Altered white matter microstructure in 22q11.2 deletion syndrome: a multisite diffusion tensor imaging study.

22q11.2 deletion syndrome (22q11DS)-a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22-is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6-52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen's d's ranging from -0.9 to -1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers.

Wireless versus routine physiologic monitoring after cesarean delivery to reduce maternal morbidity and mortality in a resource-limited setting: protocol of type 2 hybrid effectiveness-implementation study.

BACKGROUND: Women in sub-Saharan Africa have the highest rates of morbidity and mortality during childbirth globally. Despite increases in facility-based childbirth, gaps in quality of care at facilities have limited reductions in maternal deaths. Infrequent physiologic monitoring of women around childbirth is a major gap in care that leads to delays in life-saving interventions for women experiencing complications. METHODS: We will conduct a type-2 hybrid effectiveness-implementation study over 12 months to evaluate using a wireless physiologic monitoring system to detect and alert clinicians of abnormal vital signs in women for 24 h after undergoing emergency cesarean delivery at a tertiary care facility in Uganda. We will provide physiologic data (heart rate, respiratory rate, temperature and blood pressure) to clinicians via a smartphone-based application with alert notifications if monitored women develop predefined abnormalities in monitored physiologic signs. We will alternate two-week intervention and control time periods where women and clinicians use the wireless monitoring system during intervention periods and current standard of care (i.e., manual vital sign measurement when clinically indicated) during control periods. Our primary outcome for effectiveness is a composite of severe maternal outcomes per World Health Organization criteria (e.g. death, cardiac arrest, jaundice, shock, prolonged unconsciousness, paralysis, hysterectomy). Secondary outcomes include maternal mortality rate, and case fatality rates for postpartum hemorrhage, hypertensive disorders, and sepsis. We will use the RE-AIM implementation framework to measure implementation metrics of the wireless physiologic system including Reach (proportion of eligible women monitored, length of time women monitored), Efficacy (proportion of women with monitoring according to Uganda Ministry of Health guidelines, number of appropriate alerts sent), Adoption (proportion of clinicians utilizing physiologic data per shift, clinical actions in response to alerts), Implementation (fidelity to monitoring protocol), Maintenance (sustainability of implementation over time). We will also perform in-depth qualitative interviews with up to 30 women and 30 clinicians participating in the study. DISCUSSION: This is the first hybrid-effectiveness study of wireless physiologic monitoring in an obstetric population. This study offers insights into use of wireless monitoring systems in low resource-settings, as well as normal and abnormal physiologic parameters among women delivering by cesarean. TRIAL REGISTRATION: ClinicalTrials.gov , NCT04060667 . Registered on 08/01/2019.

Neuroanatomical deficits shared by youth with autism spectrum disorders and psychotic disorders.

Autism spectrum disorders (ASD) and early-onset psychosis (EOP) are neurodevelopmental disorders that share genetic, clinical and cognitive facets; it is unclear if these disorders also share spatially overlapping cortical thickness (CT) and surface area (SA) abnormalities. MRI scans of 30 ASD, 29 patients with early-onset first-episode psychosis (EO-FEP) and 26 typically developing controls (TD) (age range 10-18 years) were analyzed by the FreeSurfer suite to calculate vertex-wise estimates of CT, SA, and cortical volume. Two publicly available datasets of ASD and EOP (age range 7-18 years and 5-17 years, respectively) were used for replication analysis. ASD and EO-FEP had spatially overlapping areas of cortical thinning and reduced SA in the bilateral insula (all p's < .00002); 37% of all left insular vertices presenting with significant cortical thinning and 20% (left insula) and 61% (right insula) of insular vertices displaying decreased SA overlapped across both disorders. In both disorders, SA deficits contributed more to cortical volume decreases than reductions in CT did. This finding, as well as the novel finding of an absence of spatial overlap (for ASD) or marginal overlap (for EOP) of deficits in CT and SA, was replicated in the two nonoverlapping independent samples. The insula appears to be a region with transdiagnostic vulnerability for deficits in CT and SA. The finding of nonexistent or small spatial overlap between CT and SA deficits in young people with ASD and psychosis may point to the involvement of common aberrant early neurodevelopmental mechanisms in their pathophysiology.

Local functional connectivity suggests functional immaturity in children with attention-deficit/hyperactivity disorder.

Previous studies have associated Attention-Deficit/Hyperactivity Disorder (ADHD) with a maturational lag of brain functional networks. Functional connectivity of the human brain changes from primarily local to more distant connectivity patterns during typical development. Under the maturational lag hypothesis, we expect children with ADHD to exhibit increased local connectivity and decreased distant connectivity compared with neurotypically developing (ND) children. We applied a graph-theory method to compute local and distant connectivity levels and cross-sectionally compared them in a sample of 120 children with ADHD and 120 age-matched ND children (age range = 7-17 years). In addition, we measured if potential group differences in local and distant connectivity were stable across the age range considered. Finally, we assessed the clinical relevance of observed group differences by correlating the connectivity levels and ADHD symptoms severity separately for each group. Children with ADHD exhibited more local connectivity than age-matched ND children in multiple brain regions, mainly overlapping with default mode, fronto-parietal and ventral attentional functional networks (p < .05- threshold free-cluster enhancement-family-wise error). We detected an atypical developmental pattern of local connectivity in somatomotor regions, that is, decreases with age in ND children, and increases with age in children with ADHD. Furthermore, local connectivity within somatomotor areas correlated positively with clinical severity of ADHD symptoms, both in ADHD and ND children. Results suggest an immature functional state of multiple brain networks in children with ADHD. Whereas the ADHD diagnosis is associated with the integrity of the system comprising the fronto-parietal, default mode and ventral attentional networks, the severity of clinical symptoms is related to atypical functional connectivity within somatomotor areas. Additionally, our findings are in line with the view of ADHD as a disorder of deviated maturational trajectories, mainly affecting somatomotor areas, rather than delays that normalize with age.

Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T1-weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc.

Enhanced structural connectivity within a brain sub-network supporting working memory and engagement processes after cognitive training.

The structural connectome provides relevant information about experience and training-related changes in the brain. Here, we used network-based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty-six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images. We acquired and analyzed diffusion-weighted images to reconstruct the anatomical connectome and we computed standardized changes in connectivity as well as group differences across time using NBS. We also compared group differences relying on a variety of graph-theory indices (clustering, characteristic path length, global and local efficiency and strength) for the whole network as well as for the sub-network derived from NBS analyses. Finally, we calculated correlations between these graph indices and training performance as well as the behavioral changes in cognitive function. Our results revealed enhanced connectivity for the training group within one specific network comprised of nodes/regions supporting cognitive processes required by the training (working memory, interference resolution, inhibition, and task engagement). Significant group differences were also observed for strength and global efficiency indices in the sub-network detected by NBS. Therefore, the connectome approach is a valuable method for tracking the effects of cognitive training interventions across specific sub-networks. Moreover, this approach allowsfor the computation of graph theoretical network metricstoquantifythetopological architecture of the brain networkdetected. The observed structural brain changes support the behavioral results reported earlier (see Colom, Román, et al., 2013).

Atypical age-dependency of executive function and white matter microstructure in children and adolescents with autism spectrum disorders.

Executive function (EF) performance is associated with measurements of white matter microstructure (WMS) in typical individuals. Impaired EF is a hallmark symptom of autism spectrum disorders (ASD) but it is unclear how impaired EF relates to variability in WMS. Twenty-one male youth (8-18 years) with ASD and without intellectual disability and twenty-one typical male participants (TP) matched for age, intelligence quotient, handedness, race and parental socioeconomic status were recruited. Five EF domains were assessed and several DTI-based measurements of WMS [fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD)] were estimated for eighteen white matter tracts. The ASD group had lower scores for attention (F = 8.37, p = 0.006) and response inhibition (F = 13.09, p = 0.001). Age-dependent changes of EF performance and WMS measurements were present in TP but attenuated in the ASD group. The strongest diagnosis-by-age effect was found for forceps minor, left anterior thalamic radiation and left cingulum angular bundle (all p's ≤ 0.002). In these tracts subjects with ASD tended to have equal or increased FA and/or reduced MD and/or RD at younger ages while controls had increased FA and/or reduced MD and/or RD thereafter. Only for TP individuals, increased FA in the left anterior thalamic radiation was associated with better response inhibition, while reduced RD in forceps minor and left cingulum angular bundle was related to better problem solving and working memory performance respectively. These findings provide novel insight into the age-dependency of EF performance and WMS in ASD, which can be instructive to cognitive training programs.

Sex differences in neocortical structure and cognitive performance: A surface-based morphometry study.

On average, men show larger brain volumes than women. Regional differences have been also observed, although most of the available studies apply voxel-based morphometry (VBM). Reports applying surface-based morphometry (SBM) have been focused mainly on cortical thickness (CT). Here we apply SBM for obtaining global and regional indices of CT, cortical surface area (CSA), and cortical gray matter volume (CGMV) from samples of men (N=40) and women (N=40) matched for their performance on four cognitive factors varying in their complexity: processing speed, attention control, working memory capacity, and fluid intelligence. These were the main findings: 1) CT and CSA produced very weak correlations in both sexes, 2) men showed larger values in CT, CSA, and CGMV, and 3) cognitive performance was unrelated to brain structural variation within sexes. Therefore, we found substantial group differences in brain structure, but there was no relationship with cognitive performance both between and within-sexes.

Sensation-to-cognition cortical streams in attention-deficit/hyperactivity disorder.

We sought to determine whether functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits are atypical in attention-deficit/hyperactivity disorder (ADHD). We applied a graph-theory method to the resting-state functional magnetic resonance imaging data of 120 children with ADHD and 120 age-matched typically developing children (TDC). Starting in unimodal primary cortex-visual, auditory, and somatosensory-we used stepwise functional connectivity to calculate functional connectivity paths at discrete numbers of relay stations (or link-step distances). First, we characterized the functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits in TDC and found that systems do not reach the level of integration achieved by adults. Second, we searched for stepwise functional connectivity differences between children with ADHD and TDC. We found that, at the initial steps of sensory functional connectivity streams, patients display significant enhancements of connectivity degree within neighboring areas of primary cortex, while connectivity to attention-regulatory areas is reduced. Third, at subsequent link-step distances from primary sensory cortex, children with ADHD show decreased connectivity to executive processing areas and increased degree of connections to default mode regions. Fourth, in examining medication histories in children with ADHD, we found that children medicated with psychostimulants present functional connectivity streams with higher degree of connectivity to regions subserving attentional and executive processes compared to medication-naïve children. We conclude that predominance of local sensory processing and lesser influx of information to attentional and executive regions may reduce the ability to organize and control the balance between external and internal sources of information in ADHD.

Reproducibility of brain-cognition relationships using three cortical surface-based protocols: An exhaustive analysis based on cortical thickness.

People differ in their cognitive functioning. This variability has been exhaustively examined at the behavioral, neural and genetic level to uncover the mechanisms by which some individuals are more cognitively efficient than others. Studies investigating the neural underpinnings of interindividual differences in cognition aim to establish a reliable nexus between functional/structural properties of a given brain network and higher order cognitive performance. However, these studies have produced inconsistent results, which might be partly attributed to methodological variations. In the current study, 82 healthy young participants underwent MRI scanning and completed a comprehensive cognitive battery including measurements of fluid, crystallized, and spatial intelligence, along with working memory capacity/executive updating, controlled attention, and processing speed. The cognitive scores were obtained by confirmatory factor analyses. T1 -weighted images were processed using three different surface-based morphometry (SBM) pipelines, varying in their degree of user intervention, for obtaining measures of cortical thickness (CT) across the brain surface. Distribution and variability of CT and CT-cognition relationships were systematically compared across pipelines and between two cognitively/demographically matched samples to overcome potential sources of variability affecting the reproducibility of findings. We demonstrated that estimation of CT was not consistent across methods. In addition, among SBM methods, there was considerable variation in the spatial pattern of CT-cognition relationships. Finally, within each SBM method, results did not replicate in matched subsamples.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered.

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical connections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 different brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very-large-scale integration circuits analyses, shows that functional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrangements for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal-ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organizations that can only be identified when the physical locations of the nodes are included in the analysis.

