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Schizotypy is a multidimensional construct that captures a continuum of risk for developing schizophrenia-spectrum psychopathology. Existing 3-factor models of schizotypy, consisting of positive, negative, and disorganized dimensions have yielded mixed evidence of genetic continuity with schizophrenia using polygenic risk scores. Here, we propose an approach that involves splitting positive and negative schizotypy into more specific subdimensions that are phenotypically continuous with distinct positive symptoms and negative symptoms recognized in clinical schizophrenia. We used item response theory to derive high-precision estimates of psychometric schizotypy using 251 self-report items obtained from a non-clinical sample of 727 (424 females) adults. These subdimensions were organized hierarchically using structural equation modeling into 3 empirically independent higher-order dimensions enabling associations with polygenic risk for schizophrenia to be examined at different levels of phenotypic generality and specificity. Results revealed that polygenic risk for schizophrenia was associated with variance specific to delusional experiences (γ = 0.093, P = .001) and reduced social interest and engagement (γ = 0.076, P = .020), and these effects were not mediated via the higher-order general, positive, or negative schizotypy factors. We further fractionated general intellectual functioning into fluid and crystallized intelligence in 446 (246 females) participants that underwent onsite cognitive assessment. Polygenic risk scores explained 3.6% of the variance in crystallized intelligence. Our precision phenotyping approach could be used to enhance the etiologic signal in future genetic association studies and improve the detection and prevention of schizophrenia-spectrum psychopathology.

Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.

Animal neurophysiological studies have identified neural signals within dorsal frontoparietal areas that trace a perceptual decision by accumulating sensory evidence over time and trigger action upon reaching a threshold. Although analogous accumulation-to-bound signals are identifiable on extracranial human electroencephalography, their cortical origins remain unknown. Here neural metrics of human evidence accumulation, predictive of the speed of perceptual reports, were isolated using electroencephalography and related to dorsal frontoparietal network (dFPN) connectivity using diffusion and resting-state functional magnetic resonance imaging. The build-up rate of evidence accumulation mediated the relationship between the white matter macrostructure of dFPN pathways and the efficiency of perceptual reports. This association between steeper build-up rates of evidence accumulation and the dFPN was recapitulated in the resting-state networks. Stronger connectivity between dFPN regions is thus associated with faster evidence accumulation and speeded perceptual decisions. Our findings identify an integrated network for perceptual decisions that may be targeted for neurorehabilitation in cognitive disorders. How efficiently humans make perceptual decisions varies between people. Based on EEG and structural and functional MRI data, Brosnan et al. suggest a role for dorsal frontoparietal network connectivity in the speed of perceptual decisions.

ImportancePsychotic illness is associated with anatomically distributed grey matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown.ObjectiveTo test the hypothesis that brain network architecture constrains cross-sectional and longitudinal grey matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicentres from which volume loss spreads.Design, Settings, ParticipantsThis study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naïve first episode psychosis (N=59) and a group of medicated patients within 3 years of psychosis onset (N=121). Late-stage cohorts comprised two independent samples of people with established schizophrenia (N=136 in total). Each patient group had a corresponding matched control group (N=218 in total). A further independent sample of healthy adults (N=346) was used to derive representative structural and functional brain networks for modelling of network-based spreading processes. We additionally examined longitudinal illness-related and antipsychotic-related grey matter changes over 3 and 12 months using a triple-blind randomised placebo-control MRI study of the antipsychotic-naïve patients. All data were collected between April 2008 and January 2020, and analyses were performed between March 2021 and January 2023.Main Outcomes and MeasuresWe used coordinated deformation models to predict the extent of grey matter volume change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicentres of volume loss, we used a network diffusion model to simulate the spread of pathology from different seed regions. Correlations between predicted and empirical spatial patterns of grey matter volume alterations were used to quantify model performance.ResultsIn both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately predicted by coordinated deformation models constrained by structural, rather than functional, network architecture (. 46 52;p< .001) and antipsychotic exposure (r> .50;p< .001). Diffusion modelling consistently identified, across all four datasets, the anterior hippocampus as a putative epicentre of pathological spread in psychosis (all p< .05). Epicentres of longitudinal grey matter loss were apparent posteriorly early in the illness and shifted anteriorly to prefrontal cortex with illness progression.Conclusion and RelevanceOur findings highlight a robust and central role for white matter fibres as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicentre of early brain pathology from which dysfunction may spread to affect connected areas.Key pointsQuestionAre grey matter changes across the psychosis continuum constrained by brain network architecture and are certain regions epicentres of volume loss?FindingsAcross four independent samples spanning different stages of psychotic illness, grey matter alterations are strongly constrained by the underlying architecture of the brain’s axonal pathways and the hippocampus is consistently identified as a putative source from which volume-loss may spread to connected regions.MeaningWhite matter fibres may act as conduits for the spread of pathology across all stages of psychotic illness and medial temporal regions play a critical role in the origins of grey matter reductions.

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.

Regional heterogeneity in the brain’s transcriptional landscape supports complex neuronal dynamics., Brain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles or MRI-derived estimates of myeloarchitecture. We further show that regional transcriptional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional-activity time scales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptomic data to constrain models of large-scale brain function.

BackgroundAltered functional connectivity (FC) is a common finding in resting-state functional Magnetic Resonance Imaging (rs-fMRI) studies of people with psychosis, yet how FC disturbances evolve in the early stages of illness, and how antipsychotics may influence the temporal evolution of these disturbances, remains unclear. Here, we scanned first episode psychosis (FEP) patients who were and were not exposed to antipsychotic medication during the first six months of illness at baseline, three months, and 12 months, to characterize how FC changes over time and in relation to medication use.MethodsSixty-two antipsychotic-naïve patients with FEP received either an atypical antipsychotic or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n=27) was also recruited. A total of 202 rs-fMRI scans were obtained across three timepoints: baseline, 3-months and 12-months. Our primary aim was to differentiate patterns of FC in antipsychotic-treated and antipsychotic-naive patients within the first 3 months of treatment, and to examine associations with clinical and functional outcomes. A secondary aim was to investigate long-term effects at the 12-month timepoint.ResultsAt baseline, FEP patients showed widespread functional dysconnectivity in comparison to controls, with reductions predominantly affecting interactions between the default mode network (DMN), limbic systems, and the rest of the brain. From baseline to 3 months, patients receiving placebo showed increased FC principally within the same systems, and some of these changes correlated with improved clinical outcomes. Antipsychotic exposure was associated with increased FC primarily between the thalamus and the rest of the brain. At the 12-month follow-up, antipsychotic treatment was associated with a prolonged increase of FC primarily in the DMN and limbic systems.Conclusions and RelevanceAntipsychotic-naïve FEP patients show widespread functional dysconnectivity at baseline, followed by an early normalization of DMN and paralimbic dysfunction in patients receiving a psychosocial intervention only. Antipsychotic exposure is associated with distinct FC changes, principally concentrated on thalamo-cortical and limbic networks.

Obsessive-compulsive disorder (OCD) is a symptomatically heterogeneous disease. Symptoms of OCD can be grouped into a six-factor structure including washing, checking, neutralizing, obsessing, ordering and hoarding. These different symptom profiles might be one of the critical factors contributing to the inconsistent neuroanatomical findings in OCD according to the literature. In this study, whole-brain voxel-based morphometry was used to examine neuroanatomical alterations in gray matter (GM) for OCD compared to healthy controls, and the variations associated with differing symptoms of OCD. The high-quality structural imaging data from 39 OCD individuals and 42 age-matched healthy controls were recruited. First, we found increased cortical GM volume in the left postcentral gyrus in OCD participants compared to healthy controls. Next, six independent regression analyses were conducted to examine the correlation between OCD symptom dimensions and inter-individual variation in neuroanatomy. After a rigorous multiple comparison correction, greater hoarding symptom was robustly found associated with greater GM volumes at various frontotemporal regions (including orbitofrontal, middle frontal and superior temporal GMs). Additionally, greater washing symptoms were associated with increased GM volume at the superior temporal cortex. The symptom-specific GM alterations observed here support the notion that OCD is an etiologically heterogeneous disorder, with both overlapping and distinct neuroanatomical structure across symptom dimensions.

Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signaling or impaired top-down cortical regulation. Here, we used spectral dynamic causal modelling (DCM) of resting-state functional magnetic resonance imaging (fMRI) to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis (FEP) patients and 23 controls and an independent sample of 36 patients with established schizophrenia (SCZ) patients and 100 controls. We found that midbrain and thalamic connectivity were implicated across both patient groups. Dysconnectivity in FEP patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in SCZ patients. In another independent sample of 33 healthy individuals who underwent concurrent fMRI and [18F]DOPA positron emission tomography, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits as those associated with psychotic symptom severity in patients. Our findings thus indicate that subcortical dysconnectivity is salient in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signaling are closely related to striatal dopamine synthesis capacity, which is a robust risk marker for psychosis.

The symptoms of psychosis are proposed to lie on continuous distribution of severity. Expressions of psychotic symptoms have been linked with the function of the brain’s fronto-striato-thalamic (FST) circuits. This thesis investigated the role of this circuitry in the emergence of psychotic symptoms across the psychosis continuum. The findings suggest that distinct stages of psychosis, from mild psychotic symptoms in the general population to established psychotic illness, demonstrated similar connectivity patterns of FST circuits that was also associated with dopamine functions. A prominent role for subcortical dysconnectivity was identified in early psychosis, presenting a promising target for treatment development.

Brain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles and MRI-derived estimates of myeloarchitecture. We further show that regional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional activity timescales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptional data to constrain models of large-scale brain function.

Changes in brain volume are a common finding in Magnetic Resonance Imaging (MRI) studies of people with psychosis and numerous longitudinal studies suggest that volume deficits progress with illness duration. However, a major unresolved question concerns whether these changes are driven by the underlying illness or represent iatrogenic effects of antipsychotic medication. In this study, 62 antipsychotic-naïve patients with first-episode psychosis (FEP) received either a second-generation antipsychotic (risperidone or paliperidone) or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n = 27) was also recruited. Structural MRI scans were obtained at baseline, 3 months and 12 months. Our primary aim was to differentiate illness-related brain volume changes from medication-related changes within the first 3 months of treatment. We secondarily investigated long-term effects at the 12-month timepoint. From baseline to 3 months, we observed a significant group x time interaction in the pallidum (p

Changes in brain volume are a common finding in Magnetic Resonance Imaging (MRI) studies of people with psychosis and numerous longitudinal studies suggest that volume deficits progress with illness duration. However, a major unresolved question concerns whether these changes are driven by the underlying illness or represent iatrogenic effects of antipsychotic medication. Here, we report MRI findings from a triple-blind randomised placebo-controlled study where 62 antipsychotic-naïve patients with first episode psychosis (FEP) received either an atypical antipsychotic or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n=27) was also recruited. Structural MRI scans were obtained at baseline, 3-months and 12- months. Our primary aim was to differentiate illness-related brain volume changes from medication-related changes within the first 3 months of treatment. We secondarily investigated long-term effects at the 12-month timepoint. From baseline to 3 months, we observed a significant group x time interaction in the pallidum (p < 0.05 FWE-corrected), such that patients receiving antipsychotic medication showed increased volume, patients on placebo showed decreased volume, and healthy controls showed no change. In patients, a greater increase in pallidal grey matter volume over 3 months was associated with a greater reduction in symptom severity. We additionally found preliminary evidence for illness- related volume reductions in prefrontal cortices at 12 months and medication-related volume reductions in cerebellum at both 3-months and 12-months. Our findings indicate that psychotic illness and antipsychotic exposure exert distinct and spatially distributed effects on brain volume. Our results align with prior work in suggesting that the therapeutic efficacy of antipsychotic medications may be primarily mediated through their effects on the basal ganglia.

Aerobic exercise (AE) interventions represent promising therapeutic approaches in disorders that compromise hippocampal integrity, but a more comprehensive account of the neural mechanisms stimulated by AE in the human brain is needed. We conducted a longitudinal pilot-study to assess the impact of a 12-week AE intervention on hippocampal structure and function in 10 healthy, human participants (50% females; 25-59 years). Using a novel combination of multimodal MRI techniques, we found significant increases in left hippocampal volume, Cornu Ammonis subfield area 1, NAA concentration and immediate verbal recall performance. Our preliminary findings highlight the utility of a multimodal approach in assessing hippocampal integrity.

Key Points Question Are there different patterns of brain connectivity in antipsychotic-treated and antipsychotic-naive patients with psychosis, and how do these patterns evolve over time? Findings In this secondary analysis of a triple-blind, longitudinal, placebo-controlled, randomized clinical trial in antipsychotic-naive patients, patients showed widespread brain dysconnectivity at baseline relative to healthy controls. Patients treated with therapy and placebo or with therapy and antipsychotics showed evidence of circuit-specific and treatment-specific normalization of connectivity over time. Meaning In this study, some prominent baseline connectivity differences in first-episode psychosis normalized with both psychosocial therapy and placebo early in the illness course, with antipsychotics exerting circuit-specific effects., This secondary analysis of a randomized clinical trial investigates differential patterns of brain connectivity in antipsychotic-treated and antipsychotic-naive patients with psychosis and how these patterns change over time., Importance Altered functional connectivity (FC) is a common finding in resting-state functional magnetic resonance imaging (rs-fMRI) studies of people with psychosis, yet how FC disturbances evolve in the early stages of illness, and how antipsychotic treatment influences these disturbances, remains unknown. Objective To investigate longitudinal FC changes in antipsychotic-naive and antipsychotic-treated patients with first-episode psychosis (FEP). Design, Setting, and Participants This secondary analysis of a triple-blind, randomized clinical trial was conducted over a 5-year recruitment period between April 2008 and December 2016 with 59 antipsychotic-naive patients with FEP receiving either a second-generation antipsychotic or a placebo pill over a treatment period of 6 months. Participants were required to have low suicidality and aggression, to have a duration of untreated psychosis of less than 6 months, and to be living in stable accommodations with social support. Both FEP groups received intensive psychosocial therapy. A healthy control group was also recruited. Participants completed rs-fMRI scans at baseline, 3 months, and 12 months. Data were analyzed from May 2019 to August 2020. Interventions Resting-state functional MRI was used to probe brain FC. Patients received either a second-generation antipsychotic or a matched placebo tablet. Both patient groups received a manualized psychosocial intervention. Main Outcomes and Measures The primary outcomes of this analysis were to investigate (1) FC differences between patients and controls at baseline; (2) FC changes in medicated and unmedicated patients between baseline and 3 months; and (3) associations between longitudinal FC changes and clinical outcomes. An additional aim was to investigate long-term FC changes at 12 months after baseline. These outcomes were not preregistered. Results Data were analyzed for 59 patients (antipsychotic medication plus psychosocial treatment: 28 [47.5%]; mean [SD] age, 19.5 [3.0] years; 15 men [53.6%]; placebo plus psychosocial treatment: 31 [52.5%]; mean [SD] age, 18.8 [2.7]; 16 men [51.6%]) and 27 control individuals (mean [SD] age, 21.9 [1.9] years). At baseline, patients showed widespread functional dysconnectivity compared with controls, with reductions predominantly affecting interactions between the default mode network, limbic systems, and the rest of the brain. From baseline to 3 months, patients receiving placebo showed increased FC principally within the same systems; some of these changes correlated with improved clinical outcomes (canonical correlation analysis R = 0.901; familywise error–corrected P = .005). Antipsychotic exposure was associated with increased FC primarily between the thalamus and the rest of the brain. Conclusions and Relevance In this secondary analysis of a clinical trial, antipsychotic-naive patients with FEP showed widespread functional dysconnectivity at baseline, followed by an early normalization of default mode network and cortical limbic dysfunction in patients receiving placebo and psychosocial intervention. Antipsychotic exposure was associated with FC changes concentrated on thalamocortical networks. Trial Registration ACTRN12607000608460

