Study of the brain connectivity in an Immersive Space

National audienceVirtual reality is a powerful tool for scientific visualization. When the amount and complexity of the visualized data grows, standard visualization applications on desktop computers become inefficient. In this paper we present the use of a CAVE like VR facility in a neuroscientific context. The aim is to have a better understanding of the brain connectivity. Both anatomical and functional data are attached to a mesh representing the brain surface. Specific tools developed for this study and the way we used them are presented below, emphasizing drawbacks and advantages of virtual reality in a scientific visualization context

Tract-based statistical analyzes in dMRI in autism spectrum disorder

International audienceIntroduction Recent studies show an atypical perceptive behavior on face processing in autism. Functional studies show that the fusiform gyrus is involved in face perception and is not or less activated in autistic subjects [1]. These face processing is believed to affect social interaction, which can be quantified by ADOS scores and related to the functionality of the prefrontal cortex. The aim of this study is to quantify anatomical changes in autistic subjects on the white matter tracts that traverse the fusiform gyrus, the prefrontal cortex and the superior temporal gyrus and correlate them with ADOS scores to complete. In this study, we first verified the connectivity difference between the fusiform gyrus, the prefrontal cortex and the superiotemporal gyrus through fMRI. Then, we used Diffusion Tensor MRI (DT) images to assess the integrity of automatically segmented white matter bundles connecting these girii. Finally, we perform statistical analysis on these fiber bundles using diffusivity measures calculated from DT to characterize tissue microstructure changes and correlate these changes with ADOS scores. Materials and methods Data acquisition. We acquired dMRI of eight adults with high-functioning autism or Asperger syndrome and eleven healthy adults at the University of Buenos Aires on a GE Signa Hdxt 3.0T scanner. The acquisition consisted in 80 directions with b=1000s/mm2 and 1 image with b=0s/mm2 with 1×1×1.3mm voxel size. Data preparation. We started by generating an unbiased template of the DT images and registering linearly and non-linearly all of the images to it. Then, we computed DT-based full brain tractography for every subject. Finally, we used the tools developed by Wassermann et al [2] to cluster fiber bundles and select the bundles traversing the fusiform gyrus. This gyrus was identified through the girii parcelation of the JHU atlas. We clustered these bundles across subjects extracting a set of population-obtained bundles (see for Fig 1 for an example). Data analysis. We applied the statistical analysis of Wassermann et al [3] for each population-obtained bundle, we calculated its tract-probability map (TPM) (see Fig.3 for an example) and skeletonized this map to obtain a bidimensional representation of each bundle. For each patient, we projected the measure of diffusivity (FA, axial or radial diffusivity) around the tract to their closest point on the skeleton and we average them with a weight according to the TPM. This produces two populations (one for autists and one for controls) of projected functions on the skeleton. For each tract and each measure, we used a cluster-based permutation hypothesis testing approach [4] to detect dissimilarities between both populations. For significant clusters, we calculated correlation between the mean diffusivity measure and ADOS scores. Results We found different clusters (Fig 1, red voxels) where there were dissimilarities between autistic and healthy subjects in FA measures on tracts traversing the fusiform gyrus in both hemispheres of the brain. We observed a reduction of FA values in a cluster (Fig 2, red voxels) on a bundle joined the superior temporal gyrus to the prefrontal cortex. In this cluster, the mean FA on the autistic subjects was strongly correlated with their scores to ADOS social interaction with a correlation coefficient lower than -0.96 a p-value lower than 0.004 (Fig3). Discussion First, results revealing difference between controls and autists in clusters on fiber bundle traversing the fusiform gyrus are in agreement with current literature giving this area as a classical area of face perception. Agreement reinforced by functional study of autists showing a drop of connectivity between the fusiform gyrus and the superior temporal cortex in comparison with controls (Fig 4). The localisation of the cluster where we founded a correlation with ADOS social interaction scores (Fig3) is in agreement with current anatomical literature, the superior temporal gyrus being a classical area of face perception and emotion and the prefrontal cortex a classical area of social interaction. This is reinforced by the strong inverse correlation showing that in this linking cluster a drop of FA value is strongly correlated by a rise of the intensity of autism. Our fMRI study (Fig 4) corroborates these statistical results, showing a drop of connectivity between the prefrontal cortex and the superior temporal gyrus. Disruption of white matter tracts between regions implicated in social functioning and face perception may contribute to increase the severity of autism