Subcortical regional morphology correlates with fluid and spatial intelligence.

Neuroimaging studies have revealed associations between intelligence and brain morphology. However, researchers have focused primarily on the anatomical features of the cerebral cortex, whereas subcortical structures, such as the basal ganglia (BG), have often been neglected despite extensive functional evidence on their relation with higher-order cognition. Here we performed shape analyses to understand how individual differences in BG local morphology account for variability in cognitive performance. Structural MRI was acquired in 104 young adults (45 men, 59 women, mean age = 19.83, SD = 1.64), and the outer surface of striatal structures (caudate, nucleus accumbens, and putamen), globus pallidus, and thalamus was estimated for each subject and hemisphere. Further, nine cognitive tests were used to measure fluid (Gf), crystallized (Gc), and spatial intelligence (Gv). Latent scores for these factors were computed by means of confirmatory factor analysis and regressed vertex-wise against subcortical shape (local displacements of vertex position), controlling for age, sex, and adjusted for brain size. Significant results (FDR < 5%) were found for Gf and Gv, but not Gc, for the right striatal structures and thalamus. The main results show a relative enlargement of the rostral putamen, which is functionally connected to the right dorsolateral prefrontal cortex and other intelligence-related prefrontal areas.

Reversed hierarchy in the brain for general and specific cognitive abilities: a morphometric analysis.

Intelligence is composed of a set of cognitive abilities hierarchically organized. General and specific abilities capture distinguishable, but related, facets of the intelligence construct. Here, we analyze gray matter with three morphometric indices (volume, cortical surface area, and cortical thickness) at three levels of the intelligence hierarchy (tests, first-order factors, and a higher-order general factor, g). A group of one hundred and four healthy young adults completed a cognitive battery and underwent high-resolution structural MRI. Latent scores were computed for the intelligence factors and tests were also analyzed. The key finding reveals substantial variability in gray matter correlates at the test level, which is substantially reduced for the first-order and the higher-order factors. This supports a reversed hierarchy in the brain with respect to cognitive abilities at different psychometric levels: the greater the generality, the smaller the number of relevant gray matter clusters accounting for individual differences in intelligent performance.

Neuroanatomic overlap between intelligence and cognitive factors: morphometry methods provide support for the key role of the frontal lobes.

Evidence from neuroimaging studies suggests that intelligence differences may be supported by a parieto-frontal network. Research shows that this network is also relevant for cognitive functions such as working memory and attention. However, previous studies have not explicitly analyzed the commonality of brain areas between a broad array of intelligence factors and cognitive functions tested in the same sample. Here fluid, crystallized, and spatial intelligence, along with working memory, executive updating, attention, and processing speed were each measured by three diverse tests or tasks. These twenty-one measures were completed by a group of one hundred and four healthy young adults. Three cortical measures (cortical gray matter volume, cortical surface area, and cortical thickness) were regressed against psychological latent scores obtained from a confirmatory factor analysis for removing test and task specific variance. For cortical gray matter volume and cortical surface area, the main overlapping clusters were observed in the middle frontal gyrus and involved fluid intelligence and working memory. Crystallized intelligence showed an overlapping cluster with fluid intelligence and working memory in the middle frontal gyrus. The inferior frontal gyrus showed overlap for crystallized intelligence, spatial intelligence, attention, and processing speed. The fusiform gyrus in temporal cortex showed overlap for spatial intelligence and attention. Parietal and occipital areas did not show any overlap across intelligence and cognitive factors. Taken together, these findings underscore that structural features of gray matter in the frontal lobes support those aspects of intelligence related to basic cognitive processes.

Changes in resting-state functionally connected parietofrontal networks after videogame practice.

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Hippocampal structure and human cognition: key role of spatial processing and evidence supporting the efficiency hypothesis in females.

Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05) significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences.

Cortical thinning over two years after first-episode psychosis depends on age of onset.

