On the nature of monozygotic twin concordance and discordance for autistic trait severity: A quantitative analysis

The characterizing features of autism spectrum disorder (ASD) are continuously distributed in nature; however, prior twin studies have not systematically incorporated this knowledge into estimations of concordance and discordance. We conducted a quantitative analysis of twin-twin similarity for autistic trait severity in three existing data sets involving 366 pairs of uniformly-phenotyped monozygotic (MZ) twins with and without ASD. Probandwise concordance for ASD was 96%; however, MZ trait correlations differed markedly for pairs with ASD trait burden below versus above the threshold for clinical diagnosis, with

Brain connectivity and socioeconomic status at birth and externalizing symptoms at age 2 years

Low childhood socioeconomic status (SES) predisposes individuals to altered trajectories of brain development and increased rates of mental illness. Brain connectivity at birth is associated with psychiatric outcomes. We sought to investigate whether SES at birth is associated with neonatal brain connectivity and if these differences account for socioeconomic disparities in infant symptoms at age 2 years that are predictive of psychopathology. Resting state functional MRI was performed on 75 full-term and 37 term-equivalent preterm newborns (n = 112). SES was characterized by insurance type, the Area Deprivation Index, and a composite score. Seed-based voxelwise linear regression related SES to whole-brain functional connectivity of five brain regions representing functional networks implicated in psychiatric illnesses and affected by socioeconomic disadvantage: striatum, medial prefrontal cortex (mPFC), ventrolateral prefrontal cortex (vlPFC), and dorsal anterior cingulate cortex. Lower SES was associated with differences in striatum and vlPFC connectivity. Striatum connectivity with frontopolar and medial PFC mediated the relationship between SES and behavioral inhibition at age 2 measured by the Infant-Toddler Social Emotional Assessment (n = 46). Striatum-frontopolar connectivity mediated the relationship between SES and externalizing symptoms. These results, convergent across three SES metrics, suggest that neurodevelopmental trajectories linking SES and mental illness may begin as early as birth

Parallel hippocampal-parietal circuits for self- and goal-oriented processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing

Measuring Granger Causality between Cortical Regions from Voxelwise fMRI BOLD Signals with LASSO

Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis

A somato-cognitive action network alternates with effector regions in motor cortex

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representation

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the enigma-anxiety working group

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology

Asymmetry of anticipatory activity in visual cortex predicts the locus of attention and perception

Humans can use advance information to direct spatial attention before stimulus presentation and respond more accurately to stimuli at the attended location compared with unattended locations. Likewise, spatially directed attention is associated with anticipatory activity in the portion of visual cortex representing the attended location. It is unknown, however, whether and how anticipatory signals predict the locus of spatial attention and perception. Here, we show that prestimulus, preparatory activity is highly correlated across regions representing attended and unattended locations. Comparing activity representing attended versus unattended locations, rather than measuring activity for only one location, dramatically improves the accuracy with which preparatory signals predict the locus of attention, largely by removing this positive correlation common across locations. In V3A, moreover, only the difference in activity between attended and unattended locations predicts whether upcoming visual stimuli will be accurately perceived. These results suggest that the locus of attention is coded in visual cortex by an asymmetry of anticipatory activity between attended and unattended locations and that this asymmetry predicts the accuracy of perception. This coding strategy may bias activity in downstream brain regions to represent the stimulus at the attended location