE

Our results indicated that corticostriatal functional dysconnectivity in psychosis is a state-dependent phenomenon. Increased functional connectivity of the striatum with prefrontal and limbic regions may be a biomarker for improvement in symptoms associated with antipsychotic treatment.

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.

Neural correlates of insight in dreaming and psychosis

The idea that dreaming can serve as a model for psychosis has a long and honourable tradition, however it is notoriously speculative. Here we demonstrate that recent research on the phenomenon of lucid dreaming sheds new light on the debate. Lucid dreaming is a rare state of sleep in which the dreamer gains insight into his state of mind during dreaming. Recent electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data for the first time allow very specific hypotheses about the dream-psychosis relationship: if dreaming is a reasonable model for psychosis, then insight into the dreaming state and insight into the psychotic state should share similar neural correlates. This indeed seems to be the case: cortical areas activated during lucid dreaming show striking overlap with brain regions that are impaired in psychotic patients who lack insight into their pathological state. This parallel allows for new therapeutic approaches and ways to test antipsychotic medication.

Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine

Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to a strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D "connectome space," offering an additional layer of interpretability that could provide new insights about various disease processes.

Disrupted network architecture of the resting brain in attention-deficit/hyperactivity disorder

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders of childhood. Neuroimaging investigations of ADHD have traditionally sought to detect localized abnormalities in discrete brain regions. Recent years, however, have seen the emergence of complementary lines of investigation into distributed connectivity disturbances in ADHD. Current models emphasize abnormal relationships between default network-involved in internally directed mentation and lapses of attention-and task positive networks, especially ventral attention network. However, studies that comprehensively investigate interrelationships between large-scale networks in ADHD remain relatively rare.

METHODS

Resting state functional magnetic resonance imaging scans were obtained from 757 participants at seven sites in the ADHD-200 multisite sample. Functional connectomes were generated for each subject, and interrelationships between seven large-scale brain networks were examined with network contingency analysis.

RESULTS

ADHD brains exhibited altered resting state connectivity between default network and ventral attention network [P < 0.0001, false discovery rate (FDR)-corrected], including prominent increased connectivity (more specifically, diminished anticorrelation) between posterior cingulate cortex in default network and right anterior insula and supplementary motor area in ventral attention network. There was distributed hypoconnectivity within default network (P = 0.009, FDR-corrected), and this network also exhibited significant alterations in its interconnections with several other large-scale networks. Additionally, there was pronounced right lateralization of aberrant default network connections.

CONCLUSIONS

Consistent with existing theoretical models, these results provide evidence that default network-ventral attention network interconnections are a key locus of dysfunction in ADHD. Moreover, these findings contribute to growing evidence that distributed dysconnectivity within and between large-scale networks is present in ADHD.

Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack

Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics.