Altered structural connectivity of the left visual thalamus in developmental dyslexia

Developmental dyslexia is characterized by persistent reading and spelling deficits. Partly due to technical challenges with investigating subcortical sensory structures, current research on dyslexia in humans by-and-large focuses on the cerebral cortex. These studies found that dyslexia is typically associated with functional and structural alterations of a distributed left-hemispheric cerebral cortex network. However, findings from animal models and post-mortem studies in humans suggest that developmental dyslexia might also be associated with structural alterations in subcortical sensory pathways. Whether these alterations also exist in developmental dyslexia in-vivo and how they relate to dyslexia symptoms is currently unknown. Here we used ultra-high resolution structural magnetic resonance imaging (MRI), diffusion MRI and probabilistic tractography to investigate the structural connections of the visual sensory pathway in dyslexia in-vivo. We discovered that individuals with developmental dyslexia have reduced structural connections in the direct pathway between the left visual thalamus (LGN) and left middle temporal area V5/MT, but not between the left LGN and left primary visual cortex (V1). In addition, left V5/MT-LGN connectivity strength correlated with rapid naming abilities - a key deficit in dyslexia [14]. These findings provide the first evidence of specific structural alterations in the connections between the sensory thalamus and cortex in developmental dyslexia. The results challenge current standard models and provide novel evidence for the importance of cortico-thalamic interactions in explaining dyslexia.Comment: 31 pages, 5 figures, 2 table

Tensor Lines in Tensor Fields of Arbitrary Order: Tracking Lines in Higher Order Tensor Fields

This paper presents a method to reduce time complexity of the computation of higher–order tensor lines. The method can be applied to higher–order tensors and the spherical harmonics representation, both widely used in medical imaging. It is based on a gradient descend technique and integrates well into fiber tracking algorithms. Furthermore, the method improves the angular resolution in contrast to discrete sampling methods which is especially important to tractography, since there, small errors accumulate fast and make the result unusable. Our implementation does not interpolate derived directions but works directly on the interpolated tensor information. The specific contribution of this paper is a fast algorithm for tracking lines tensor fields of arbitrary order that increases angular resolution compared to previous approaches

Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS)

We introduce an algorithm for diffusion weighted magnetic resonance imaging data enhancement based on structural adaptive smoothing in both space and diffusion direction. The method, called POAS, does not refer to a specific model for the data, like the diffusion tensor or higher order models. It works by embedding the measurement space into a space with defined metric and group operations, in this case the Lie group of three-dimensional Euclidean motion SE(3). Subsequently, pairwise comparisons of the values of the diffusion weighted signal are used for adaptation. The position-orientation adaptive smoothing preserves the edges of the observed fine and anisotropic structures. The POAS-algorithm is designed to reduce noise directly in the diffusion weighted images and consequently also to reduce bias and variability of quantities derived from the data for specific models. We evaluate the algorithm on simulated and experimental data and demonstrate that it can be used to reduce the number of applied diffusion gradients and hence acquisition time while achieving similar quality of data, or to improve the quality of data acquired in a clinically feasible scan time setting

Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS)

We introduce an algorithm for diffusion weighted magnetic resonance imaging data enhancement based on structural adaptive smoothing in both space and diffusion direction. The method, called POAS, does not refer to a specific model for the data, like the diffusion tensor or higher order models. It works by embedding the measurement space into a space with defined metric and group operations, in this case the Lie group of three-dimensional Euclidean motion SE(3). Subsequently, pairwise comparisons of the values of the diffusion weighted signal are used for adaptation. The position-orientation adaptive smoothing preserves the edges of the observed fine and anisotropic structures. The POAS-algorithm is designed to reduce noise directly in the diffusion weighted images and consequently also to reduce bias and variability of quantities derived from the data for specific models. We evaluate the algorithm on simulated and experimental data and demonstrate that it can be used to reduce the number of applied diffusion gradients and hence acquisition time while achieving similar quality of data, or to improve the quality of data acquired in a clinically feasible scan time setting

Brain structure and function: a multidisciplinary pipeline to study hominoid brain evolution

