Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

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

Background: Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods: We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions: Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

A method for estimating and characterizing explicitly nonlinear dynamic functional network connectivity in resting-state fMRI data.

The past 10 years have seen an explosion of approaches that focus on the study of time-resolved change in functional connectivity (FC). FC characterization among networks at a whole-brain level is frequently termed functional network connectivity (FNC). Time-resolved or dynamic functional network connectivity (dFNC) focuses on the estimation of transient, recurring, whole-brain patterns of FNC. While most approaches in this area have attempted to capture dynamic linear correlation, we are particularly interested in whether explicitly nonlinear relationships, above and beyond linear, are present and contain unique information. This study thus proposes an approach to assess explicitly nonlinear dynamic functional network connectivity (EN dFNC) derived from the relationship among independent component analysis time courses. Linear relationships were removed at each time point to evaluate, typically ignored, explicitly nonlinear dFNC using normalized mutual information (NMI). Simulations showed the proposed method estimated explicitly nonlinearity over time, even within relatively short windows of data. We then, applied our approach on 151 schizophrenia patients, and 163 healthy controls fMRI data and found three unique, highly structured, mostly long-range, functional states that also showed significant group differences. In particular, explicitly nonlinear relationships tend to be more widespread than linear ones. Results also highlighted a state with long range connections to the visual domain, which were significantly reduced in schizophrenia. Overall, this work suggests that quantifying EN dFNC may provide a complementary and potentially valuable tool for studying brain function by exposing relevant variation that is typically ignored.

Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder.

Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB). Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.

In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).

Polymorphisms in MIR137HG and microRNA-137-regulated genes influence gray matter structure in schizophrenia.

Evidence suggests that microRNA-137 (miR-137) is involved in the genetic basis of schizophrenia. Risk variants within the miR-137 host gene (MIR137HG) influence structural and functional brain-imaging measures, and miR-137 itself is predicted to regulate hundreds of genes. We evaluated the influence of a MIR137HG risk variant (rs1625579) in combination with variants in miR-137-regulated genes TCF4, PTGS2, MAPK1 and MAPK3 on gray matter concentration (GMC). These genes were selected based on our previous work assessing schizophrenia risk within possible miR-137-regulated gene sets using the same cohort of subjects. A genetic risk score (GRS) was determined based on genotypes of these four schizophrenia risk-associated genes in 221 Caucasian subjects (89 schizophrenia patients and 132 controls). The effects of the rs1625579 genotype with the GRS of miR-137-regulated genes in a three-way interaction with diagnosis on GMC patterns were assessed using a multivariate analysis. We found that schizophrenia subjects homozygous for the MIR137HG risk allele show significant decreases in occipital, parietal and temporal lobe GMC with increasing miR-137-regulated GRS, whereas those carrying the protective minor allele show significant increases in GMC with GRS. No correlations of GMC and GRS were found in control subjects. Variants within or upstream of genes regulated by miR-137 in combination with the MIR137HG risk variant may influence GMC in schizophrenia-related regions in patients. Given that the genes evaluated here are involved in protein kinase A signaling, dysregulation of this pathway through alterations in miR-137 biogenesis may underlie the gray matter loss seen in the disease.

The impact of parent socio-economic status on executive functioning and cortical morphology in individuals with schizophrenia and healthy controls.

BACKGROUND: Relatively lower executive functioning is characteristic of individuals with schizophrenia. As low socio-economic status (SES) early in life (i.e. parent SES) has been linked with lower executive skills in healthy children, we hypothesized that parental SES (pSES) would be more strongly related to executive functioning in individuals with schizophrenia than in controls and have a greater impact on prefrontal cortical morphology. METHOD: Healthy controls (n = 125) and individuals with schizophrenia (n = 102) completed tests assessing executive functioning and intelligence. The groups were matched on pSES, which was evaluated with the Hollingshead-Redlich scale. A principal components analysis (PCA) was conducted on 10 variables from six executive tests, yielding three specific components (fluency, planning and response inhibition). Voxel-based morphometry (VBM) was used to evaluate effects of pSES on gray matter (GM) concentration. RESULTS: Lower pSES was associated with lower scores across the three executive functioning components, and a significant group by pSES interaction was observed such that low pSES, in particular, affected individuals with schizophrenia. These effects remained significant when intellectual ability, education and self-SES (sSES) were added as covariates. VBM revealed that lower pSES was associated with reduced GM volume in several anterior brain regions, especially the superior frontal gyrus, in patients but not in controls. CONCLUSIONS: These findings suggest that individuals with schizophrenia may be particularly vulnerable to the adverse impact of low pSES, in terms of both lower executive skills and reduced anterior GM volumes.

Using joint ICA to link function and structure using MEG and DTI in schizophrenia.

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p<0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (neurophysiology) and structure (white matter integrity) and demonstrates that this multivariate, multimodal integration technique is sensitive to group differences in function and structure.

1H-MRS at 4 tesla in minimally treated early schizophrenia.

We investigated glutamate-related neuronal dysfunction in the anterior cingulate (AC) early in schizophrenia before and after antipsychotic treatment. A total of 14 minimally treated schizophrenia patients and 10 healthy subjects were studied with single-voxel proton magnetic resonance spectroscopy ((1)H-MRS) of the AC, frontal white matter and thalamus at 4 T. Concentrations of N-acetylaspartate (NAA), glutamate (Glu), glutamine (Gln) and Gln/Glu ratios were determined and corrected for the partial tissue volume. Patients were treated with antipsychotic medication following a specific algorithm and (1)H-MRS was repeated after 1, 6 and 12 months. There were group x region interactions for baseline NAA (P=0.074) and Gln/Glu (P=0.028): schizophrenia subjects had lower NAA (P=0.045) and higher Gln/Glu (P=0.006) in the AC before treatment. In addition, AC Gln/Glu was inversely related to AC NAA in the schizophrenia (P=0.0009) but not in the control group (P=0.92). Following antipsychotic treatment, there were no further changes in NAA, Gln/Glu or any of the other metabolites in any of the regions studied. We conclude that early in the illness, schizophrenia patients already show abnormalities in glutamatergic metabolism and reductions in NAA consistent with glutamate-related excitotoxicity.

The psychoses: cluster 3 of the proposed meta-structure for DSM-V and ICD-11.

BACKGROUND: In an effort to group mental disorders on the basis of etiology, five clusters have been proposed. Here we consider the validity of the cluster comprising selected psychotic and related disorders. METHOD: A group of diagnostic entities classified under schizophrenia and other psychotic disorders in DSM-IV-TR were assigned to this cluster and the bordering disorders, bipolar (BD) and schizotypal personality disorders (SPD), were included. We then reviewed the literature in relation to 11 validating criteria proposed by the DSM-V Task Force Study Group. RESULTS: Relevant comparisons on the 11 spectrum criteria are rare for the included disorders except for schizophrenia and the two border conditions, BD and SPD. The core psychosis group is congruent at the level of shared psychotic psychopathology and response to antipsychotic medication. BD and SPD are exceptions in that psychosis is not typical in BD-II disorder and frank psychosis is excluded in SPD. There is modest similarity between schizophrenia and BD relating to risk factors, neural substrates, cognition and endophenotypes, but key differences are noted. There is greater support for a spectrum relationship of SPD and schizophrenia. Antecedent temperament, an important validator for other groupings, has received little empirical study in the various psychotic disorders. CONCLUSIONS: The DSM-IV-TR grouping of psychotic disorders is supported by tradition and shared psychopathology, but few data exist across these diagnoses relating to the 11 spectrum criteria. The case for including BD is modest, and the relationship of BD to other mood disorders is addressed elsewhere. Evidence is stronger for inclusion of SPD, but the relationship with other personality disorders along the 11 criteria is not addressed and the absence of psychosis presents a conceptual problem. There are no data along the 11 spectrum criteria that are decisive for a cluster based on etiology, and inclusion of BD and SPD is questionable.

