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Palmer, C. E.

Publications and source records attributed to Palmer, C. E..

14 recordsLinked to original sources

Fast, Efficient Multimodal Image Normalisation Tool (FEMINisT) for the Adolescent Brain and Cognitive Development study: the FEMINisT ABCD Atlas

The Adolescent Brain and Cognitive Development (ABCD) study aims to measure the trajectories of brain, cognitive, and emotional development. Cognitive and behavioural development during late childhood and adolescence have been associated with a myriad of microstructural and morphological alterations across the brain, as measured by magnetic resonance imaging (MRI). These associations may be strongly localised or spatially diffuse, therefore, it would be advantageous to analyse multimodal MRI data in concert, and across the whole brain. The ABCD study presents the unique challenge of integrating multimodal data from tens of thousands of scans at multiple timepoints, within a reasonable computation time. To address the need for a multimodal registration and atlas for the ABCD dataset, we present the synthesis of an ABCD atlas using the Multimodal Image Normalisation Tool (MINT). The MINT ABCD atlas was generated from baseline and two-year follow up imaging data using an iterative approach to synthesise a cohort-specific atlas from linear and nonlinear deformations of eleven channels of diffusion and structural MRI data. We evaluated the performance of MINT against two widely used methods and show that MINT achieves comparable alignment to current state-of-the-art multimodal registration, at a fraction of the computation time. To validate the use of the ABCD MINT atlas in whole brain, voxelwise analysis, we replicate and expand on previously published region-of-interest analysis between diffusion MRI-derived measures and body mass index (BMI). We also report novel association between BMI and brain morphology derived from the registration deformations. We present the ABCD MINT atlas as a publicly available resource to facilitate whole brain voxelwise analyses for the ABCD study.

neuroscience↗

FEMA: Fast and efficient mixed-effects algorithm for population-scale whole brain imaging data

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME, however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

neuroscience↗

A Comprehensive Overview of the Physical Health of the Adolescent Brain Cognitive Development Study (ABCD) Cohort at Baseline

Physical health in childhood is crucial for neurobiological as well as overall development, and can shape long-term outcomes into adulthood. The landmark, longitudinal Adolescent Brain Cognitive Development StudySM (ABCD study(R)), was designed to investigate brain development and health in almost 12,000 youth who were recruited when they were 9-10 years old and will be followed through adolescence and early adulthood. The overall goal of this paper is to provide descriptive analyses of physical health measures in the ABCD study at baseline, including but not limited to sleep, physical activity and sports involvement, and body mass index, and how these measures vary across demographic groups. This paper outlines how the physical health of the ABCD sample corresponds with that of the US population and highlights important avenues for health disparity research. This manuscript will provide important information for ABCD users and help guide analyses investigating physical health as it pertains to adolescent and young adult development.

developmental biology↗

Spatially heterogeneous microstructural development within subcortical regions from 9-13 years

During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-subcortical circuits. Understanding microstructural changes in subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered and restricted compartments. This yields greater specificity than conventional methods of characterizing intracellular diffusion. Using RSI, we modelled voxelwise restricted isotropic, N0, and anisotropic, ND, diffusion across the brain and measured cross-sectional and longitudinal age associations in a large sample (n=8,039) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9-13 years. Older participants had higher N0 and ND across subcortical regions. The largest associations for N0 were within the basal ganglia and for ND within the ventral diencephalon. Importantly, age associations varied with respect to the internal cytoarchitecture within subcortical structures, for example age associations differed across thalamic nuclei. This suggests that developmental effects may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this subcortical microstructural developmental for behavioral outcomes.

neuroscience↗

Microstructural development across white matter from 9-13 years

During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n=8,086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9-14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes.

neuroscience↗

Generalization of Cortical Multivariate Genome-Wide Associations Within and Across Samples

Genome-Wide Association studies have typically been limited to single phenotypes, given that high dimensional phenotypes incur a large multiple comparisons burden: ~1 million tests across the genome times the number of phenotypes. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci when compared to established approaches (min-P). One question that arises is how well these discovered loci replicate in independent data. Here we perform 10 times cross validation within 35,644 individuals from UK Biobank for imaging measures of cortical area, thickness and sulcal depth (>1,000 dimensionality for each). By deploying a replication method that aggregates discovered effects distributed across multiple phenotypes, termed PolyVertex Score (PVS), we demonstrate a higher replication yield and comparable replication rate of discovered loci for MOSTest (# replicated loci: 348-845, replication rate: 94-95%) in independent data when compared with the established min-P approach (# replicated loci: 31-68, replication rate: 65-80%). An out-of-sample replication of discovered loci was conducted with a sample of 8,336 individuals from the Adolescent Brain Cognitive Development(R) (ABCD) study, who are on average 50 years younger than UK Biobank individuals. We observe a higher replication yield and comparable replication rate of MOSTest compared to min-P. This finding underscores the importance of using well-powered multivariate techniques for both discovery and replication of high dimensional phenotypes in Genome-Wide Association studies.

genomics↗

Multivariate genome-wide association study identifies 1735 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we exploit the distributed nature of genetic effects across the brain and apply the Multivariate Omnibus Statistical Test (MOSTest) to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology. This reflects an approximate 10-fold increase compared to the commonly applied univariate GWAS methods. Power analysis indicates that applying MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. Functional follow up including gene-based analyses implicate 10% of all protein-coding genes and point towards pathways involved in neurogenesis and cell differentiation.

genetics↗

Meaningful Effects in the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and childrens health in the United States. A cohort of n= 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

neuroscience↗

Neural divergence and convergence for interoceptive and somatosensory attention and detection

Body awareness is constructed by signals originating from within and outside the body. How do these apparently divergent signals converge? We developed a signal detection task to study the neural convergence and divergence of interoceptive and somatosensory signals. Participants focused on either cardiac or tactile events and reported their presence or absence. Beyond some evidence of divergence, we observed a robust overlap in the pattern of activation evoked across both conditions in frontal areas including the insular cortex, as well as parietal and occipital areas, and for both attention and detection of these signals. Psycho-physiological interaction analysis revealed that right insular cortex connectivity was modulated by the conscious detection of cardiac compared to somatosensory sensations, with greater connectivity to occipito-parietal regions when attending to cardiac signals. Our findings speak in favour of the inherent convergence of bodily-related signals and move beyond the apparent antagonism between exteroception and interoception.

neuroscience↗

Fluid and crystallised intelligence are associated with distinct regionalisation patterns of cortical morphology

Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N=10,145) of 9-11 year old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.

neuroscience↗

Economic, social, and physiological resilience predict brain structure and cognitive performance in 9 - 10-year-old children

While children with economic disadvantage are at risk for poorer outcomes in cognitive and brain development, less understood is the contribution of other factors in the broader socioeconomic context that may more closely index the underlying mechanisms influencing risk and resilience. We examined brain structure and cognitive test performance in association with economic disadvantage and 22 measures in the broader socioeconomic context among n = 8,158 demographically diverse 9-10-year-old children from the ABCD Study. Total cortical surface area and total cognition scores increased as a function of income-to-needs, with the steepest differences most apparent among children below and near poverty relative to their wealthier peers. We found three latent factors encompassing distinct relationships among our proximal measures, including social, economic, and physiological well-being, each associated with brain structure and cognitive performance independently of economic advantage. Our findings will inform future studies of risk and resilience in developmental outcomes for children with economic disadvantage.

neuroscience↗

Determining the association between cortical morphology and cognition in 10,145 children from the Adolescent Brain and Cognitive Development (ABCD) study using the MOSTest

Individuals undergo protracted changes in cortical morphology during childhood and adolescence, coinciding with cognitive development. Studies quantifying the association between brain structure and cognition do not always assess regional cortical morphology relative to global brain measures and typically rely on mass univariate statistics or ROI-based analyses. After controlling for global brain measures, it is possible to detect a residual regionalisation pattern indicating the size or thickness of different regions relative to the total cortical surface area or mean thickness. Individual variability in regionalisation may be important for understanding and predicting between subject variability in cognitive performance. Here we sought to determine whether the relative configuration of cortical architecture across the whole cortex was associated with cognition using a novel multivariate omnibus statistical test (MOSTest) in 10,145 children aged 9-10 years from the Adolescent Brain and Cognitive Development (ABCD) Study. MOSTest is better powered to detect associations that are widely distributed across the cortex compared to methods that assume sparse associations. We then quantified the magnitude of the association between vertex-wise cortical morphology and cognitive performance using a linear weighted sum across vertices, based on the estimated vertex-wise effect sizes. We show that the relative pattern of cortical architecture, after removing the effects of global brain measures, predicted unique variance associated with cognition across different imaging modalities and cognitive domains. SIGNIFICANCE STATEMENTThis paper demonstrates a significant advance in our understanding of the relationship between cortical morphology and individual variability in cognition. There is increasing evidence that brain-behaviour associations are distributed across the cortex. Using the unprecedented sample from the Adolescent Brain and Cognitive Development (ABCD) study and a novel application of a multivariate statistical approach (MOSTest), we have discovered specific distributed regionalization patterns across the cortex associated with cognition across multiple cognitive domains. This furthers our understanding of the relationship between brain structure and cognition, namely that these associations are not sparse and localized as assumed with traditional neuroimaging analyses. This multivariate method is extremely versatile and can be used in several different applications.

neuroscience↗

The polyvertex score (PVS): a whole-brain phenotypic prediction framework for neuroimaging studies

The traditional brain mapping approach has greatly advanced our understanding of the localized effect of the brain on behavior. However, the statistically significant brain regions identified by standard mass univariate models only explain minimal variance in behavior despite increased sample sizes and statistical power. This is potentially due to the generalizable explanatory signal in the brain being non-sparse, therefore not captured by the thresholded, localized model. Here we introduced the Bayesian polyvertex score (PVS-B), a whole-brain prediction framework that aggregates the effect sizes across all vertices to predict individual variability in behavior. The PVS-B estimates the posterior mean effect size at each vertex with mass univariate summary statistics and the correlation structure of the imaging phenotype, and weights the imaging phenotype of participants from an independent sample with these posterior mean effect sizes to estimate the generalizable effect of a brain-behavior association. Empirical data showed that the PVS-B was able to double the variance explained in general cognitive ability by an n-back fMRI contrast when compared to prediction models based on the mass univariate parameter estimates as well as models in which only vertices thresholded based on p-value were included. A fivefold improvement in variance explained by the PVS-B was observed using a stop signal task fMRI contrast to predict individual variability in the stop signal reaction time. We believe that the PVS-B can shed light on the multivariate investigation of brain-behavioral associations and will empower small scale neuroimaging studies with more reliable and accurate effect size estimates.

neuroscience↗

Polygenic Score of Intelligence is More Predictive of Crystallized than Fluid Performance Among Children

BackgroundFindings in adults have shown more culturally sensitive crystallized measures of intelligence have greater heritability, these results were not able to be shown in children. MethodsWith data from 8,518 participants, aged 9 to 11, from the Adolescent Brain Cognitive Development (ABCD) Study(R), we used polygenic predictors of intelligence test performance (based on genome-wide association meta-analyses of data from 269,867 individuals) and of educational attainment (based on data from 1.1 million individuals), associating these predictors with neurocognitive performance. We then assessed the extent of mediation of these associations by a measure of recreational reading. Resultsmore culturally sensitive crystallized measures were more strongly associated with the polygenic predictors than were less culturally sensitive fluid measures. This mirrored heritability differences reported previously in adults and suggests similar associations in children. Recreational reading more strongly statistically mediated the genetic associations with crystallized than those with fluid measures of cognition. ConclusionThis is consistent with a prominent role of gene-environment correlation in cognitive development measured by "crystallized" intelligence tests. Such experiential mediators may represent malleable targets for improving cognitive outcomes.

neuroscience↗