[Show abstract][Hide abstract] ABSTRACT: 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. Hum Brain Mapp, 2016.
Full-text · Article · Jan 2016 · Human Brain Mapping
[Show abstract][Hide abstract] ABSTRACT: In the present study, we explored how Age of Acquisition (AoA) of L2 affected brain structures in bilingual individuals. Thirty-six native English speakers who were bilingual were scanned with high resolution MRI. After MRI signal intensity inhomogeneity correction, we applied both voxel-based morphometry (VBM) and surface-based morphometry (SBM) approaches to the data. VBM analysis was performed using FSL's standard VBM processing pipeline. For the SBM analysis, we utilized a semi-automated sulci delineation procedure, registered the brains to an atlas, and extracted measures of twenty four pre-selected regions of interest. We addressed three questions: (1) Which areas are more susceptible to differences in AoA? (2) How do AoA, proficiency and current level of exposure work together in predicting structural differences in the brain? And (3) What is the direction of the effect of AoA on regional volumetric and surface measures? Both VBM and SBM results suggested that earlier second language exposure was associated with larger volumes in the right parietal cortex. Consistently, SBM showed that the cortical area of the right superior parietal lobule increased as AoA decreased. In contrast, in the right pars orbitalis of the inferior frontal gyrus, AoA, proficiency, and current level of exposure are equally important in accounting for the structural differences. We interpret our results in terms of current theory and research on the effects of L2 learning on brain structures and functions.
Full-text · Article · Nov 2015 · Journal of Neurolinguistics
[Show abstract][Hide abstract] ABSTRACT: Depression, anxiety, and posttraumatic stress disorder are linked to altered limbic morphology, dysregulated neuroendocrine function, and heightened amygdala responses to salient social cues. Oxytocin appears to be a potent modulator of amygdala reactivity and neuroendocrine responses to psychosocial stress. Given these stress regulatory effects, there is increasing interest in understanding the role of oxytocin in vulnerability to stress-related clinical disorders. The present study examines the impact of a common functional variant within the oxytocin receptor (OXTR) gene (rs2254298) on structure and function of the amygdala in a high-risk sample of urban, low-income, minority youth with a high incidence of early life stress (ELS). Compared to G/G homozygotes, youth carrying the OXTR A-allele showed increased amygdala volume, reduced behavioral performance, and heightened amygdala response during two functional magnetic resonance imaging (fMRI) tasks that involved viewing socially-relevant face stimuli. Higher amygdala response was related to ELS in A-alleles carriers but not G/G homozygotes. These findings underscore a series of relationships among a common oxytocin system gene variant, ELS exposure, and structure and function of the amygdala in early life. Heightened amygdala response to salient social cues in OXTR A-allele carriers may elevate risk for emotional psychopathology by increasing amygdala involvement in disambiguating environmental cues, particularly for individuals with ELS.
[Show abstract][Hide abstract] ABSTRACT: Childhood trauma is a major precipitating factor in psychiatric disease. Emerging data suggest that stress susceptibility is genetically determined, and that risk is mediated by changes in limbic brain circuitry. There is a need to identify markers of disease vulnerability, and it is critical that these markers be investigated in childhood and adolescence, a time when neural networks are particularly malleable and when psychiatric disorders frequently emerge. In this preliminary study, we evaluated whether a common variant in the brain-derived neurotrophic factor (BDNF) gene (Val66Met; rs6265) interacts with childhood trauma to predict limbic gray matter volume in a sample of 55 youth high in sociodemographic risk. We found trauma-by-BDNF interactions in the right subcallosal area and right hippocampus, wherein BDNF-related gray matter changes were evident in youth without histories of trauma. In youth without trauma exposure, lower hippocampal volume was related to higher symptoms of anxiety. These data provide preliminary evidence for a contribution of a common BDNF gene variant to the neural correlates of childhood trauma among high-risk urban youth. Altered limbic structure in early life may lay the foundation for longer term patterns of neural dysfunction, and hold implications for understanding the psychiatric and psychobiological consequences of traumatic stress on the developing brain.
Full-text · Article · Aug 2015 · European Child & Adolescent Psychiatry
[Show abstract][Hide abstract] ABSTRACT: Magnetic field inhomogeneities in echo planar images (EPI) can cause large distortion in the phase encoding dimension. In functional MRI (fMRI), this distortion can shift activation loci, increase inter subject variability, and reduce statistical power during group analysis. Distortion correction methods that make use of acquired magnetic field maps have been developed, however, field maps are not always acquired or may not be available to researchers. An alternative approach, which we pursue in this paper, is to estimate the distortion retrospectively by spatially registering the EPI to a structural MRI. We describe a constrained non-linear registration method for correcting fMRI distortion that uses T1-weighted images and does not require field maps. We compared resting state results from uncorrected fMRI, fMRI data corrected with field maps, and fMRI data corrected with our proposed method in data from 20 subjects. The results show that the estimated field maps were similar to the acquired field maps and that the proposed method reduces the overall error in independent component location.
