Neural mechanisms of psychedelic visual imagery.

Visual alterations under classic psychedelics can include rich phenomenological accounts of eyes-closed imagery. Preclinical evidence suggests agonism of the 5-HT2A receptor may reduce synaptic gain to produce psychedelic-induced imagery. However, this has not been investigated in humans. To infer the directed connectivity changes to visual connectivity underlying psychedelic visual imagery in healthy adults, a double-blind, randomised, placebo-controlled, cross-over study was performed, and dynamic causal modelling was applied to the resting state eyes-closed functional MRI scans of 24 subjects after administration of 0.2 mg/kg of the serotonergic psychedelic drug, psilocybin (magic mushrooms), or placebo. The effective connectivity model included the early visual area, fusiform gyrus, intraparietal sulcus, and inferior frontal gyrus. We observed a pattern of increased self-inhibition of both early visual and higher visual-association regions under psilocybin that was consistent with preclinical findings. We also observed a pattern of reduced inhibition from visual-association regions to earlier visual areas that indicated top-down connectivity is enhanced during visual imagery. The results were analysed with behavioural measures taken immediately after the scans, suggesting psilocybin-induced decreased sensitivity to neural inputs is associated with the perception of eyes-closed visual imagery. The findings inform our basic and clinical understanding of visual perception. They reveal neural mechanisms that, by affecting balance, may increase the impact of top-down feedback connectivity on perception, which could contribute to the visual imagery seen with eyes-closed during psychedelic experiences.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Accelerated cortical thinning precedes and predicts conversion to psychosis: The NAPLS3 longitudinal study of youth at clinical high-risk.

Progressive grey matter loss has been demonstrated among clinical high-risk (CHR) individuals who convert to psychosis, but it is unknown whether these changes occur prior to psychosis onset. Identifying illness-related neurobiological mechanisms that occur prior to conversion is essential for targeted early intervention. Among participants in the third wave of the North American Prodrome Longitudinal Study (NAPLS3), this report investigated if steeper cortical thinning was observable prior to psychosis onset among CHR individuals who ultimately converted (CHR-C) and assessed the shortest possible time interval in which rates of cortical thinning differ between CHR-C, CHR non-converters (CHR-NC), and health controls (HC). 338 CHR-NC, 42 CHR-C, and 62 HC participants (age 19.3±4.2, 44.8% female, 52.5% racial/ethnic minority) completed up to 5 MRI scans across 8 months. Accelerated thinning among CHR-C compared to CHR-NC and HC was observed in multiple prefrontal, temporal, and parietal cortical regions. CHR-NC also exhibited accelerated cortical thinning compared to HC in several of these areas. Greater percent decrease in cortical thickness was observed among CHR-C compared to other groups across 2.9±1.8 months, on average, in several cortical areas. ROC analyses discriminating CHR-C from CHR-NC by percent thickness change in a left hemisphere region of interest, scanner, age, age2, and sex had an AUC of 0.74, with model predictive power driven primarily by percent thickness change. Findings indicate that accelerated cortical thinning precedes psychosis onset and differentiates CHR-C from CHR-NC and HC across short time intervals. Mechanisms underlying cortical thinning may provide novel treatment targets prior to psychosis onset.

The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen's d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen's d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Effects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model.

The synaptic balance between excitation and inhibition (E/I balance) is a fundamental principle of cortical circuits, and disruptions in E/I balance are commonly linked to cognitive deficits such as impaired decision-making. Explanatory gaps remain in a mechanistic understanding of how E/I balance contributes to cognitive computations, and how E/I disruptions at the synaptic level can propagate to induce behavioral deficits. Here, we studied how E/I perturbations may impair perceptual decision-making in a biophysically-based association cortical circuit model. We found that both elevating and lowering E/I ratio, via NMDA receptor (NMDAR) hypofunction at inhibitory interneurons and excitatory pyramidal neurons, respectively, can similarly impair psychometric performance, following an inverted-U dependence. Nonetheless, these E/I perturbations differentially alter the process of evidence accumulation across time. Under elevated E/I ratio, decision-making is impulsive, overweighting early evidence and underweighting late evidence. Under lowered E/I ratio, decision-making is indecisive, with both evidence integration and winner-take-all competition weakened. The distinct time courses of evidence accumulation at the circuit level can be measured at the behavioral level, using multiple psychophysical task paradigms which provide dissociable predictions. These results are well captured by a generalized drift-diffusion model (DDM) with self-coupling, implementing leaky or unstable integration, which thereby links biophysical circuit modeling to algorithmic process modeling and facilitates model fitting to behavioral choice data. In general, our findings characterize critical roles of cortical E/I balance in cognitive function, bridging from biophysical to behavioral levels of analysis.SIGNIFICANCE STATEMENT Cognitive deficits in multiple neuropsychiatric disorders, including schizophrenia, have been associated with alterations in the balance of synaptic excitation and inhibition (E/I) in cerebral cortical circuits. However, the circuit mechanisms by which E/I imbalance leads to cognitive deficits in decision-making have remained unclear. We used a computational model of decision-making in cortical circuits to study the neural and behavioral effects of E/I imbalance. We found that elevating and lowering E/I ratio produce distinct modes of dysfunction in decision-making processes, which can be dissociated in behavior through psychophysical task paradigms. The biophysical circuit model can be mapped onto a psychological model of decision-making which can facilitate experimental tests of model predictions.

Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography.

BACKGROUND: Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles. METHODS: We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT). RESULTS: The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected). CONCLUSION: Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals.

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Greater male than female variability in regional brain structure across the lifespan.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Thalamic dysconnectivity in the psychosis risk syndrome and early illness schizophrenia.

BACKGROUND: Schizophrenia (SZ) is associated with thalamic dysconnectivity. Compared to healthy controls (HCs), individuals with SZ have hyperconnectivity with sensory regions, and hypoconnectivity with cerebellar, thalamic, and prefrontal regions. Despite replication of this pattern in chronically ill individuals, less is known about when these abnormalities emerge in the illness course and if they are present prior to illness onset. METHODS: Resting-state functional magnetic resonance imaging data were collected from psychosis risk syndrome (PRS) youth (n = 45), early illness SZ (ESZ) (n = 74) patients, and HCs (n = 85). Age-adjusted functional connectivity, seeded from the thalamus, was compared among the groups. RESULTS: Significant effects of group were observed in left and right middle temporal regions, left and right superior temporal regions, left cerebellum, and bilateral thalamus. Compared to HCs, ESZ demonstrated hyperconnectivity to all temporal lobe regions and reduced connectivity with cerebellar, anterior cingulate, and thalamic regions. Compared to HCs, PRS demonstrated hyperconnectivity with the left and right middle temporal regions, and hypoconnectivity with the cerebellar and other thalamic regions. Compared to PRS participants, ESZ participants were hyperconnected to temporal regions, but did not differ from PRS in hypoconnectivity with cerebellar and thalamic regions. Thalamic dysconnectivity was unrelated to positive symptom severity in ESZ or PRS groups. CONCLUSIONS: PRS individuals demonstrated an intermediate level of thalamic dysconnectivity, whereas ESZ showed a pattern consistent with prior observations in chronic samples. These cross-sectional findings suggest that thalamic dysconnectivity may occur prior to illness onset and become more pronounced in early illness stages.

White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis.

Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1-5 over 1 year) in 286 subjects (aged 12-32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p < 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis-regardless of transition outcome-is characterized by subtle age-related white matter changes that occur in tandem with development.

Transcranial direct current stimulation targeting the medial prefrontal cortex modulates functional connectivity and enhances safety learning in obsessive-compulsive disorder: Results from two pilot studies.

BACKGROUND: Exposed-based psychotherapy is a mainstay of treatment for obsessive-compulsive disorder (OCD) and anxious psychopathology. The medial prefrontal cortex (mPFC) and the default mode network (DMN), which is anchored by the mPFC, promote safety learning. Neuromodulation targeting the mPFC might augment therapeutic safety learning and enhance response to exposure-based therapies. METHODS: To characterize the effects of mPFC neuromodulation on functional connectivity, 17 community volunteers completed resting-state functional magnetic resonance imaging scans before and after 20 min of frontopolar anodal multifocal transcranial direct current stimulation (tDCS). To examine the effects of tDCS on therapeutic safety learning, 24 patients with OCD completed a pilot randomized clinical trial; they were randomly assigned (double-blind, 50:50) to receive active or sham frontopolar tDCS before completing an in vivo exposure and response prevention (ERP) challenge. Changes in subjective emotional distress during the ERP challenge were used to index therapeutic safety learning. RESULTS: In community volunteers, frontal pole functional connectivity with the middle and superior frontal gyri increased, while connectivity with the anterior insula and basal ganglia decreased (ps < .001, corrected) after tDCS; functional connectivity between DMN and salience network also decreased after tDCS (ps < .001, corrected). OCD patients who received active tDCS exhibited more rapid therapeutic safety learning (ps < .05) during the ERP challenge than patients who received sham tDCS. CONCLUSIONS: Frontopolar tDCS may modulate mPFC and DMN functional connectivity and can accelerate therapeutic safety learning. Though limited by small samples, these findings motivate further exploration of the effects of frontopolar tDCS on neural and behavioral targets associated with exposure-based psychotherapies.

A Whole-Brain and Cross-Diagnostic Perspective on Functional Brain Network Dysfunction.