Background Neuroimaging studies have found dysconnectivity of frontostriatal circuits across a broad spectrum of psychotic symptoms. However, it is unknown whether dysconnectivity within frontostriatal circuits originates from disrupted bottom-up or top-down control signaling within these systems. Here, we used dynamic causal modelling (DCM) to examine the effective connectivity of frontostriatal systems in first-episode psychosis (FEP). Methods A total of 55 FEP patients (26 males; mean [SD] age = 19.24 [2.89]) and 24 healthy controls (15 males; mean [SD] age = 21.83 [1.93]) underwent a resting-state functional magnetic resonance imaging protocol. Biologically plausible connections between eight left hemisphere regions encompassing the dorsal and ventral frontostriatal systems were modelled using spectral DCM. The regions comprise dorsolateral prefrontal cortex, ventromedial prefrontal cortex, anterior hippocampus, amygdala, dorsal caudate, nucleus accumbens, thalamus, and the midbrain. Effective connectivity between groups were assessed using a parametric Bayesian model. Associations between effective connectivity parameters and positive symptoms, measured by the Brief Psychiatric Rating Scale positive subscale, was assessed in the patient group in a separate Bayesian general linear model. Results DCM shows evidence for differences in effective connectivity between patients and healthy controls, namely in the bottom-down connections distributed in the frontostriatal system encompassing the hippocampus, amygdala, striatum, and midbrain. Compared to healthy controls, patients also demonstrated increased disinhibition of the midbrain. In patients, positive symptoms are associated with increased top-down connections to the midbrain. Outgoing connection from the midbrain to the nucleus accumbens is also increased in association with positive symptoms. Discussion Aberrant top-down connectivity in the frontostriatal system in patients is consistent with top-down dysregulation of dopamine function in FEP, as dopaminergic activity in the midbrain is proposed to be under the control of higher brain areas. In patients, increased self-inhibition of the midbrain, as well as symptom associations in both ingoing and outgoing connections of this region, are congruous with hyperactivity of the midbrain as proposed by the dopamine dysregulation hypothesis. Here, we demonstrate that mathematical models of brain imaging signals can be used to identify the key disruptions driving brain circuit dysfunction, identifying new targets for treatment.

