Shape analysis based on depth-ordering

In this paper we propose a new method for shape analysis based on the ordering of shapes using band-depth. We use this band-depth to non-parametrically define a global depth for a shape with respect to a reference population, typically consisting of normal control subjects. This allows us to globally quantify differences with respect to “normality”. Using the depth-ordering of shapes also allows the detection of localized shape differences by using α-central values of shapes. We propose permutation tests to statistically assess global and local shape differences. We further determine the directionality of shape differences (local inflation versus deflation). The method is evaluated on a synthetically generated striatum dataset, and applied to detect shape differences in the hippocampus between subjects with first-episode schizophrenia and normal controls

Effect of 16P11.2 copy number variants on cognitive traits and brain structures

The 600kb 16p11.2 CNVs (breakpoints 4–5, 29.6-30.2 Mb-Hg19) are among the most frequent genetic risk factors for neurodevelopmental and psychiatric conditions: A 10-fold enrichment of deletions and duplications is observed in autism cohorts and a 10-fold enrichment of duplications in schizophrenia cohorts. Previous studies demonstrated “mirror” effects of both CNVs on body mass index and head circumference (deletion>control>duplication). However, the large global effect of brain size and the sample size of the two previous neuroimaging studies limited the interpretation of the analyses on regional brain structures, any estimate of the effect size, and the generalizability of the results across different ascertainments of the patients. In the first part of my Ph.D., I analyze structural magnetic resonance imaging (MRI) on 78 deletion carriers, 71 duplication carriers, and 212 controls. I show that both CNVs affect in a “mirror” way the volume and the cortical surface of the insula (Cohen’s d>1), whilst other brain regions are preferentially altered in either the deletion carriers (calcarine cortex and superior, middle, transverse temporal gyri, Cohen’s d>1) or the duplication carriers (caudate and hippocampus, Cohen’s d of 0.5 to 1). Results are generalizable across scanning sites, computational methods, age, sex, ascertainment for psychiatric disorders. They partially overlap with results of meta-analyses performed across psychiatric disorders. In the second part, I characterize the developmental trajectory of global brain metrics and regional brain structures in the 16p11.2 CNV carriers. I adapt a previously published longitudinal pipeline and normalizing method, derived from 339 typically developing individuals aged from 4.5 to 20 years old. From this population of reference, I Z-score our cross-sectional 16p11.2 dataset and show that all the brain alterations in the 16p11.2 carriers are already present at 4.5 years old and follow parallel trajectories to the controls. In summary, my results suggest that brain alterations, present in childhood and stable across adolescence and adulthood, are related to the risk conferred by the 16p11.2 CNVs, regardless of the carriers’ symptoms. Additional factors are therefore likely required for the development of psychiatric disorders. I highlight the relevance of studying genetic risk factors and mechanisms as a complement to groups defined by behavioral criteria. Further studies comparing multiple CNVs and monogenic conditions, from the earliest age, are required to understand the onset of neuroanatomical alterations and their overlap between different genetic risk factors for neurodevelopmental disorders. -- Les variations en nombre de copies (CNV), au locus 16p11.2 et d’une taille d’600kb (points de cassure 4–5, 29.6-30.2 Mb-Hg19) représentent un des facteurs de risque génétique les plus fréquents parmi les troubles psychiatriques : 10% d’enrichissement en délétion et duplication pour les troubles du spectre autistique, 10% d’enrichissement en duplication pour la schizophrénie. Les effets « miroirs » des deux CNVs sur l’indice de masse corporelle et le périmètre cranien ont déjà été démontrés (délétion>contrôle>duplication). Cependant, les différences en taille de cerveau et les échantillons des deux précédentes études de neuro- imagerie ont limité les analyses des régions cérébrales, l’estimation de la taille des effets, et la généralisation des résultats selon les modes de recrutement des patients. Dans cette thèse, j’analyse les images par résonance magnétique (IRM) de 78 porteurs de la délétion, 71 porteurs de la duplication et 212 participants contrôles. Je montre que les deux CNVs sont associées à des différences « en miroir » du volume et de la surface corticale de l’insula (Cohen’s d>1), tandis que le cortex calcarin, les gyri temporaux supérieur, moyen et transverse sont préférentiellement altérés par la délétion (Cohen’s d>1), les noyaux caudés et l’hippocampe sont préférentiellement altérés par la duplication (0.5<Cohen’s d<1). Les résultats sont généralisables à travers les differents sites d’IRM, les méthodes d’analyse computationnelle, les âges, les sexes et les divers diagnostiques psychiatriques des patients. Les résultats chevauchent partiellement ceux d’une méta-analyse sur plusieurs diagnostiques psychiatriques. Dans un second temps, je caractérise la trajectoire développementale de ces différences cérébrales. J’adapte un pipeline longitunal et une méthode de normalisation déjà publiés, construits à partir de 339 participants contrôles de 4.5 à 20 ans. Je calcule des Z-scores pour nos données transversales et montre que les différences cérébrales liées aux CNVs sont déjà présentes à 4.5 ans, avec les mêmes tailles d’effet et une trajectoire parallèle aux contrôles. En résumé, mes résultats suggèrent que les différences cérébrales, présentes dans la jeune enfance et stables à l’adolescence et l’âge adulte, sont liées au risque conféré par les CNVs en 16p11.2, quelque soient les symptômes. Des facteurs additionnels sont probablement nécessaires pour le développement de maladies psychiatriques. Je montre la pertinence d’étudier les facteurs de risque génétiques en complément des groupes de patients définis sur des critères comportementaux. Des études comparant diverses conditions génétiques, dès la naissance, sont nécessaires pour comprendre le début et le chevauchement des différences neuro-anatomiques observées pour différents facteurs de risque génétiques

Brain Microstructure: Impact of the Permeability on Diffusion MRI

Diffusion Magnetic Resonance Imaging (dMRI) enables a non invasive in-vivo characterization of the brain tissue. The disentanglement of each microstructural property reflected on the total dMRI signal is one of the hottest topics in the field. The dMRI reconstruction techniques ground on assumptions on the signal model and consider the neurons axons as impermeable cylinders. Nevertheless, interactions with the environment is characteristic of the biological life and diffusional water exchange takes place through cell membranes. Myelin wraps axons with multiple layers constitute a barrier modulating exchange between the axon and the extracellular tissue. Due to the short transverse relaxation time (T2) of water trapped between sheets, myelin contribution to the diffusion signal is often neglected. This thesis aims to explore how the exchange influences the dMRI signal and how this can be informative on myelin structure. We also aimed to explore how recent dMRI signal reconstruction techniques could be applied in clinics proposing a strategy for investigating the potential as biomarkers of the derived tissue descriptors. The first goal of the thesis was addressed performing Monte Carlo simulations of a system with three compartments: intra-axonal, spiraling myelin and extra-axonal. The experiments showed that the exchange time between intra- and extra-axonal compartments was on the sub-second level (and thus possibly observable) for geometries with small axon diameter and low number of wraps such as in the infant brain and in demyelinating diseases. The second goal of the thesis was reached by assessing the indices derived from three dimensional simple harmonics oscillator-based reconstruction and estimation (3D-SHORE) in stroke disease. The tract-based analysis involving motor networks and the region-based analysis in grey matter (GM) were performed. 3D-SHORE indices proved to be sensitive to plasticity in both white matter (WM) and GM, highlighting their viability as biomarkers in ischemic stroke. The overall study could be considered the starting point for a future investigation of the interdependence of different phenomena like exchange and relaxation related to the established dMRI indices. This is valuable for the accurate dMRI data interpretation in heterogeneous tissues and different physiological conditions

From gene to function: using new technologies for solving old problems.

Recent advances in DNA sequencing have changed the field of genomics as well as that of proteomics making it possible to generate gigabases of genome and transcriptome sequence data at substantially lower cost than it was possible just ten years ago. In recent years, many high-throughput technologies have been developed to interrogate various aspects of cellular processes, including sequence and structural variation and the transcriptome, epigenome, proteome and interactome. These Next Generation Sequencing (NGS) experimental technologies are more mature and accessible than the computational tools available for individual researchers to move, store, analyse and present data in a user-friendly and reproducible fashion. My research work is placed in this scenario and focuses on the analysis of data produced by NGS technologies as well as on the development of new tools aimed at solving the different problems that arise during NGS data analysis. In order to achieve this aim, my group and I have dealt with several open biomedical problems in collaboration with different research groups of the Sapienza University. Some of these experiments have already given interesting results but mostly have represented the occasion and starting point for the development of new tools able to improve some crucial steps of the analyses, solve problems derived by the system complexity and make the results easier to understand for the researchers. Some examples are IsomirT, a tool for the small RNA-Seq analysis and isomiR identification, Phagotto, a tool for analysing deep sequencing data derived from phage-displayed libraries and FIDEA, a web server for the functional interpretation of differential expression analysis. Recent reports have demonstrated that individual microRNAs can be heterogeneous in length and/or sequence producing multiple mature variants that have been dubbed isomiRs. IsomirT is a useful tool to improve and simplify the search for isomiRs starting directly from the results of a miRNA-sequencing experiment. By using it, we observed the behaviour of isomiRs in different cell types and in different biological replicates. Our results indicate that the distribution of the microRNA variants is similar among replicates and different among cells/tissues suggesting that the isomiRs have a functional role in the cell. The use of the NGS technologies for the analysis of antibody selected sequences both using phage display libraries and in vitro selection processes is becoming increasingly popular. By using these technologies, the experimental group headed by prof. Felici has introduced a new experimental pipeline, named PROFILER, aimed at significantly empowering the analysis of antigen-specific libraries. A key step to exploit this idea has been to develop a new tool, Phagotto, for processing and analysing the data derived by sequencing. PROFILER, in combination with Phagotto, seems ideally suited to streamline and guide rational antigen design, adjuvant selection, and quality control of newly produced vaccines. The publicly available web server FIDEA allows experimentalists to obtain a functional interpretation of the results derived from differential expression analysis and to test their hypothesis quickly and easily. The tool performs an enrichment analysis i.e. an analysis of specific properties that are distributed in a non random fashion in the up-regulated and down-regulated genes, taken both together and separately. It has been shown to be very useful and is being heavily used from scientists all over the world, more than 1500 requests for analysis have been submitted to the server in six months. Furthermore, during the course of the PhD I implemented pipelines for the speeding up and optimization of protocols for NGS data analysis and applied them to biomedical projects. Of course not all the proteins have a complete functional annotation and consequently the issue of predicting the function of proteins with a partial or no functional annotation arises. This can be done both by exploiting the 3D structure of the protein or by inferring the function directly from the sequence. A real challenge, however, is the assessment of the accuracy of existing methods. In this context the help that critical assessment experiments can give is essential. We have had the possibility to be involved, as assessors, in the world wide experiment CASP (Critical Assessment of protein Structure Prediction). In particular, we are involved in the assessment of the residue-residue contacts in which the participant groups provide a list of predicted contacts between residues that hopefully can be used as constraints to fold the protein. We proposed and implemented new methodologies to understand which method works better and where future efforts should be focused

Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging

The value of in vivo preclinical diffusion MRI (dMRI) is substantial. Small-animal dMRI has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. Many of the influential works in this field were first performed in small animals or ex vivo samples. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the data. This work aims to serve as a reference, presenting selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. In each section, we also highlight areas for which no guidelines exist (and why), and where future work should focus. We first describe the value that small animal imaging adds to the field of dMRI, followed by general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss how they are appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, imaging sequences and data processing, including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Comment: 69 pages, 6 figures, 1 tabl

Image and Shape Analysis for Spatiotemporal Data

In analyzing brain development or identifying disease it is important to understand anatomical age-related changes and shape differences. Data for these studies is frequently spatiotemporal and collected from normal and/or abnormal subjects. However, images and shapes over time often have complex structures and are best treated as elements of non-Euclidean spaces. This dissertation tackles problems of uncovering time-varying changes and statistical group differences in image or shape time-series. There are three major contributions: 1) a framework of parametric regression models on manifolds to capture time-varying changes. These include a metamorphic geodesic regression approach for image time-series and standard geodesic regression, time-warped geodesic regression, and cubic spline regression on the Grassmann manifold; 2) a spatiotemporal statistical atlas approach, which augments a commonly used atlas such as the median with measures of data variance via a weighted functional boxplot; 3) hypothesis testing for shape analysis to detect group differences between populations. The proposed method for cross-sectional data uses shape ordering and hence does not require dense shape correspondences or strong distributional assumptions on the data. For longitudinal data, hypothesis testing is performed on shape trajectories which are estimated from individual subjects. Applications of these methods include 1) capturing brain development and degeneration; 2) revealing growth patterns in pediatric upper airways and the scoring of airway abnormalities; 3) detecting group differences in longitudinal corpus callosum shapes of subjects with dementia versus normal controls.Doctor of Philosoph

MRI measures of brain integrity and their relation to processing speed in the elderly

A significant percentage of the elderly population experiences at least one geriatric disability. Previous studies have shown that geriatric disabilities are preceded by sub-clinical cognitive changes of aging and brain changes seen on magnetic resonance imaging (MRI). Decreased information processing speed has been identified as a common factor associated with age-related disabilities in gait, cognition, and mood. However, the current neurocognitive model of aging is incomplete; there remains uncertainty about the relationships between the different components of brain integrity and cognitive function. The goals of this dissertation are to characterize the relationships between different functional and structural MRI markers (for example: macro-structural, micro-structural, physiologic) with respect to cognitive aging and to improve the neuroimaging toolset for oldest old.We studied the relationship between functional MRI markers, structural MRI markers, and information processing speed in a sample of twenty-five healthy elderly subjects. We found that recruitment of fronto-parietal brain areas was associated with higher performance. Also, greater structural damage (white matter integrity) was associated with lower activation in prefrontal and anterior cingulate regions. In the presence of underlying brain connectivity structural abnormalities, additional posterior parietal activation was found to be important for maintaining higher task performance.MRI MEASURES OF BRAIN INTEGRITY AND THEIR RELATION TO PROCESSING SPEED IN THE ELDERLYVijay Krishna Venkatraman, Ph.D.University of Pittsburgh, 2010vWe also studied MRI measures of brain structure in a sample of 277 community-dwelling older adults free from neurological diseases. This study used a set of neuroimage analysis pathways optimized for the MRI images and examined the macro- and micro-structural indices. The results indicate that both the macro- and micro-structural MRI indices may provide complementary information on neuroanatomical correlates of information processing speed. The micro-structural MRI indices of white matter integrity were found to be the strongest correlate of information processing speed in this sample.While developing the image analysis pipelines for this dataset, we noticed that the diffusion tensor-imaging pathway was particularly sensitive to the approach of localizing the white matter tracts. We used both empirical and simulated datasets to confirm our hypothesis that the mean fractional anisotropy of the white matter tract is more sensitive to individual differences in the elderly when compared to a skeleton based approach

Applications of realtime fMRI for non-invasive brain computer interface-decoding and neurofeedback

Non-invasive brain-computer interfaces (BCIs) seek to enable or restore brain function by using neuroimaging e.g. functional magnetic resonance imaging (fMRI), to engage brain activations without the need for explicit behavioural output or surgical implants. Brain activations are converted into output signals, for use in communication interfaces, motor prosthetics, or to directly shape brain function via a feedback loop. The aim of this thesis was to develop cognitive BCIs using realtime fMRI (rt-fMRI), with the potential for use as a communication interface, or for initiating neural plasticity to facilitate neurorehabilitation. Rt-fMRI enables brain activation to be manipulated directly to produce changes in function, such as perception. Univariate and multivariate classification approaches were used to decode brain activations produced by the deployment of covert spatial attention to simple visual stimuli. Primary and higher order visual areas were examined, as well as potential control regions. The classification platform was then developed to include the use of real-world visual stimuli, exploiting the use of category-specific visual areas, and demonstrating real-world applicability as a communications interface. Online univariate classification of spatial attention was successfully achieved, with individual classification accuracies for 4-quadrant spatial attention reaching 70%. Further, a novel implementation of m-sequences enabled the use of the timing of stimuli presentation to enhance signal characterisation. An established rt-fMRI analysis loop was then used for neurofeedback-led manipulation of category-specific visual brain regions, modulating their functioning, and, as a result, biasing visual perception during binocular rivalry. These changes were linked with functional and effective connectivity changes in trained regions, as well as in a putative top-down control region. The work presented provides proof-of-principle for non-invasive BCIs using rt-fMRI, with the potential for translation into the clinical environment. Decoding and 4 neurofeedback applied to non-invasive and implantable BCIs form an evolving continuum of options for enabling and restoring brain function

Imaging genetics : Methodological approaches to overcoming high dimensional barriers

Imaging genetics is still a quite novel area of research which attempts to discover how genetic factors affect brain structures and functions. In this thesis, using a various methodological approaches I showed how it can contribute to our understanding of the complex genetic architecture of the human brain