A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations appear to support theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in a broad, whole-brain perspective. Using a graph distance approach-connectome-wide similarity-we found that whole-brain resting-state functional network organization is highly similar across groups of individuals with and without a variety of mental diseases. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease, those differences are informative. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases. Such small network alterations suggest the possibility that small, well-targeted alterations to brain network organization may provide meaningful improvements for a variety of mental disorders.

Characterizing effects of age, sex and psychosis symptoms on thalamocortical functional connectivity in youth.

The thalamus is composed of multiple nuclei densely connected with the cortex in an organized manner, forming parallel thalamocortical networks critical to sensory, motor, and cognitive functioning. Thalamocortical circuit dysfunction has been implicated in multiple neurodevelopmental disorders, including schizophrenia, which also often exhibit sex differences in prevalence, clinical characteristics, and neuropathology. However, very little is known about developmental and sex effects on thalamocortical networks in youth. The present study characterized the effects of age, sex and psychosis symptomatology in anatomically constrained thalamocortical networks in a large community sample of youth (n = 1100, aged 8-21) from the Philadelphia Neurodevelopmental Cohort (PNC). Cortical functional connectivity of seven anatomically defined thalamic nuclear groups were examined: anterior, mediodorsal, ventral lateral, ventral posterolateral, pulvinar, medial and lateral geniculate nuclear groups. Age and sex effects were characterized using complementary thalamic region-of-interest (ROI) to cortical ROI and voxel-wise analyses. Effects of clinical symptomatology were analyzed by separating youth into three groups based on their clinical symptoms; typically developing youth (n = 298), psychosis spectrum youth (n = 320), and youth with other psychopathologies (n = 482). As an exploratory analysis, association with PRIME scores were used as a dimensional measure of psychopathology. Age effects were broadly characterized by decreasing connectivity with sensory/motor cortical areas, and increasing connectivity with heteromodal prefrontal and parietal cortical areas. This pattern was most pronounced for thalamic motor and sensory nuclei. Females showed greater connectivity between multiple thalamic nuclear groups and the visual cortex compared to males, while males showed greater connectivity with the inferior frontal and orbitofrontal cortices. Youth with psychosis spectrum symptoms showed a subtle decrease in thalamic connectivity with the premotor and prefrontal cortices. Across all youth, greater PRIME scores were associated with lower connectivity between the prefrontal cortex and mediodorsal thalamus. By characterizing typical development in anatomically constrained thalamocortical networks, this study provides an anchor for conceptualizing disruptions to the integrity of these networks observed in neurodevelopmental disorders.

Mapping data-driven individualized neurobehavioral phenotypes in heavy alcohol drinkers.

OBJECTIVE: Recent studies have examined the factor structure and associated correlates of three neurofunctional domains, executive function, incentive salience, and negative emotionality in the development and maintenance of alcohol use disorders in clinical samples. The current study sought to replicate and extend prior work by testing this 3-factor model, utilizing both exact and similar phenotypic measures, as well as novel measures, in a non-treatment-seeking sample. METHODS: Self-report measures of alcohol addiction, impulsivity, behavior, and exposure to early-life stress were collected as part of baseline assessments for alcohol imaging and pharmacotherapy studies in 335 individuals. Confirmatory factor analysis (CFA) was used to examine model structure and fit. A multiple indicators, multiple causes (MIMIC) model identified predictors of latent factors identified by CFA. RESULTS: Results supported an intercorrelated model with three factors: executive function, incentive salience, and emotionality. All factors were associated with current AUD, and incentive salience was uniquely associated with past 30-day drinking frequency. MIMIC results identified multiple significant predictors of these latent factors, including history of alcohol use disorder, positive family history of alcohol dependence, earlier age of first drink, and a history of childhood emotional abuse and physical neglect. CONCLUSIONS: Our results support an intercorrelated 3-factor model of neurofunctional domains in alcohol use models, consistent with published findings. Because childhood physical neglect was a significant predictor of all latent factors, these results also highlight the significant negative impact of childhood neglect on later addiction development.

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Dissociable Disruptions in Thalamic and Hippocampal Resting-State Functional Connectivity in Youth with 22q11.2 Deletions.