[Show abstract][Hide abstract] ABSTRACT: Several studies comparing adult musicians and non-musicians have provided compelling evidence for functional and anatomical differences in the brain systems engaged by musical training. It is not known, however, whether those differences result from long-term musical training or from pre-existing traits favoring musicality. In an attempt to begin addressing this question, we have launched a longitudinal investigation of the effects of childhood music training on cognitive, social and neural development. We compared a group of 6- to 7-year old children at the start of intense after-school musical training, with two groups of children: one involved in high intensity sports training but not musical training, another not involved in any systematic training. All children were tested with a comprehensive battery of cognitive, motor, musical, emotional, and social assessments and underwent magnetic resonance imaging and electroencephalography. Our first objective was to determine whether children who participate in musical training were different, prior to training, from children in the control groups in terms of cognitive, motor, musical, emotional, and social behavior measures as well as in structural and functional brain measures. Our second objective was to determine whether musical skills, as measured by a music perception assessment prior to training, correlates with emotional and social outcome measures that have been shown to be associated with musical training. We found no neural, cognitive, motor, emotional, or social differences among the three groups. In addition, there was no correlation between music perception skills and any of the social or emotional measures. These results provide a baseline for an ongoing longitudinal investigation of the effects of music training.
Full-text · Article · Sep 2014 · Frontiers in Human Neuroscience
[Show abstract][Hide abstract] ABSTRACT: Background / Purpose:
Sulcal landmarks have been used extensively for cortical registration, and we have recently seen increasing interest in analyzing the geometry of sulcal anatomy in the study of disease progression, aging, brain asymmetry and various studies of differences in neuropsychological groupings. We present a method for automated generation and analysis of sulcal curves. We also present a novel invariant representation of curves termed the Anisotropic Global Point signature (AGPS) that allows quantitative comparison of the shapes of curves. The AGPS representation is applied to analysis of sulcal shape symmetry and sulcal shape inheritability in a twins study.
We have developed a method for automated shape analysis of sulcal curves allowing us to perform quantitative morphometric analysis of the cortical shapes.This cortical morphometry allows us to analyze the shape of the sulcal curves on the cortex in a quantitative manner.
[Show abstract][Hide abstract] ABSTRACT: Analyzing geometry of sulcal curves on the human cortical surface requires a shape representation invariant to Euclidean motion. We present a novel shape representation that characterizes the shape of a curve in terms of a coordinate system based on the eigensystem of the anisotropic Helmholtz equation. This representation has many desirable properties: stability, uniqueness and invariance to scaling and isometric transformation. Under this representation, we can find a point-wise shape distance between curves as well as a bijective smooth point-to-point correspondence. When the curves are sampled irregularly, we also present a fast and accurate computational method for solving the eigensystem using a finite element formulation. This shape representation is used to find symmetries between corresponding sulcal shapes between cortical hemispheres. For this purpose, we automatically generate 26 sulcal curves for 24 subject brains and then compute their invariant shape representation. Left-right sulcal shape symmetry as measured by the shape representation's metric demonstrates the utility of the presented invariant representation for shape analysis of the cortical folding pattern.
[Show abstract][Hide abstract] ABSTRACT: Background / Purpose:
To improve the accuracy of the cortical surface registration method.
We now use the automated method presented here to perform surface registration and label refinement, making the entire surface and volume registration and labeling sequence fully automatic.
[Show abstract][Hide abstract] ABSTRACT: The degree to which one identifies as male or female has a profound impact on one's life. Yet, there is a limited understanding of what contributes to this important characteristic termed gender identity. In order to reveal factors influencing gender identity, studies have focused on people who report strong feelings of being the opposite sex, such as male-to-female (MTF) transsexuals.
To investigate potential neuroanatomical variations associated with transsexualism, we compared the regional thickness of the cerebral cortex between 24 MTF transsexuals who had not yet been treated with cross-sex hormones and 24 age-matched control males.
Results revealed thicker cortices in MTF transsexuals, both within regions of the left hemisphere (i.e., frontal and orbito-frontal cortex, central sulcus, perisylvian regions, paracentral gyrus) and right hemisphere (i.e., pre-/post-central gyrus, parietal cortex, temporal cortex, precuneus, fusiform, lingual, and orbito-frontal gyrus).
These findings provide further evidence that brain anatomy is associated with gender identity, where measures in MTF transsexuals appear to be shifted away from gender-congruent men.
Full-text · Article · Aug 2012 · Journal of Behavioral and Brain Science
[Show abstract][Hide abstract] ABSTRACT: Registration and delineation of anatomical features in MRI of the human brain play an important role in the investigation of brain development and disease. Accurate, automatic and computationally efficient cortical surface registration and delineation of surface-based landmarks, including regions of interest (ROIs) and sulcal curves (sulci), remain challenging problems due to substantial variation in the shapes of these features across populations. We present a method that performs a fast and accurate registration, labeling and sulcal delineation of brain images. The new method presented in this paper uses a multiresolution, curvature based approach to perform a registration of a subject brain surface model to a delineated atlas surface model; the atlas ROIs and sulcal curves are then mapped to the subject brain surface. A geodesic curvature flow on the cortical surface is then used to refine the locations of the sulcal curves sulci and label boundaries further, such that they follow the true sulcal fundi more closely. The flow is formulated using a level set based method on the cortical surface, which represents the curves as zero level sets. We also incorporate a curvature based weighting that drives the curves to the bottoms of the sulcal valleys in the cortical folds. Finally, we validate our new approach by comparing sets of automatically delineated sulcal curves it produced to corresponding sets of manually delineated sulcal curves. Our results indicate that the proposed method is able to find these landmarks accurately.
[Show abstract][Hide abstract] ABSTRACT: Knowledge of the properties of white matter fiber tracts isa crucial and necessary step toward a precise understanding of the functional architecture of the living human brain. Previously, this knowledge was severely limited, as it was difficult to visualize these structures or measure their functions in vivo. The HCP has recently generated considerable interest because of its potential to explore connectivity and its relationship with genetics and behavior. For neuroscientists and the lay public alike, the ability to assess, measure, and explore this wealth of layered information concerning how the brain is wired is a much sought after prize.The navigation of the human connectome and the discovery of how it is affected through genetics, and in a range of neurological and psychiatric diseases, have far reaching implications. From a range of ongoing connectomics related activities, the systematic characterization of brain connectedness and the resulting functional aspects of such connectivity will not only realize the work of Ramón y Cajal and others, but will also greatly expand our understanding of the brain, the mind, and what it is to be truly human. The similarities and differences that mark normal diversity will help us to understand variation among people and set the stage to chart genetic influences on typical brain development and decline during aging. What is more, an understanding of how brains might become disordered will shed light on autism, schizophrenia, Alzheimer’s, and other diseases that exact a tremendous and terrible social and economic toll.
[Show abstract][Hide abstract] ABSTRACT: Sulcal folds (sulci) on the cortical surface are important landmarks of interest for investigating brain development and disease. Accurate and automatic delineation of the sulci is a challenging problem due to substantial variability in their shapes across populations. We present a geodesic curvature flow method for an automatic and accurate delineation of sulcal curves. We assume as input an atlas brain surface mesh on which a set of sulcal curves have been delineated. The sulcal curves are transferred to approximate corresponding locations on the subject brain using a transformation defined by an automatic surface based registration method. The locations of these curves are then refined to follow the true sulcal fundi more closely using geodesic curvature flow on the cortical surface. We present a level set based formulation of this flow on non-flat surfaces which represents the sulcal curves as zero level sets. We also incorporate a curvature based weighting that drives the sulcal curves to the bottoms of the sulcal valleys in the cortical folds. The resulting PDE is discretized on a triangulated mesh using finite elements. Finally, we present a validation by comparing sets of automatically delineated sul-cal curves with sets of manually delineated sulcal curves and show that the proposed method is able to find them accurately.
[Show abstract][Hide abstract] ABSTRACT: Insight into brain development and organization can be gained by computing correlations between structural and functional measures in parcellated cortex. Partial correlations can often reduce ambiguity in correlation data by identifying those pairs of regions whose similarity cannot be explained by the influence of other regions with which they may both interact. Consequently a graph with edges indicating non-zero partial correlations may reveal important subnetworks obscured in the correlation data. Here we describe and investigate PC∗, a graph pruning algorithm for identification of the partial correlation network in comparison to direct calculation of partial correlations from the inverse of the sample correlation matrix. We show that PC∗ is far more robust and illustrate its use in the study of covariation in cortical thickness in ROIs defined on a parcellated cortex.
Preview · Article · Jan 2012 · Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging
[Show abstract][Hide abstract] ABSTRACT: The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.
Full-text · Article · Nov 2011 · Journal of the American Medical Informatics Association
[Show abstract][Hide abstract] ABSTRACT: Segmenting brain from non-brain tissue within magnetic resonance (MR) images of the human head, also known as skull-stripping, is a critical processing step in the analysis of neuroimaging data. Though many algorithms have been developed to address this problem, challenges remain. In this paper, we apply the “deformable organism” framework to the skull-stripping problem. Within this framework, deformable models are equipped with higher-level control mechanisms based on the principles of artificial life, including sensing, reactive behavior, knowledge representation, and proactive planning. Our new deformable organisms are governed by a high-level plan aimed at the fully-automated segmentation of various parts of the head in MR imagery, and they are able to cooperate in computing a robust and accurate segmentation. We applied our segmentation approach to a test set of human MRI data using manual delineations of the data as a reference “gold standard.” We compare these results with results from three widely used methods using set-similarity metrics.