To decipher the evolution of the hominoid brain and its functions, it is essential to conduct comparative studies in primates, including our closest living relatives. However, strong ethical concerns preclude in vivo neuroimaging of great apes. We propose a responsible and multidisciplinary alternative approach that links behavior to brain anatomy in non-human primates from diverse ecological backgrounds. The brains of primates observed in the wild or in captivity are extracted and fixed shortly after natural death, and then studied using advanced MRI neuroimaging and histology to reveal macro- and microstructures. By linking detailed neuroanatomy with observed behavior within and across primate species, our approach provides new perspectives on brain evolution. Combined with endocranial brain imprints extracted from computed tomographic scans of the skulls these data provide a framework for decoding evolutionary changes in hominin fossils. This approach is poised to become a key resource for investigating the evolution and functional differentiation of hominoid brains

Changes in the superior longitudinal fasciculus and anterior thalamic radiation in the left brain are associated with developmental dyscalculia

Developmental dyscalculia is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood lowering the individual’s quality of life. However, the neural correlates of developmental dyscalculia are poorly understood. This study aimed to identify brain structural connectivity alterations in developmental dyscalculia. All participants were recruited from a large scale, non-referred population sample in a longitudinal design. We studied 10 children with developmental dyscalculia (11.3 ± 0.7 years) and 16 typically developing peers (11.2 ± 0.6 years) using diffusion-weighted magnetic resonance imaging. We assessed white matter microstructure with tract-based spatial statistics in regions-of-interest tracts that had previously been related to math ability in children. Then we used global probabilistic tractography for the first time to measure and compare tract length between developmental dyscalculia and typically developing groups. The high angular resolution diffusion-weighted magnetic resonance imaging and crossing-fiber probabilistic tractography allowed us to evaluate the length of the pathways compared to previous studies. The major findings of our study were reduced white matter coherence and shorter tract length of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the developmental dyscalculia group. Furthermore, the lower white matter coherence and shorter pathways tended to be associated with the lower math performance. These results from the regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might be related to developmental dyscalculia in children

Segmentation d\u27images couleur par un opérateur gradient vectoriel multiéchelle et contour actif : application à la quantification des phases minéralogiques du clinker de ciment

L\u27objectif de cette thèse est la quantification des phases de clinker de ciment par analyse d\u27images couleur issues d\u27un microscope optique. La segmentation des cristaux a été abordée par une double démarche adaptée aux contraintes industrielles : La première porte sur une méthode originale de calcul du gradient couleur dans le cas des images acquises avec une camera couleur standard mono-CCD. Ces images multi-spectrales ont la particularité de présenter une résolution réduite des composantes couleur par rapport à celle de la luminosité. L\u27adaptation d\u27une approche multi-échelle et une pondération des composantes sont intégrée dans un nouvel opérateur de gradient couleur multi-échelle (GCM). Les études comparatives avec des techniques classiques, effectuées dans le cadre de la détection des contours, montrent la contribution du GCM. Le deuxième modèle original concerne la segmentation d\u27images par un contour déformable de type "ballon". Notre modèle stabilise la déformation par normalisation de la longueur du contour actif avant chaque itération. Ceci permet des grandes déformations du contour sans requérir le ré-échantillonnage de la courbe, étape nécessaire dans lapproche classique. Lalgorithme est plus rapide et plus robuste et autorise un contour initial loin du contour final.Le logiciel développé en partenariat avec la société Lafarge Ciments intègre ces différentes techniques de traitement d\u27image couleur : Pré-traitement des images, segmentation par approche contour effectuée à l\u27aide du GCM des images microscopiques couleur, une fermeture des contours. Les régions homogènes ainsi segmentées, sont ensuite classifiées grâce à des paramètres de texture et de couleur. Le système fourni une quantification des trois phases principales du clinker et une analyse statistique des dimensions des cristaux. Il remplace une mesure manuelle longue et fastidieuse et permet daugmenter la qualité de la fabrication par des mesures plus fréquentes en sortie du four à ciment

Segmentation d'images couleur par un opérateur gradient vectoriel multiéchelle et contour actif (application à la quantification des phases minéralogiques du clinker de cimen)