The 22q11.2 deletion syndrome (22q11DS) is a recurrent copy number variant with high penetrance for developmental neuropsychiatric disorders. Study of individuals with 22q11DS therefore may offer key insights into neural mechanisms underlying such complex illnesses. Resting-state functional connectivity MRI studies in idiopathic schizophrenia have consistently revealed disruption of thalamic and hippocampal circuitry. Here, we sought to test whether this circuitry is similarly disrupted in the context of this genetic high-risk condition. To this end, resting-state functional connectivity patterns were assessed in a sample of human youth with 22q11DS (n = 42; 59.5% female) and demographically matched healthy controls (n = 39; 53.8% female). Neuroimaging data were acquired via single-band protocols and analyzed in line with methods provided by the Human Connectome Project. We computed functional relationships between individual-specific anatomically defined thalamic and hippocampal seeds and all gray matter voxels in the brain. Whole-brain Type I error protection was achieved through nonparametric permutation-based methods. The 22q11DS patients displayed dissociable disruptions in thalamic and hippocampal functional connectivity relative to control subjects. Thalamocortical coupling was increased in somatomotor regions and reduced across associative networks. The opposite effect was observed for the hippocampus in regards to somatomotor and associative network connectivity. The thalamic and hippocampal dysconnectivity observed in 22q11DS suggests that high genetic risk for psychiatric illness is linked with disruptions in large-scale corticosubcortical networks underlying higher-order cognitive functions. These effects highlight the translational importance of large-effect copy number variants for informing mechanisms underlying neural disruptions observed in idiopathic developmental neuropsychiatric disorders.SIGNIFICANCE STATEMENT Investigation of neuroimaging biomarkers in highly penetrant genetic syndromes represents a more biologically tractable approach to identify neural circuit disruptions underlying developmental neuropsychiatric conditions. The 22q11.2 deletion syndrome confers particularly high risk for psychotic disorders and is thus an important translational model in which to investigate systems-level mechanisms implicated in idiopathic illness. Here, we show resting-state fMRI evidence of large-scale sensory and executive network disruptions in youth with 22q11DS. In particular, this study provides the first evidence that these networks are disrupted in a dissociable fashion with regard to the functional connectivity of the thalamus and hippocampus, suggesting circuit-level dysfunction.

Generative modeling of brain maps with spatial autocorrelation.

Studies of large-scale brain organization have revealed interesting relationships between spatial gradients in brain maps across multiple modalities. Evaluating the significance of these findings requires establishing statistical expectations under a null hypothesis of interest. Through generative modeling of synthetic data that instantiate a specific null hypothesis, quantitative benchmarks can be derived for arbitrarily complex statistical measures. Here, we present a generative null model, provided as an open-access software platform, that generates surrogate maps with spatial autocorrelation (SA) matched to SA of a target brain map. SA is a prominent and ubiquitous property of brain maps that violates assumptions of independence in conventional statistical tests. Our method can simulate surrogate brain maps, constrained by empirical data, that preserve the SA of cortical, subcortical, parcellated, and dense brain maps. We characterize how SA impacts p-values in pairwise brain map comparisons. Furthermore, we demonstrate how SA-preserving surrogate maps can be used in gene set enrichment analyses to test hypotheses of interest related to brain map topography. Our findings demonstrate the utility of SA-preserving surrogate maps for hypothesis testing in complex statistical analyses, and underscore the need to disambiguate meaningful relationships from chance associations in studies of large-scale brain organization.

The Association of Impulsivity and Family History of Alcohol Use Disorder on Alcohol Use and Consequences.

BACKGROUND: Extensive research indicates that having a positive family history of alcohol use disorder (FHP) and impulsivity are 2 risk factors for problem drinking. To our knowledge, no study has investigated which facets of impulsivity interact with family history to increase risk for problem drinking. The goal of this study was to: (i) examine whether FHP individuals with higher levels of impulsivity are more likely to engage in problematic drinking, and (ii) identify which facets of impulsivity interact with FHP to increase risk for problems. METHODS: The data consisted of a combined sample of 757 participants (50% female, 73% White, mean age = 32.85, SD = 11.31) drawn from the Transdisciplinary Tobacco Use Research Center and the Center for the Translational Neuroscience of Alcohol. Analyses of covariance and cumulative logistic regression models investigated the association of family history and impulsivity-related traits with drinking quantity, frequency, and alcohol-related problems. Models were adjusted for age, sex, race, ethnic group, education level, and data source. RESULTS: Significant interactions between impulsivity and family history were found for measures of alcohol-related problems. Specifically, there was a stronger positive association of Barratt Impulsiveness Scale (BIS) poor self-regulation with interpersonal, F(1, 504) = 6.27, p = 0.01, and impulse control alcohol-related problems, F(1, 504) = 6.00, p = 0.01, among FHP compared to FHN individuals. Main effects of family history and impulsivity on alcohol quantity and frequency of use and problems were also found. CONCLUSIONS: These findings suggest that having both a family history of AUD and high BIS poor self-regulation is more strongly associated with alcohol-related consequences in the interpersonal and impulse control domains. Given the heterogeneity of impulsivity, these findings highlight the need for additional research to examine which facets of impulsivity are associated with which alcohol outcomes to narrow phenotypic risk for alcohol misuse.

Structural Covariance Reveals Alterations in Control and Salience Network Integrity in Chronic Schizophrenia.

Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ.