Spatio-temporal Modeling and Analysis of Brain Development

The incidence of preterm birth is increasing and has emerged as a leading cause of neurodevelopmental impairment in childhood. In early development, defined here as the period before and around birth, the brain undergoes significant morphological, functional and appearance changes. The scope and rate of change is arguably greater than at any other time in life, but quantitative markers of this period of development are limited. Improved understanding of cerebral changes during this critical period is important for mapping normal growth, and for investigating mechanisms of injury associated with risk factors for maldevelopment such as premature birth. The objective of this thesis is the development of methods for spatio-temporal modeling and quantitative measures of brain development that can assist understanding the patterns of normal growth and can guide interventions designed to reduce the burden of preterm brain injury. An approach for constructing high-definition spatio-temporal atlases of the developing brain is introduced. A novelty in the proposed approach is the use of a time-varying kernel width, to overcome the variations in the distribution of subjects at different ages. This leads to an atlas that retains a consistent level of detail at every time-point. The resulting 4D fetal and neonatal average atlases have greater anatomic definition than currently available 4D atlases, an important factor in improving registrations between the atlas and individual subjects with clear anatomical structures and atlas-based automatic segmentation. The fetal atlas provides a natural benchmark for assessing preterm born neonates and gives some insight into differences between the groups. Also, a novel framework for longitudinal registration which can accommodate large intra-subject anatomical variations is introduced. The framework exploits previously developed spatio-temporal atlases, which can aid the longitudinal registration process as it provides prior information about the missing anatomical evolution between two scans taken over large time-interval. Finally, a voxel-wise analysis framework is proposed which complements the analysis of changes in brain morphology by the study of spatio-temporal signal intensity changes in multi-modal MRI, which can offer a useful marker of neurodevelopmental changes

Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth

Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth

A lifespan perspective on brain-behavioural heterogeneity following very preterm birth

Background: Very preterm birth (VPT; at ≤ 32 weeks’ gestation) occurs during a highly critical stage of brain development, which makes the VPT new-born brain highly vulnerable to insult and long-lasting neurodevelopmental sequelae. Structural and functional brain alterations may be at least partly responsible for the behavioural difficulties described in VPT individuals across the lifespan. However, there is marked heterogeneity in the extent and presence of behavioural difficulties amongst VPT individuals, making it challenging to identify those vulnerable to developing mental health problems and cognitive difficulties. Hence, identifying underlying neurobiological markers of specific behavioural outcomes could help recognize those VPT individuals who may benefit from targeted support.Objective: The overarching objective of this PhD thesis is to stratify the heterogeneity in behavioural outcomes exhibited by VPT individuals, explore structural and functional brain alterations which may characterise distinct behavioural subgroups, and investigate the influence of clinical and environmental factors. The thesis is organised into four experimental studies addressing the following specific aims:o Study #1: to identify differences in neonatal structural brain volumes in subgroups of VPT born children screening negatively and positively for autism spectrum conditions and to explore the role of developmental delay in mediating and moderating childhood autism traits.o Study #2: to parse heterogeneity in neonatal clinical and social risk and childhood behavioural outcomes using data-driven integrative consensus clustering and to explore differences in neonatal brain volumes and structural and functional connectivity between the resultant subgroups.o Study #3: to compare resting state functional connectivity and structural volumes between groups of children stratified both in terms of their clinical characteristics (i.e., VPT and fullterm (FT) birth) and their behavioural profiles identified using data-driven consensus clustering regardless of their gestational age at birth. Post-hoc analyses aimed to elucidate whether clinical and environmental factors differ within VPT or FT children belonging to distinct subgroups.o Study #4: to use the same approach employed in Study #3 to investigate resting state functional connectivity in a sample of adults born VPT and FT.Methodology: Distinct psychometric screening criteria (Study #1) and advanced data-driven clustering approaches (Studies #2-4) were used to parse behavioural heterogeneity at different time points throughout development: toddlerhood (Study #1), early childhood (Study #2), middle childhood (Study #3), and adulthood (Study #4). Magnetic resonance (MR) imaging data were collected and analysed using advanced whole-brain approaches such as Tensor Based Morphometry, Tract Based Spatial Statistics, graph theory metrics, and Network Based Statistic to quantify brain volumes and structural and functional connectivity patterns characterising behavioural heterogeneity.Study participants: Participants were drawn from two cohort studies: (i) the Evaluation of Preterm Imaging Study (ePrime), which evaluated brain development using multi-modal MR imaging (at term equivalent age and at 7-12 years) and behavioural assessments (at 2, 4-7, and 7-12 years); and (ii) the University College Hospital London (UCHL) study, which studied adults (median age 30 years) using multi-modal MR imaging and behavioural assessments.Results:o Study #1: Smaller neonatal brainstem volumes and high levels of developmental delay were seen in one of two subgroups of VPT toddlers screening positively for autism according to different psychometric criteria, relative to those screening negatively. Developmental delay in this positively screening subgroup was seen to be mediating and moderating the onset of autism traits in childhood. Smaller neonatal cerebellar volumes differentiated between the two distinct subgroups of VPT children screening positively for autism, despite exhibiting similar extent of autism traits in early childhood. Together, results suggest the presence of distinct aetiological trajectories associated with autism traits.o Study #2: In early childhood, three data-driven behavioural subgroups of VPT children were delineated: (i) a ‘Resilient’ subgroup with favourable behavioural outcomes and a more cognitively stimulating home environment, (ii) an ‘At-risk’ subgroup with behavioural difficulties and high neonatal clinical risk, and (iii) an ‘Intermediate’ subgroup with intermediate behavioural outcomes, low neonatal clinical risk and a less cognitively stimulating home environment. Relative to the ‘Intermediate’ subgroup, the ‘Resilient’ subgroup displayed larger neonatal fronto-limbic regional volumes and functional connectivity and the ‘At-risk’ subgroup showed widespread fronto-temporo-limbic white matter alterations. These findings highlight the value of studying neonatal patterns of functional and structural brain development as potential biomarkers of childhood outcomes, as well as the importance of a supportive home environment to foster child development following VPT birth.o Study #3: Results show evidence of widespread volumetric alterations and increased functional connectivity in VPT children relative to controls. In middle childhood, stratifying the sample into two data-driven behavioural subgroups, independently of birth status identified: (i) a ‘General Difficulties’ subgroup displaying widespread decreases in functional connectivity and greater behavioural difficulties relative to a (ii) ‘General Resilience’ subgroup. A three-subgroup solution was also explored, identifying: a (I) ‘Neurodevelopmental Difficulties’ subgroup with socio-emotional and higher-order cognitive difficulties and reduced rostro-lateral prefrontal, brainstem, occipital, and cerebellar volumes, and a (II) ‘Psychiatric Difficulties’ subgroup exhibiting psychiatric and executive function difficulties with reduced dorsolateral prefrontal and cerebellar volumes, relative to a (III) ‘Typical Development’ subgroup. All brain differences, apart from cerebellar and occipital volumetric alterations, significantly differentiated between distinct data-driven behavioural subgroups after adjusting for preterm birth, highlighting the presence of VPT-specific neural alterations as well as unique neural patterns underlying behavioural difficulties in the general population, independently of birth status. Furthermore, VPT (but not FT) children belonging to Neurodevelopmental Difficulties or Psychiatric Difficulties subgroups displayed greater social risk relative to those in the Typical Development subgroup.o Study #4: Complex widespread patterns of both increased and decreased functional connectivity were found in VPT compared to FT born adults in default mode, visual, and ventral attention networks. In adulthood, when VPT and FT born adults were stratified in terms of their behavioural profiles (irrespective of preterm birth), two data-driven subgroups were identified: (i) an ‘At-risk’ subgroup with more behavioural difficulties and reduced functional connectivity in frontal opercular and insular areas relative to a (ii) ‘Resilient’ subgroup with more favourable behavioural outcomes. These results indicate that functional connectivity between the default mode, ventral attention, and visual networks characterise clinically defined groups (VPT and FT) and are different from the connectivity patterns that characterise adults subdivided in terms of their behavioural profiles (irrespective of birth group), which are anchored in insular and frontal opercular regions. Moreover, social risk was found to be greater within adults born VPT belonging to At-risk relative to Resilient subgroups, while this relationship was not identified in those born FT.Conclusions: Collectively, these findings indicate a long-lasting presence of neurodevelopmental heterogeneity within VPT and FT samples which seems to persist throughout the lifespan. Specific structural and functional alterations differentiating between distinct behavioural profiles across both VPT and FT samples are also identified; whereby alterations localised to fronto-temporolimbic regions seem to be characteristic of behavioural difficulties in VPT and FT samples regardless of their birth status, while alterations to brain regions including visual and cerebellar areas may be characterising biomarkers of outcomes specifically in VPT samples. Implications of these findings suggest a potential benefit of using MRI to detect neurobiological markers of behavioural outcomes, which can in turn guide the implementation of personalised interventions for those at-risk of developing specific behavioural difficulties. Results presented here also highlight the importance of fostering an enriching environment to probe resilience against developing behavioural difficulties, particularly for those born VPT.<br/

The Origins and Development of Visual Categorization

Forming categories is a core part of human cognition, allowing us to make quickly make inferences about our environment. This thesis investigated some of the major theoretical interpretations surrounding the neural basis of visual category development. In adults, there are category-selective regions (e.g. in ventral temporal cortex) and networks (which include regions outside traditional visual regions—e.g. the amygdala) that support visual categorization. While there has been extensive behavioural work investigating visual categorization in infants, the neural sequence of development remains poorly understood. Based on behavioral experiments, one view holds that infants are initially using subcortical structures to recognize faces. Indeed, it has been proposed that the subcortical pathway remains active for rapid face detection in adults. In order to test this in adults, I exploited the nasal-temporal asymmetry of the proposed retinocollicular pathway to see if preferentially presenting stimuli to the nasal hemiretina resulted in a fast face detection advantage when contrasted with presentations to the temporal hemiretina. Across four experiments, I failed to find any evidence of a subcortical advantage but still found that a rapid, coarse pathway exists. Therefore, I moved to investigate the development of the cortical visual categorization regions in the ventral temporal cortex (VTC). I characterised the maturity of the face, place and tool regions found in the VTC, looking at the long-range connectivity in 1-9 month-old infants using MRI tractography and a linear discriminant classifier. The face and place regions showed adult-like connectivity throughout infancy, but the tool-network underwent significant maturation until 9 months. Finally, given this maturity of face and place regions in early infancy, I decided to test whether the organization of the VTC was related to the sequence of categories infants acquire. I used language age of acquisition measurements, determining that infants produce significantly more animate than inanimate words up until 29-months, in line with the animacy distinction in the VTC. My work demonstrates the surprising role and maturity of the cortical regions and networks involved in visual categorization. My thesis develops new methods for studying the infant brain and underscores the utility of publicly available data when studying development

Modeling longitudinal MRI changes in populations using a localized, information-theoretic measure of contrast

pre-printLongitudinal MR imaging during early brain development provides important information about growth patterns and the development of neurological disorders. We propose a new framework for studying brain growth patterns within and across populations based on MRI contrast changes, measured at each time point of interest and at each voxel. Our method uses regression in the LogOdds space and an information-theoretic measure of distance between distributions to capture contrast in a manner that is robust to imaging parameters and without requiring intensity normalization. We apply our method to a clinical neuroimaging study on early brain development in autism, where we obtain a 4D spatiotemporal model of contrast changes in multimodal structural MRI

A longitudinal structural MRI study of change in regional contrast in Autism Spectrum Disorder

pre-printAuthors: Avantika Vardhan1, Joseph Piven2, Marcel Prastawa3, Guido Gerig3 Institutions: 1Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, United States, 2Dept of Psychiatry, UNC School of Medicine, Chapel Hill, NC, 3University of Utah, Salt Lake City, UT Introduction: The brain undergoes tremendous changes in shape, size, structure, and chemical composition, between birth and 2 years of age [Rutherford, 2001]. Existing studies have focused on morphometric and volumetric changes to study the early developing brain. Although there have been some recent appearance studies based on intensity changes [Serag et al., 2011], these are highly dependent on the quality of normalization. The study we present here uses the changes in contrast between gray and white matter tissue intensities in structural MRI of the brain, as a measure of regional growth [Vardhan et al., 2011]. Kernel regression was used to generate continuous curves characterizing the changes in contrast with time. A statistical analysis was then performed on these curves, comparing two population groups : (i) HR+ : high-risk subjects who tested positive for Autism Spectrum Disorder (ASD), and (ii) HR- : high-risk subjects who tested negative for ASD

Processing of structural neuroimaging data in young children:bridging the gap between current practice and state-of-the-art methods

The structure of the brain is subject to very rapid developmental changes during early childhood. Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the developing brain, toward understanding typical and atypical trajectories. However, it has also been demonstrated that application of currently standard MRI processing methods that have been developed with datasets from adults may not be appropriate for use with pediatric datasets. In this review, we examine the approaches currently used in MRI studies involving young children, including an overview of the rationale for new MRI processing methods that have been designed specifically for pediatric investigations. These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained with longitudinal designs. The overall goal is to raise awareness of the existence of these methods and the possibilities for implementing them in developmental neuroimaging studies