Validation of material models for inter and intra-laminar damage in laminated composites

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Tractography via the Ensemble Average Propagator in diffusion MRI

International audienceIt's well known that in diffusion MRI (dMRI), fibre crossing is an important problem for most existing diffusion tensor imaging (DTI) based tractography algorithms. To overcome these limitations, High Angular Resolution Diffusion Imaging (HARDI) based tractography has been proposed with a particular emphasis on the the Orientation Distribution Function (ODF). In this paper, we advocate the use of the Ensemble Average Propagator (EAP) instead of the ODF for tractography in dMRI and propose an original and efficient EAP-based tractography algorithm that outperforms the classical ODF-based tractography, in particular, in the regions that contain complex fibre crossing configurations. Various experimental results including synthetic, phantom and real data illustrate the potential of the approach and clearly show that our method is especially efficient to handle regions where fiber bundles are crossing, and still well handle other fiber bundle configurations such as U-shape and kissing fibers

Diffusion Magnetic Resonance information as a regularization term for MEG/EEG inverse problem

International audienceSeveral regularization terms are used to constrain the Magnetoencephalography (MEG) and the Electroencephalography (EEG) inverse problem. It has been shown that the brain can be divided into several regions[1] with functional homogeneity inside each one of them. To locate these regions, we use the structural information coming from the diffusion Magnetic Resonance (dMRI) and more specifically, the anatomical connectivity of the distributed sources computed from dMRI. To invistigate the importance of the dMRI in the source reconstruction, we compare the solution based on dMRI-based parcellation to random parcellation

Tract-based statistical analyzes in dMRI in autism spectrum disorder

International audienceIntroduction Recent studies show an atypical perceptive behavior on face processing in autism. Functional studies show that the fusiform gyrus is involved in face perception and is not or less activated in autistic subjects [1]. These face processing is believed to affect social interaction, which can be quantified by ADOS scores and related to the functionality of the prefrontal cortex. The aim of this study is to quantify anatomical changes in autistic subjects on the white matter tracts that traverse the fusiform gyrus, the prefrontal cortex and the superior temporal gyrus and correlate them with ADOS scores to complete. In this study, we first verified the connectivity difference between the fusiform gyrus, the prefrontal cortex and the superiotemporal gyrus through fMRI. Then, we used Diffusion Tensor MRI (DT) images to assess the integrity of automatically segmented white matter bundles connecting these girii. Finally, we perform statistical analysis on these fiber bundles using diffusivity measures calculated from DT to characterize tissue microstructure changes and correlate these changes with ADOS scores. Materials and methods Data acquisition. We acquired dMRI of eight adults with high-functioning autism or Asperger syndrome and eleven healthy adults at the University of Buenos Aires on a GE Signa Hdxt 3.0T scanner. The acquisition consisted in 80 directions with b=1000s/mm2 and 1 image with b=0s/mm2 with 1×1×1.3mm voxel size. Data preparation. We started by generating an unbiased template of the DT images and registering linearly and non-linearly all of the images to it. Then, we computed DT-based full brain tractography for every subject. Finally, we used the tools developed by Wassermann et al [2] to cluster fiber bundles and select the bundles traversing the fusiform gyrus. This gyrus was identified through the girii parcelation of the JHU atlas. We clustered these bundles across subjects extracting a set of population-obtained bundles (see for Fig 1 for an example). Data analysis. We applied the statistical analysis of Wassermann et al [3] for each population-obtained bundle, we calculated its tract-probability map (TPM) (see Fig.3 for an example) and skeletonized this map to obtain a bidimensional representation of each bundle. For each patient, we projected the measure of diffusivity (FA, axial or radial diffusivity) around the tract to their closest point on the skeleton and we average them with a weight according to the TPM. This produces two populations (one for autists and one for controls) of projected functions on the skeleton. For each tract and each measure, we used a cluster-based permutation hypothesis testing approach [4] to detect dissimilarities between both populations. For significant clusters, we calculated correlation between the mean diffusivity measure and ADOS scores. Results We found different clusters (Fig 1, red voxels) where there were dissimilarities between autistic and healthy subjects in FA measures on tracts traversing the fusiform gyrus in both hemispheres of the brain. We observed a reduction of FA values in a cluster (Fig 2, red voxels) on a bundle joined the superior temporal gyrus to the prefrontal cortex. In this cluster, the mean FA on the autistic subjects was strongly correlated with their scores to ADOS social interaction with a correlation coefficient lower than -0.96 a p-value lower than 0.004 (Fig3). Discussion First, results revealing difference between controls and autists in clusters on fiber bundle traversing the fusiform gyrus are in agreement with current literature giving this area as a classical area of face perception. Agreement reinforced by functional study of autists showing a drop of connectivity between the fusiform gyrus and the superior temporal cortex in comparison with controls (Fig 4). The localisation of the cluster where we founded a correlation with ADOS social interaction scores (Fig3) is in agreement with current anatomical literature, the superior temporal gyrus being a classical area of face perception and emotion and the prefrontal cortex a classical area of social interaction. This is reinforced by the strong inverse correlation showing that in this linking cluster a drop of FA value is strongly correlated by a rise of the intensity of autism. Our fMRI study (Fig 4) corroborates these statistical results, showing a drop of connectivity between the prefrontal cortex and the superior temporal gyrus. Disruption of white matter tracts between regions implicated in social functioning and face perception may contribute to increase the severity of autism