L'objectif de cette thèse est la quantification des phases de clinker de ciment par analyse d'images couleur issues d'un microscope optique. La segmentation des cristaux a été abordée par une double démarche adaptée aux contraintes industrielles : La première porte sur une méthode originale de calcul du gradient couleur dans le cas des images acquises avec une camera couleur standard mono-CCD. Ces images multi-spectrales ont la particularité de présenter une résolution réduite des composantes couleur par rapport à celle de la luminosité. L'adaptation d'une approche multi-échelle et une pondération des composantes sont intégrée dans un nouvel opérateur de gradient couleur multi-échelle (GCM). Les études comparatives avec des techniques classiques, effectuées dans le cadre de la détection des contours, montrent la contribution du GCM. Le deuxième modèle original concerne la segmentation d'images par un contour déformable de type "ballon". Notre modèle stabilise la déformation par normalisation de la longueur du contour actif avant chaque itération. Ceci permet des grandes déformations du contour sans requérir le ré-échantillonnage de la courbe, étape nécessaire dans l approche classique. L algorithme est plus rapide et plus robuste et autorise un contour initial loin du contour final.Le logiciel développé en partenariat avec la société Lafarge Ciments intègre ces différentes techniques de traitement d'image couleur : Pré-traitement des images, segmentation par approche contour effectuée à l'aide du GCM des images microscopiques couleur, une fermeture des contours. Les régions homogènes ainsi segmentées, sont ensuite classifiées grâce à des paramètres de texture et de couleur. Le système fourni une quantification des trois phases principales du clinker et une analyse statistique des dimensions des cristaux. Il remplace une mesure manuelle longue et fastidieuse et permet d augmenter la qualité de la fabrication par des mesures plus fréquentes en sortie du four à ciment.The objective of this thesis is the quantification of cement clinker phases by analysis of color images acquired with an optical microscope. The segmentation of the crystals is approached in a double way adapted to industrial constraints. The first introduces an orignal computation of the color gradient for images acquired with a standard mono-CCD color camera. These multispectral images have the particularity of a reduced resolution of color components compared to that of luminance. The adaptation of a multiscale approach and weighting of the components are integrated in a new multiscale color gradient (MCG) operator. Comparative studies with classical techniques in the domain of edge detection, show the contribution of the MCG. The second original model concerns image segmentation by deformable contours of balloon type. Our model stabilizes the deformation by normalizing the contour length at each iteration. This allows big deformations of the contour without re-sampling of the contour, which is necessary in the classical approach. The algorithm is faster, more robust and allows an initial contour which is far from the final contour. The software developed in partnership with the company Lafarge Ciments integrates the different color image processing techniques. Pre-processing of the images, segmentation by edge detection using the MCG of the microscopic color images and edge closing. The homogeneous regions segmentation in this way are classified using color and texture parameters. The system computes a quantification of the three clinker phases and a statistical analysis of the crystal dimensions. It replaces long and tiring manual measurements and allows a high quality production by more frequent measurements at the exit of the cement kiln.VILLEURBANNE-DOC'INSA LYON (692662301) / SudocSudocFranceF

Anatomical connectivity of temporal voice areas

The voice localizer sequence consists of 60 8-second blocks (16 bit, mono, 22050 Hz sampling rate), including 20 blocks of silence, 20 blocks of only human vocal sounds (speech and non-speech), and 20 blocks of only non-vocal sounds (industrial sounds, environmental sounds, animal vocalizations)

Deterministic and Probabilistic Tractography Based on Complex Fiber Orientation Distributions

accepted July 6th 2008, in pressInternational audienceWe propose an integral concept for tractography to describe crossing and splitting fibre bundles based on the fibre orientation distribution function (ODF) estimated from high angular resolution diffusion imaging (HARDI). We show that in order to perform accurate probabilistic tractography, one needs to use a fibre ODF estimation and not the diffusion ODF. We use a new fibre ODF estimation obtained from a sharpening deconvolution transform (SDT) of the diffusion ODF reconstructed from q-ball imaging (QBI). This SDT provides new insight into the relationship between the HARDI signal, the diffusion ODF, and the fibre ODF. We demonstrate that the SDT agrees with classical spherical deconvolution and improves the angular resolution of QBI. Another important contribution of this paper is the development of new deterministic and new probabilistic tractography algorithms using the full multidirectional information obtained through use of the fibre ODF. An extensive comparison study is performed on human brain datasets comparing our new deterministic and probabilistic tracking algorithms in complex fibre crossing regions. Finally, as an application of our new probabilistic tracking, we quantify the reconstruction of transcallosal fibres intersecting with the corona radiata and the superior longitudinal fasciculus in a group of eight subjects. Most current diffusion tensor imaging (DTI)-based methods neglect these fibres, which might lead to incorrect interpretations of brain functions