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Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

"Sense of agency" (SoA), the feeling of control for events caused by one's own actions, is deceived by visuomotor incongruence. Sensorimotor networks are implicated in SoA, however little evidence exists on brain functionality during agency processing. Concurrently, it has been suggested that the brain's intrinsic resting-state (rs) activity has a preliminary influence on processing of agency cues. Here, we investigated the relation between performance in an agency attribution task and functional interactions among brain regions as derived by network analysis of rs functional magnetic resonance imaging. The action-effect delay was adaptively increased (range 90-1,620 ms) and behavioral measures correlated to indices of cognitive processes and appraised self-concepts. They were then regressed on local metrics of rs brain functional connectivity as to isolate the core areas enabling self-agency. Across subjects, the time window for self-agency was 90-625 ms, while the action-effect integration was impacted by self-evaluated personality traits. Neurally, the brain intrinsic organization sustaining consistency in self-agency attribution was characterized by high connectiveness in the secondary visual cortex, and regional segregation in the primary somatosensory area. Decreased connectiveness in the secondary visual area, regional segregation in the superior parietal lobule, and information control within a primary visual cortex-frontal eye fields network sustained self-agency over long-delayed effects. We thus demonstrate that self-agency is grounded on the intrinsic mode of brain function designed to organize information for visuomotor integration. Our observation is relevant for current models of psychopathology in clinical conditions in which both rs activity and sense of agency are altered., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

White matter abnormalities have been shown in the large deep fibers of Alzheimer's disease patients. However, the late myelinating superficial white matter comprised of intracortical myelin and short-range association fibers has not received much attention. To investigate this area, we extracted a surface corresponding to the superficial white matter beneath the cortex and then applied a cortical pattern-matching approach which allowed us to register and subsequently sample diffusivity along thousands of points at the interface between the gray matter and white matter in 44 patients with Alzheimer's disease (Age: 71.02 ± 5.84, 16M/28F) and 47 healthy controls (Age 69.23 ± 4.45, 19M/28F). In patients we found an overall increase in the axial and radial diffusivity across most of the superficial white matter (P < 0.001) with increases in diffusivity of more than 20% in the bilateral parahippocampal regions and the temporal and frontal lobes. Furthermore, diffusivity correlated with the cognitive deficits measured by the Mini-Mental State Examination scores (P < 0.001). The superficial white matter has a unique microstructure and is critical for the integration of multimodal information during brain maturation and aging. Here we show that there are major abnormalities in patients and the deterioration of these fibers relates to clinical symptoms in Alzheimer's disease., (© 2016 Wiley Periodicals, Inc.)

We investigated the role of the dopamine system [i.e., subcortical-medial prefrontal cortex (mPFC) network] in dreaming, by studying patients with Parkinson's Disease (PD) as a model of altered dopaminergic transmission. Subcortical volumes and cortical thickness were extracted by 3T-MR images of 27 PD patients and 27 age-matched controls, who were asked to fill out a dream diary upon morning awakening for one week. PD patients do not substantially differ from healthy controls with respect to the sleep, dream, and neuroanatomical measures. Multivariate correlational analyses in PD patients show that dopamine agonist dosage is associated to qualitatively impoverished dreams, as expressed by lower bizarreness and lower emotional load values. Visual vividness (VV) of their dream reports positively correlates with volumes of both the amygdalae and with thickness of the left mPFC. Emotional load also positively correlates with hippocampal volume. Beside the replication of our previous finding on the role of subcortical nuclei in dreaming experience of healthy subjects, this represents the first evidence of a specific role of the amygdala-mPFC dopaminergic network system in dream recall. The association in PD patients between higher dopamine agonist dosages and impoverished dream reports, however, and the significant correlations between VV and mesolimbic regions, however, provide an empirical support to the hypothesis that a dopamine network plays a key role in dream generation. The causal relation is however precluded by the intrinsic limitation of assuming the dopamine agonist dosage as a measure of the hypodopaminergic state in PD. Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

Lack of insight into illness is a multidimensional phenomenon that has relevant implications on clinical course and therapy compliance. Here, we focused on metacognitive insight in schizophrenia, that is, the ability to monitor one's changes in state of mind and sensations, with the aim of investigating its neuroanatomical, psychopathological, and neuropsychological correlates. Fifty-seven consecutive patients with Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnosis of schizophrenia were administered the Insight Scale, and comprehensive psychopathological and neuropsychological batteries. They underwent a high-resolution T1-weighted magnetic resonance imaging investigation. Gray matter (GM) and white matter (WM) volumes were analyzed on a voxel-by-voxel basis using Statistical Parametric Mapping 8. Reduced metacognitive insight was related to reduced GM volumes in the left ventrolateral prefrontal cortex, right dorsolateral prefrontal cortex and insula, and bilateral premotor area and putamen. Further, it was related to reduced WM volumes of the right superior longitudinal fasciculum, left corona radiata, left forceps minor, and bilateral cingulum. Increased metacognitive insight was related to increased depression severity and attentional control impairment, while the latter was related to increased GM volumes in brain areas linked to metacognitive insight. Results of this study suggest that prefrontal GM and WM bundles, all implied in cognitive control and self-reflection, may be the neuroanatomical correlates of metacognitive insight in schizophrenia. Further, higher metacognitive insight is hypothesized to be a risk factor for depression which may subsequently impair attention. This line of research may provide the basis for the development of cognitive interventions aimed at improving self-monitoring and compliance to treatment., (Copyright © 2014 Wiley Periodicals, Inc.)

Personality traits are multidimensional traits comprising cognitive, emotional, and behavioral characteristics, and a wide array of cerebral structures mediate individual variability. Differences in personality traits covary with brain morphometry in specific brain regions, and neuroimaging studies showed structural or functional abnormalities of cerebellum in subjects with personality disorders, suggesting a cerebellar role in affective processing and an effect on personality characteristics. To test the hypothesis that cerebellar [white matter (WM) and cortex] volumes are correlated with scores obtained in the four temperamental scales of the Temperament and Character Inventory (TCI) by Cloninger, a total of 125 healthy participants aged 18-67 years of both genders (males = 52) completed the TCI and underwent magnetic resonance imaging. The scores obtained in each temperamental scale were associated with the volumes of cerebellar WM and cortex of right and left hemispheres separately by using linear regression analyses. In line with our hypothesis, novelty seeking (NS) scores were positively associated with WM and cortex cerebellar volumes. Harm avoidance (HA) scores were negatively associated with WM and cortex cerebellar volumes. The range of individual differences in NS and HA scores reflects the range of variances of cerebellar volumes. The present data indicating a cerebellar substrate for some personality traits extend the relationship between personality and brain areas to a structure up to now thought to be involved mainly in motor and cognitive functions, much less in emotional processes and even less in personality individual differences., (Copyright © 2012 Wiley Periodicals, Inc.)

Although apathy has been extensively studied in relation to neuropsychiatric disorders, it is still unclear whether, in healthy people, it should be considered as a physiological phenomenon or whether it is a risk factor for progression to clinical disturbances. Here, we investigated subclinical apathy phenomenology and its brain microstructural correlates in healthy individuals. We submitted 72 participants to a comprehensive clinical assessment, a high-resolution structural MRI and a diffusion tensor imaging scan protocol. Data of individual microstructural (mean diffusivity and fractional anisotropy) variations were processed across genders in relation to the Apathy Rating Scale score. In females, subclinical apathy phenomenology was associated with microstructural variation of the bilateral thalami, the anterior thalamic radiation, the forceps major, and the corona radiate. These are white matter areas mostly connecting the thalami to the frontal and occipital cortices, regions that are known to be implicated in the expression of apathy in clinical samples. No significant relationship with brain microstructure was found in males who showed a positive correlation between subclinical apathy and somatic phenomenology of depression. In conclusion, our results show that in healthy individuals subclinical apathy phenomenology is associated with different mechanisms across genders, and raise the issue about whether brain microstructural changes associated with subclinical apathy in healthy females could be a precocious marker useful in the prediction of progression to more severe apathetic conditions., (Copyright © 2012 Wiley Periodicals, Inc.)

Education has been extensively considered an influential factor in the modulation of interindividual differences in cognitive performance and cerebral structure. Consequently, education has been linked to the concept of reserve, which refers to an unspecified aspect of brain structure or function that enables people with more education to cope better with brain pathology or age-related changes. Nevertheless, the education-related neural mechanisms involved in reserve are still not completely understood. In this study, 150 healthy subjects were submitted to a comprehensive sociodemographic, clinical and cognitive assessment, and a high-resolution structural MRI and diffusion tensor imaging scan protocol. Data of micro- (mean diffusivity, MD) and macro- (volume) structural changes of six bilateral deep gray matter structures (thalamus, caudate nucleus, putamen, hippocampus, amygdala, and globus pallidus) were analyzed with reference to years of formal education. Results show that decreased MD in both left and right hippocampi was the only structural parameter that, along with decreasing age, significantly correlated with higher education. The present findings suggest that the hippocampal formation might be one site where education-mediated microstructural changes occur, possibly compensating for cognitive decline., (Copyright © 2010 Wiley-Liss, Inc.)