Using diffusion MRI information in the Maximum Entropy on Mean framework to solve MEG/EEG inverse problem

International audienceMagnetoencephalography (MEG) and Electroencephalography (EEG) inverse problem is well-known to require regularization to avoid ill-posedness. Usually, regularization is based on mathematical criteria (minum norm, ...). Physiologically, the brain is organized in functional parcels and imposing a certain homogeneity of the activity within these parcels was proven to be an efficient way to analyze the MEG/EEG data [1][6]. The parcels information can be computed from diffusion Magnetic Resonances Imaging (dMRI) by grouping together source positions shared the same connectivity profile (computed as tractograms from diffusion images). In this work, three parcel-based inverse problem approaches have been tested. The first two approaches are based on minimum norm with added regularization terms to account for the parcel information. They differ by the use of a hard/soft constraint in the way they impose that the activity is constant within each parcel [4]. The third approach is based on the Maximum Entropy on Mean (MEM) framework [2]. The dMRI-base and random cortex parcellation, we test also the use of Multivariate Source Pre-localization (MSP) [5] in the source reconstruction

Propagation of epileptic spikes revealed by diffusion-based constrained MEG source reconstruction

International audienceGoal: Study of the propagation of an epileptic spike. Method: 1- cortex parcellation via structural information coming from diffusion MRI (dMRI) 2- MEG inverse problem on a parcellated source space 3- study of the propagation of an epileptic spike via the active parcels Results on real data allowing to study the spatial propagation of an epileptic spike

Immunization Route Dictates Cross-Priming Efficiency and Impacts the Optimal Timing of Adjuvant Delivery

Delivery of cell-associated antigen represents an important strategy for vaccination. While many experimental models have been developed in order to define the critical parameters for efficient cross-priming, few have utilized quantitative methods that permit the study of the endogenous repertoire. Comparing different strategies of immunization, we report that local delivery of cell-associated antigen results in delayed T cell cross-priming due to the increased time required for antigen capture and presentation. In comparison, delivery of disseminated antigen resulted in rapid T cell priming. Surprisingly, local injection of cell-associated antigen, while slower, resulted in the differentiation of a more robust, polyfunctional, effector response. We also evaluated the combination of cell-associated antigen with poly I:C delivery and observed an immunization route-specific effect regarding the optimal timing of innate immune stimulation. These studies highlight the importance of considering the timing and persistence of antigen presentation, and suggest that intradermal injection with delayed adjuvant delivery is the optimal strategy for achieving CD8+ T cell cross-priming