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.

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.

Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.

Resting-state thalamic dysconnectivity in schizophrenia and relationships with symptoms.

BACKGROUND: Schizophrenia (SZ) is a severe neuropsychiatric disorder associated with disrupted connectivity within the thalamic-cortico-cerebellar network. Resting-state functional connectivity studies have reported thalamic hypoconnectivity with the cerebellum and prefrontal cortex as well as thalamic hyperconnectivity with sensory cortical regions in SZ patients compared with healthy comparison participants (HCs). However, fundamental questions remain regarding the clinical significance of these connectivity abnormalities. METHOD: Resting state seed-based functional connectivity was used to investigate thalamus to whole brain connectivity using multi-site data including 183 SZ patients and 178 matched HCs. Statistical significance was based on a voxel-level FWE-corrected height threshold of p < 0.001. The relationships between positive and negative symptoms of SZ and regions of the brain demonstrating group differences in thalamic connectivity were examined. RESULTS: HC and SZ participants both demonstrated widespread positive connectivity between the thalamus and cortical regions. Compared with HCs, SZ patients had reduced thalamic connectivity with bilateral cerebellum and anterior cingulate cortex. In contrast, SZ patients had greater thalamic connectivity with multiple sensory-motor regions, including bilateral pre- and post-central gyrus, middle/inferior occipital gyrus, and middle/superior temporal gyrus. Thalamus to middle temporal gyrus connectivity was positively correlated with hallucinations and delusions, while thalamus to cerebellar connectivity was negatively correlated with delusions and bizarre behavior. CONCLUSIONS: Thalamic hyperconnectivity with sensory regions and hypoconnectivity with cerebellar regions in combination with their relationship to clinical features of SZ suggest that thalamic dysconnectivity may be a core neurobiological feature of SZ that underpins positive symptoms.

Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium.

BACKGROUND: Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. METHODS: This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores). RESULTS: Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (ß std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged. CONCLUSIONS: Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Newborn insula gray matter volume is prospectively associated with early life adiposity gain.

BACKGROUND: The importance of energy homeostasis brain circuitry in the context of obesity is well established, however, the developmental ontogeny of this circuitry in humans is currently unknown. Here, we investigate the prospective association between newborn gray matter (GM) volume in the insula, a key brain region underlying energy homeostasis, and change in percent body fat accrual over the first six months of postnatal life, an outcome that represents among the most reliable infant predictors of childhood obesity risk. METHODS: A total of 52 infants (29 male, 23 female, gestational age at birth=39(1.5) weeks) were assessed using structural MRI shortly after birth (postnatal age at MRI scan=25.9(12.2) days), and serial Dual X-Ray Absorptiometry shortly after birth (postnatal age at DXA scan 1=24.6(11.4) days) and at six months of age (postnatal age at DXA scan 2=26.7(3.3) weeks). RESULTS: Insula GM volume was inversely associated with change in percent body fat from birth to six-months postnatal age and accounted for 19% of its variance (ß=-3.6%/S.D., P=0.001). This association was driven by the central-posterior portion of the insula, a region of particular importance for gustation and interoception. The direction of this effect is in concordance with observations in adults, and the results remained statistically significant after adjusting for relevant covariates and potential confounding variables. CONCLUSIONS: Altogether, these findings suggest an underlying neural basis of childhood obesity that precedes the influence of the postnatal environment. The identification of plausible brain-related biomarkers of childhood obesity risk that predate the influence of the postnatal obesogenic environment may contribute to an improved understanding of propensity for obesity, early identification of at-risk individuals, and intervention targets for primary prevention.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA Schizophrenia consortium.

OBJECTIVE: Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia. METHOD: This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness. RESULTS: Positive symptom severity was negatively related to STG thickness in both hemispheres (left: ßstd = -0.052; P = 0.021; right: ßstd = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness. CONCLUSION: Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

Huntington's disease cerebrospinal fluid seeds aggregation of mutant huntingtin.