One of the most controversial procedures in the analysis of resting-state functional magnetic resonance imaging (rsfMRI) data is global signal regression (GSR): the removal, via linear regression, of the mean signal averaged over the entire brain. On one hand, the global mean signal contains variance associated with respiratory, scanner-, and motion-related artifacts, and its removal via GSR improves various quality-control metrics, enhances the anatomical specificity of functional-connectivity patterns, and can increase the behavioral variance explained by such patterns. On the other hand, GSR alters the distribution of regional signal correlations in the brain, can induce artifactual anticorrelations, may remove real neural signal, and can distort case-control comparisons of functional-connectivity measures. Global signal fluctuations can be identified visually from a matrix of colour-coded signal intensities, called a carpet plot, in which rows represent voxels and columns represent time. Prior to GSR, large, periodic bands of coherent signal changes that affect most of the brain are often apparent; after GSR, these apparently global changes are greatly diminished. Here, using three independent datasets, we show that reordering carpet plots to emphasize cluster structure in the data reveals a greater diversity of spatially widespread signal deflections (WSDs) than previously thought. Their precise form varies across time and participants, and GSR is only effective in removing specific kinds of WSDs. We present an alternative, iterative correction method called Diffuse Cluster Estimation and Regression (DiCER), that identifies representative signals associated with large clusters of coherent voxels. DiCER is more effective than GSR at removing diverse WSDs as visualized in carpet plots, reduces correlations between functional connectivity and head-motion estimates, reduces inter-individual variability in global correlation structure, and results in comparable or improved identification of canonical functional-connectivity networks. Using task fMRI data across 47 contrasts from 7 tasks in the Human Connectome Project, we also present evidence that DiCER is more successful than GSR in preserving the spatial structure of expected task-related activation patterns. Our findings indicate that care must be exercised when examining WSDs (and their possible removal) in rsfMRI data, and that DiCER is a viable alternative to GSR for removing anatomically widespread and temporally coherent signals. All code for implementing DiCER and replicating our results is available at https://github.com/BMHLab/DiCER.

Dysfunction of dorsal corticostriatal (CST) circuitry is thought to play an important role in psychosis. Here, we use multivariate analysis to characterize covariance between CST functional connectivity and psychosis-like experiences (PLEs) in non-clinical individuals. In 353 healthy adults (155 males), we use partial least squares (PLS) to identify latent variables (LV) describing covariance between seven PLE questionnaire measures and functional connectivity estimated between each of six striatal seed regions and the rest of the brain using multiband resting-state fMRI. Hypothesis-driven PLS of the dorsal caudate (DC) seed identified one significant LV, accounting for 23.88% of covariance, with loadings from nearly all PLE subscales. Cortical regions implicated in this LV comprise anterior cingulate and left dorsolateral prefrontal cortex. Lower connectivity between these cortical areas and the DC seed was associated with more severe PLEs. Using multivariate modeling, we identified an association between dorsal CST connectivity and PLEs in the general community that implicates similar brain regions to those identified in patient groups. Our results highlight that the severity of both positive/negative symptom-like PLEs is related with functional coupling between the DC and dorsolateral PFC, suggesting this neural circuit may play a role in mediating risk for general psychosis-related psychopathology.

BackgroundPsychotic symptoms are proposed lie on a continuum, ranging from isolated psychosis-like experiences (PLEs) in non-clinical populations to frank disorder. Here, we investigate neurobiological correlates of this symptomatologic continuum by examining whether functional connectivity of dorsal corticostriatal circuitry, which is disrupted in patients and high-risk individuals, is associated with the severity of subclinical PLEs.MethodsA community sample of 672 adults with no history of psychiatric or neurological illnesses completed a battery of seven questionnaires spanning various PLE domains. Principal component analysis (PCA) estimated major dimensions of PLEs from the questionnaires. PCA dimension scores were then correlated with whole-brain voxelwise functional connectivity (FC) maps of the striatum in a subset of 353 participants who completed a resting-state neuroimaging protocol.ResultsPCA identified two dimensions of PLEs accounting for 62.57% of variance in the measures, corresponding to positive and negative PLEs. Reduced FC between the dorsal striatum and prefrontal cortex correlated with higher positive PLEs. Negative PLEs correlated with increased FC between the dorsal striatum and visual and sensorimotor areas. In the ventral corticostriatal system, positive and negative PLEs were both associated with FC between the ventro-rostral putamen and sensorimotor cortices.ConclusionsConsistent with past findings in patients and high-risk individuals, subthreshold positive symptomatology is associated with reduced FC of the dorsal circuit. These findings suggest that the connectivity of this circuit tracks the expression of psychotic phenomena across a broad spectrum of severity, extending from the subclinical domain to clinical diagnosis.