First-episode psychosis (FEP) patients show structural brain abnormalities at the first episode. Whether the cortical changes that follow a FEP are progressive and whether age at onset modulates these changes remains unclear. This is a multicenter MRI study in a deeply phenotyped sample of 74 FEP patients with a wide age range at onset (15-35 years) and 64 neurotypical healthy controls (HC). All participants underwent two MRI scans with a 2-year follow-up interval. We computed the longitudinal percentage of change (PC) for cortical thickness (CT), surface area (CSA) and volume (CV) for frontal, temporal, parietal and occipital lobes. We used general linear models to assess group differences in PC as a function of age at FEP. We conducted post-hoc analyses for metrics where PC differed as a function of age at onset. We found a significant age-by-diagnosis interaction effect for PC of temporal lobe CT (d = 0.54; p = 002). In a post-hoc-analysis, adolescent-onset (≤19 y) FEP showed more severe longitudinal cortical thinning in the temporal lobe than adolescent HC. We did not find this difference in adult-onset FEP compared to adult HC. Our study suggests that, in individuals with psychosis, CT changes that follow the FEP are dependent on the age at first episode, with those with an earlier onset showing more pronounced cortical thinning in the temporal lobe.

Prefrontal abnormalities, executive dysfunction and symptoms severity are modulated by COMT Val158Met polymorphism in first episode psychosis.

INTRODUCTION: Core dysfunctions proposed for psychotic disorders include prefrontal cortex (PFC) dopaminergic hypoactivity, executive function (EF) deficits and reduced gray matter in the PFC. The Val variant of COMT Val158Met polymorphism is associated with reduced dopaminergic signaling in the PFC. However, it is unclear how COMT Val158Met modulates PFC gray matter reduction, EF deficits and symptom severity at the time of the first psychotic episode. METHODS: The effect of COMT on both EF performance and prefrontal volume (PFC-VOL) was tested in 158 first episode psychosis (FEP) patients and 141 healthy controls (HC) matched for age (range 9-35 years), sex, ethnicity, handedness and COMT Val158Met distribution. EF and PFC-VOL were compared between FEP and HC groups within each polymorphism status (Met/Met versus Val carriers) to assess whether COMT influenced diagnostic differences. Next, correlations between PFC-VOL and EF performance were computed, as well as between both variables and other clinical characteristics of interest (PANSS scores, PAS infancy and premorbid IQ) in the FEP sample. RESULTS: COMT influenced the diagnostic differences mainly in PFC-VOL, but also in EF performance. FEP-Val carriers showed lower EF scores and reduced PFC-VOL compared to the HC group but also poorer EF performance than FEP Met/Met. Poorer EF performance was associated with smaller PFC-VOL, and both were related to increased severity of negative symptoms, poorer premorbid adjustment, and lower estimated premorbid IQ in FEP patients. CONCLUSIONS: Our findings suggest that COMT Val158Met polymorphism might contribute to PFC-VOL reductions, executive dysfunctions and symptom severity in FEP patients.

Brain resilience across the general cognitive ability distribution: Evidence from structural connectivity.

Resting state functional connectivity research has shown that general cognitive ability (GCA) is associated with brain resilience to targeted and random attacks (TAs and RAs). However, it remains to be seen if the finding generalizes to structural connectivity. Furthermore, individuals showing performance levels at the very high area of the GCA distribution have not yet been analyzed in this regard. Here we study the relation between TAs and RAs to structural brain networks and GCA. Structural and diffusion-weighted MRI brain images were collected from 189 participants: 60 high cognitive ability (HCA) and 129 average cognitive ability (ACA) individuals. All participants completed a standardized fluid reasoning ability test and the results revealed an average HCA-ACA difference equivalent to 33 IQ points. Automated parcellation of cortical and subcortical nodes was combined with tractography to achieve an 82 × 82 connectivity matrix for each subject. Graph metrics were derived from the structural connectivity matrices. A simulation approach was used to evaluate the effects of recursively removing nodes according to their network centrality (TAs) versus eliminating nodes at random (RAs). HCA individuals showed greater network integrity at baseline and prior to network collapse than ACA individuals. These effects were more evident for TAs than RAs. The networks of HCA individuals were less degraded by the removal of nodes corresponding to more complex information processing stages of the PFIT network, and from removing nodes with larger empirically observed centrality values. Analyzed network features suggest quantitative instead of qualitative differences at different levels of the cognitive ability distribution.