Huntington's disease (HD), a progressive neurodegenerative disease, is caused by an expanded CAG triplet repeat producing a mutant huntingtin protein (mHTT) with a polyglutamine-repeat expansion. Onset of symptoms in mutant huntingtin gene-carrying individuals remains unpredictable. We report that synthetic polyglutamine oligomers and cerebrospinal fluid (CSF) from BACHD transgenic rats and from human HD subjects can seed mutant huntingtin aggregation in a cell model and its cell lysate. Our studies demonstrate that seeding requires the mutant huntingtin template and may reflect an underlying prion-like protein propagation mechanism. Light and cryo-electron microscopy show that synthetic seeds nucleate and enhance mutant huntingtin aggregation. This seeding assay distinguishes HD subjects from healthy and non-HD dementia controls without overlap (blinded samples). Ultimately, this seeding property in HD patient CSF may form the basis of a molecular biomarker assay to monitor HD and evaluate therapies that target mHTT.

Absence of evidence for bornavirus infection in schizophrenia, bipolar disorder and major depressive disorder.

In 1983, reports of antibodies in subjects with major depressive disorder (MDD) to an as-yet uncharacterized infectious agent associated with meningoencephalitis in horses and sheep led to molecular cloning of the genome of a novel, negative-stranded neurotropic virus, Borna disease virus (BDV). This advance has enabled the development of new diagnostic assays, including in situ hybridization, PCR and serology based on recombinant proteins. Since these assays were first implemented in 1990, more than 80 studies have reported an association between BDV and a wide range of human illnesses that include MDD, bipolar disorder (BD), schizophrenia (SZ), anxiety disorder, chronic fatigue syndrome, multiple sclerosis, amyotrophic lateral sclerosis, dementia and glioblastoma multiforme. However, to date there has been no blinded case-control study of the epidemiology of BDV infection. Here, in a United States-based, multi-center, yoked case-control study with standardized methods for clinical assessment and blinded serological and molecular analysis, we report the absence of association of psychiatric illness with antibodies to BDV or with BDV nucleic acids in serially collected serum and white blood cell samples from 396 subjects, a study population comprised of 198 matched pairs of patients and healthy controls (52 SZ/control pairs, 66 BD/control pairs and 80 MDD/control pairs). Our results argue strongly against a role for BDV in the pathogenesis of these psychiatric disorders.

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.

Association study of cannabinoid receptor 1 (CNR1) gene in tardive dyskinesia.

Tardive dyskinesia (TD) is a severe, debilitating movement disorder observed in 25-30% of the patients treated with typical antipsychotics. Cannabinoid receptor 1 (CNR1) activators tend to inhibit movement, an effect prevented by rimonabant and other selective CNR1 antagonists. Furthermore, CNR1 receptor is downregulated in Huntington's disease and upregulated in Parkinson's disease. Twenty tagSNPs spanning the CNR1 gene were analyzed in schizophrenia patients of European ancestry (n=191; 74 with TD). Significant genotypic (P=0.012) and allelic (P=0.012) association was observed with rs806374 (T>C). Carriers of the CC genotype were more likely to be TD positive (CC vs TT+TC, odds ratio=3.4 (1.5-7.8), P=0.003) and had more severe TD (CC vs TT+TC; 9.52±9.2 vs 5.62±6.9, P=0.046). These results indicate a possible role of CNR1 in the development of TD in our patient population. However, these observations are marginal after correcting for multiple testing and need to be replicated in a larger patient population.

Effect of dopamine D3 receptor gene polymorphisms and clozapine treatment response: exploratory analysis of nine polymorphisms and meta-analysis of the Ser9Gly variant.

D2 blockade has been implicated in having a central role in antipsychotic response. However, treatment refractoriness, in spite of complete D2 blockade, as well as the efficacy of clozapine (CLZ) in a portion of this patient population, indicates the involvement of other factors as well. Several lines of evidence suggest a role for D3. Furthermore, an earlier meta-analysis by Jönsson et al. (2003) (n=233) suggested a role for genetic variation in the D3 gene. Relevant to this study, Jönsson et al. found the Ser allele of the D3 serine-to-glycine substitution at amino acid position 9 (Ser9Gly) polymorphism to be associated with worse CLZ response compared with the Gly allele. In this study, we attempt to validate these findings by performing a meta-analysis in a much larger sample (n=758). Eight other variants were also tested in our own sample to explore the possible effect of other regions of the gene. We report a negative but consistent trend across individual studies in our meta-analysis for the DRD3 Ser allele and poor CLZ response. A possible minor role for this single-nucleotide polymorphism cannot be disregarded, as our sample size may have been insufficient. Other DRD3 variants and haplotypes of possible interest were also identified for replication in future studies.

Gene discovery through imaging genetics: identification of two novel genes associated with schizophrenia.

We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.

Association study of tardive dyskinesia and five DRD4 polymorphisms in schizophrenia patients.

Tardive dyskinesia (TD) is a side effect of chronic antipsychotic medication exposure. Abnormalities in dopaminergic activity in the nigro-striatal system have been most often suggested to be involved because the agents that cause TD share in common potent antagonism of dopamine D(2) receptors (DRD2). Thus, a number of studies have focused on the association of dopamine system gene polymorphisms and TD, with the most consistent findings being an association between TD and the Ser9Gly polymorphism of the DRD3 gene and the TaqIA site 3' of the DRD2 gene. The DRD4 gene codes for the third member of the D(2)-like dopamine receptor family, and the variable number tandem-repeat polymorphism in exon 3 of DRD4 has been associated with TD. However, other polymorphisms have not been thoroughly examined. In this study, we investigated five polymorphisms spanning the DRD4 gene and their association with TD in our European Caucasian sample (N=171). Although the exon 3 variable number tandem repeat was not associated with TD, haplotypes consisting of four tag polymorphisms were associated with TD in males. This study suggests that DRD4 may be involved in TD in the Caucasian population, although further replication studies are needed.

Phenylethylamine in paranoid chronic schizophrenia.

Phenylethylamine (PEA) is an endogenous amine that is structurally and pharmacologically related to amphetamine. Urinary PEA excretion is significantly higher in paranoid chronic schizophrenics than in nonparanoid chronic schizophrenics and normal controls. Diet, hospitalization, and medication do not account for differences in PEA concentrations. These findings offer some indication that PEA may be an endogenous amphetamine.

A correlation between platelet monoamine oxidase activity and plasma prolactin concentrations in man.

Increases in plasma prolactin concentrations produced by alpha-methyl-p-tyrosine, a catecholamine synthesis inhibitor, varied inversely with baseline platelet monoamine oxidase activity in 12 patients with chronic schizophrenia. In normal volunteers with low monoamine oxidase activity and in unmedicated patients with chronic schizophrenia, plasma prolactin concentrations varied directly with platelet monoamine oxidase activity. No such relationship was found in normal subjects with high platelet monoamine oxidase activity. These data suggest that platelet monoamine oxidase activity reflects monoaminergic activity in the tubero-infundibular system, which in turn affects plasma prolactin concentrations. This relationship may be important in patients with low platelet monoamine oxidase activity, such as some chronic schizophrenics.

Auditory oddball deficits in schizophrenia: an independent component analysis of the fMRI multisite function BIRN study.

Deficits in the connectivity between brain regions have been suggested to play a major role in the pathophysiology of schizophrenia. A functional magnetic resonance imaging (fMRI) analysis of schizophrenia was implemented using independent component analysis (ICA) to identify multiple temporally cohesive, spatially distributed regions of brain activity that represent functionally connected networks. We hypothesized that functional connectivity differences would be seen in auditory networks comprised of regions such as superior temporal gyrus as well as executive networks that consisted of frontal-parietal areas. Eight networks were found to be implicated in schizophrenia during the auditory oddball paradigm. These included a bilateral temporal network containing the superior and middle temporal gyrus; a default-mode network comprised of the posterior cingulate, precuneus, and middle frontal gyrus; and multiple dorsal lateral prefrontal cortex networks that constituted various levels of between-group differences. Highly task-related sensory networks were also found. These results indicate that patients with schizophrenia show functional connectivity differences in networks related to auditory processing, executive control, and baseline functional activity. Overall, these findings support the idea that the cognitive deficits associated with schizophrenia are widespread and that a functional connectivity approach can help elucidate the neural correlates of this disorder.

Working memory and DLPFC inefficiency in schizophrenia: the FBIRN study.

BACKGROUND: The Functional Imaging Biomedical Informatics Network is a consortium developing methods for multisite functional imaging studies. Both prefrontal hyper- or hypoactivity in chronic schizophrenia have been found in previous studies of working memory. METHODS: In this functional magnetic resonance imaging (fMRI) study of working memory, 128 subjects with chronic schizophrenia and 128 age- and gender-matched controls were recruited from 10 universities around the United States. Subjects performed the Sternberg Item Recognition Paradigm1,2 with memory loads of 1, 3, or 5 items. A region of interest analysis examined the mean BOLD signal change in an atlas-based demarcation of the dorsolateral prefrontal cortex (DLPFC), in both groups, during both the encoding and retrieval phases of the experiment over the various memory loads. RESULTS: Subjects with schizophrenia performed slightly but significantly worse than the healthy volunteers and showed a greater decrease in accuracy and increase in reaction time with increasing memory load. The mean BOLD signal in the DLPFC was significantly greater in the schizophrenic group than the healthy group, particularly in the intermediate load condition. A secondary analysis matched subjects for mean accuracy and found the same BOLD signal hyperresponse in schizophrenics. CONCLUSIONS: The increase in BOLD signal change from minimal to moderate memory loads was greater in the schizophrenic subjects than in controls. This effect remained when age, gender, run, hemisphere, and performance were considered, consistent with inefficient DLPFC function during working memory. These findings from a large multisite sample support the concept not of hyper- or hypofrontality in schizophrenia, but rather DLPFC inefficiency that may be manifested in either direction depending on task demands. This redirects the focus of research from direction of difference to neural mechanisms of inefficiency.

fMRI activity correlated with auditory hallucinations during performance of a working memory task: data from the FBIRN consortium study.

INTRODUCTION: Auditory hallucinations are a hallmark symptom of schizophrenia. The neural basis of auditory hallucinations was examined using data from a working memory task. Data were acquired within a multisite consortium and this unique dataset provided the opportunity to analyze data from a large number of subjects who had been tested on the same procedures across sites. We hypothesized that regions involved in verbal working memory and language processing would show activity that was associated with levels of hallucinations during a condition where subjects were rehearsing the stimuli. METHODS: Data from the Sternberg Item Recognition Paradigm, a working memory task, were acquired during functional magnetic resonance imaging procedures. The data were collected and preprocessed by the functional imaging biomedical informatics research network consortium. Schizophrenic subjects were split into nonhallucinating and hallucinating subgroups and activity during the probe condition (in which subjects rehearsed stimuli) was examined. Levels of activation from contrast images for the probe phase (collapsed over levels of memory load) of the working memory task were also correlated with levels of auditory hallucinations from the Scale for the Assessment of Positive Symptoms scores. RESULTS: Patients with auditory hallucinations (relative to nonhallucinating subjects) showed decreased activity during the probe condition in verbal working memory/language processing regions, including the superior temporal and inferior parietal regions. These regions also showed associations between activity and levels of hallucinations in a correlation analysis. DISCUSSION: The association between activation and hallucinations scores in the left hemisphere language/working memory regions replicates the findings of previous studies and provides converging evidence for the association between superior temporal abnormalities and auditory hallucinations.