Predicting EEG responses using MEG sources in superior temporal gyrus reveals source asynchrony in patients with schizophrenia.

OBJECTIVE: An integrated analysis using Electroencephalography (EEG) and magnetoencephalography (MEG) is introduced to study abnormalities in early cortical responses to auditory stimuli in schizophrenia. METHODS: Auditory responses were recorded simultaneously using EEG and MEG from 20 patients with schizophrenia and 19 control subjects. Bilateral superior temporal gyrus (STG) sources and their time courses were obtained using MEG for the 30-100 ms post-stimulus interval. The MEG STG source time courses were used to predict the EEG signal at electrode Cz. RESULTS: In control subjects, the STG sources predicted the EEG Cz recording very well (97% variance explained). In schizophrenia patients, the STG sources accounted for substantially (86%) and significantly (P<0.0002) less variance. After MEG-derived STG activity was removed from the EEG Cz signal, the residual signal was dominated by 40 Hz activity, an indication that the remaining variance in EEG is probably contributed by other brain generators, rather than by random noise. CONCLUSIONS: Integrated MEG and EEG analysis can differentiate patients and controls, and suggests a basis for a well established abnormality in the cortical auditory response in schizophrenia, implicating a disorder of functional connectivity in the relationship between STG sources and other brain generators.

Effects of chronic haloperidol and clozapine treatments on frontal and caudate neurochemistry in schizophrenia.

N-Acetyl-aspartate (NAA), a marker of neuronal integrity, has been found to be reduced in frontal regions in schizophrenia. However, the impact of antipsychotic drug type on NAA has not been carefully evaluated. We studied outpatients with schizophrenia/schizoaffective disorders chronically treated with haloperidol or clozapine and normal controls with single-voxel 1H-MRS of the caudate nuclei and the left frontal lobe. Concentrations of NAA, choline containing compounds (Cho) and creatine plus phosphocreatine (Cre) were determined and corrected for the proportion of cerebrospinal fluid (CSF) in each voxel. The haloperidol-treated group had significantly lower CSF-uncorrected and CSF-corrected left frontal NAA than the normal controls, with the clozapine group having intermediate concentrations. The haloperidol-treated group had significantly lower CSF-uncorrected caudate NAA than the normal controls, but the three groups did not differ after correcting for CSF fraction. Performance times in the Grooved Pegboard, a measure of motor dexterity and proxy for parkinsonism, were correlated with CSF-uncorrected and CSF-corrected left frontal NAA. Demographic and illness-related variables were not related to NAA. Exposure to haloperidol-like drugs may in part account for the frontal NAA reductions previously reported in schizophrenia. Adjustment for proportion of voxel CSF should be considered in 1H-MRS studies.

Proton magnetic resonance spectroscopy (H-MRS) studies of schizophrenia.

Proton magnetic resonance spectroscopy ((1)H-MRS) is a noninvasive technique that can quantify biochemical compounds in the brain. (1)H-MRS has been used to investigate neural structures implicated in the pathology of schizophrenia. The majority of research has revealed reduced N-acetylaspartate (NAA), an index of neuronal integrity, in frontal and temporal regions of medicated and chronically ill patients with schizophrenia. This review summarizes basic principles of (1)H-MRS, studies of frontal, temporal, subcortical, and cerebellar regions in schizophrenia. Technical and study design limitations are also discussed.

Schizophrenia: improving outcome.

Therapeutic advances over the last four decades have enabled most persons with schizophrenia to live in the community. Nevertheless, the majority will continue to experience various symptoms and to have social and cognitive disabilities. With the development of new medications and psychosocial interventions, outpatient status can no longer be viewed as a satisfactory final outcome. This article presents the current state of schizophrenia therapeutics in a variety of clinically relevant situations: first-episode psychosis, treatment-resistant psychosis, chronic, relapsing psychosis, continuous poor functioning, and chronic psychosis not responsive to pharmacotherapy. The first-line atypical antipsychotics should generally be used, mainly because of their comparatively benign side-effect profiles, and they should be given as early as possible in the illness. The clinician should not be quick to accept persistent psychosis; the second-line atypical clozapine should be tried early in the course of the disease in patients showing treatment resistance. For patients residing with their families, educational and supportive family interventions have an important effect on relapse prevention; for those who live on their own and suffer frequent relapses, Assertive Community Treatment may be helpful. Patients with psychosis that is not responsive to pharmacotherapy may benefit from specific modalities of cognitive-behavioral therapy currently being developed, while persons with persistent negative symptoms and limited social competence may find social-skills training useful. In addition, new programs of supported employment may enable some patients to maintain competitive employment.

Visual information-processing impairments in deficit and nondeficit schizophrenia.

OBJECTIVE: Previous studies of covert visuospatial attention in schizophrenia suggest a subtle form of right hemispatial neglect in acutely ill patients but not in chronic, stable patients. Because of previous work documenting various visual information-processing abnormalities in deficit schizophrenia, the authors investigated whether the deficit/nondeficit categorization would help clarify the presence of visual attentional asymmetries in schizophrenia. METHOD: Performance on a covert visuospatial attention task was examined in clinically stable outpatients with schizophrenia (17 in a deficit subgroup and 28 in a nondeficit subgroup) and 25 normal subjects. Peripheral cue and central cue versions of the covert visuospatial attention task, at 100-, 200-, and 800-msec intervals between cue and target, were administered a week apart. RESULTS: The nondeficit patients exhibited a significant and abnormal asymmetry, with slower reaction time to targets presented in the right visual field than in the left visual field. This right visual field disadvantage was found with both versions of the task, but only at the 100-msec cue-target interval. The deficit patients were slowest in overall reaction time but, similar to the normal subjects, showed no asymmetry. CONCLUSIONS: The results are consistent with slower visual information processing in the left compared to the right cerebral hemisphere in nondeficit schizophrenia. This finding cannot be accounted for by differences between the deficit and nondeficit subgroups in demographic characteristics, chronicity, or medication effects, nor is it secondary to generalized cognitive impairment.

Differential effect of clozapine on weight: a controlled study.

OBJECTIVE: This study examined whether clozapine induces more weight gain than haloperidol and whether weight gain is related to clinical improvement. METHOD: The weight and symptoms of 39 outpatients with schizophrenia who were randomly assigned to double-blind treatment with either clozapine or haloperidol were assessed. The weight and symptoms of 33 of the patients who chose to take clozapine during a 1-year follow-up after the study ended were also assessed. RESULTS: The patients treated with clozapine gained significantly more weight over baseline (7%) than the haloperidol-treated patients (1%). Weight gain was not significantly correlated with improvements in either positive or negative symptoms. Fifty-eight percent of the patients followed for 1 year gained at least 10% over their baseline weight. CONCLUSIONS: Weight gain is an important side effect of clozapine and is unrelated to the drug's differential antipsychotic efficacy.

The deficit syndrome in the DSM-IV Field Trial. Part II. Depressive episodes and persecutory beliefs.

Patients with the deficit syndrome are remarkable for their decrease in interest in social relationships, suggesting they have an abnormality in those brain regions controlling social behavior and social cognition. To further assess social behavior and social cognition in this group of patients, we examined the relationships among three aspects of the psychopathology: suspiciousness; major depressive episodes; and the deficit syndrome. These features of psychopathology were examined in two clinical samples: stable outpatients from a research clinic (the MPRC sample), and patients in the DSM-IV Field Trial. In both samples, patients with history of a depressive episode had more severe suspiciousness than those without such a history; other psychotic symptoms were not associated with depressive episodes. In the MPRC sample, patients with the deficit syndrome exhibited less severe suspiciousness than nondeficit patients; in the Field Trial sample, this same comparison had a nonsignificant trend in the same direction. In the Field Trial sample, patients with the deficit syndrome also had less severe delusions with a predominantly social content than did nondeficit patients. These findings suggest suspiciousness is a risk factor for major depression in schizophrenia, and that the decreased interests in social relationships exhibited by deficit syndrome patients is reflected in the content of their delusions.