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The structural connectivity of animal brains can be revealed using post-mortem diffusion-weighted magnetic resonance imaging (MRI). Despite the existence of several structural atlases of avian brains, few of them address the bird’s structural connectivity. In this study, a novel atlas of the structural connectivity is proposed for the male Japanese quail (Coturnix japonica), aiming at investigating two lines divergent on their emotionality trait: the short tonic immobility (STI) and the long tonic immobility (LTI) lines. The STI line presents a low emotionality trait, while the LTI line expresses a high emotionality trait. 21 male Japanese quail brains from both lines were scanned post-mortem for this study, using a preclinical Bruker 11.7 T MRI scanner. Diffusion-weighted MRI was performed using a 3D segmented echo planar imaging (EPI) pulsed gradient spin-echo (PGSE) sequence with a 200 $$\upmu$$μm isotropic resolution, 75 diffusion-encoding directions and a b-value fixed at 4500 s/mm2. Anatomical MRI was likewise performed using a 2D anatomical T2-weighted spin-echo (SE) sequence with a 150 $$\upmu$$μm isotropic resolution. This very first anatomical connectivity atlas of the male Japanese quail reveals 34 labeled fiber tracts and the existence of structural differences between the connectivity patterns characterizing the two lines. Thus, the link between the male Japanese quail’s connectivity and its underlying anatomical structures has reached a better understanding.

We present a new framework for the creation of an extended atlas of short fiber bundles between 20 and 80 mm length. This method uses a Diffeomorphic inter-subject alignment procedure including information of cortical foldings and forces the accurate match of the sulci that have to be circumvented by the U-bundles. Then, a clustering is performed to extract the most reproducible bundles across subjects. First results show an increased number of U-bundles consistently mapped in the general population compared with previous atlases created from the same database. Future analysis over this new extended Brain atlas may improve our understanding of the relationship between the folding pattern and the U-bundle variability. The ultimate aim will be the possibility to detect abnormal configurations induced by developmental issues.

International audience; Robust spatial alignment of post mortem data and in vivo MRI acquisitions from different ages, especially from the early developmental stages, into standard spaces is still a bottleneck hampering easy comparison with the mainstream neuroimaging results. In this paper, we test a landmark-based spatial normalization strategy as a framework for the seamless integration of any macroscopic dataset in the context of the Human Brain Project 30 (HBP). This strategy stems from an approach called DISCO embedding sulcal constraints in a registration framework used to initialize DARTEL, the widely used spatial normalization approach proposed in the SPM software. We show that this strategy is efficient with a heterogeneous dataset including challenging data as preterm newborns, infants, post mortem histological data and a synthetic atlas computed from averaging the ICBM database, as well as more commonly studied data acquired in vivo in adults. We then describe some perspectives 35 for a research program aiming at improving folding pattern matching for atlas inference in the context of the future HBP's portal.

Diffeomorphic registration of diffusion MRI data is a non-convex optimization problem which raises issues both with respect to the choice of a model describing the dMRI data and the associated optimization method used to warp non-scalar images obtained from this model. In this paper, we take into account the full information available from the diffusion-weighted signal by using the local SHORE Mean Apparent Propagator (MAP) model. A discrete representation of the SHORE MAPs on a multiple-shell sampling of the displacement space is introduced, simplifying the comparison between MAPs which are no longer in different local tensor frames and enabling to perform a complete reorientation of the MAPs at each step of the registration. The diffeomorphic transformation is first optimized at the voxel scale using dynamic programming on a minimum spanning tree before taking advantage of the continuous diffeomorphic demons registration algorithm to match dMRI data at finer scales. The efficacy of this registration approach was assessed using diffusion MR datasets acquired on two healthy subjects to evaluate its capability to reach an optimal alignment of several well-known long white matter bundles.

Brain structure & function 223(5), 2157-2179 (2018). doi:10.1007/s00429-018-1617-1, Published by Springer, Berlin ; Heidelberg

Objectives The goal of this work was to investigate iron deposition in the basal ganglia and thalamus in symptomatic and asymptomatic leucine-rich repeat kinase 2 (LRRK2) and Parkin-associated Parkinson's disease (PD), using R2* relaxometry rate. Methods Twenty subjects with genetic PD (four symptomatic and two asymptomatic Parkin subjects, nine symptomatic and five asymptomatic LRRK2 subjects) were compared with 20 patients with idiopathic PD (IPD) and 20 healthy subjects. Images were obtained at 3 teslas, using multi-echo T2 and T2* sequences. R2 and R2* values were calculated in the substantia nigra (SN), the striatum, the globus pallidus, and the thalamus. Results The R2* values in the SN were increased in IPD and mutation-carrying patients as compared with controls and in mutation-carrying patients as compared with IPD. Asymptomatic mutation carriers showed higher R2* values than controls and did not differ from IPD patients. No changes were seen in the other structures or in R2 values. Conclusion These results are consistent with increased iron load in LRRK2- and Parkin-mutation carriers. The increased R2* in asymptomatic PD-mutation carriers suggests that iron deposition occurs early during the preclinical phase of the disease. R2* measurements may be used as markers for investigating nigrostriatal damage in preclinical mutation-carrying patients. © 2015 International Parkinson and Movement Disorder Society

Tractography from diffusion-weighted MRI (DWI) has revolutionized the brain connectivity investigation in vivo but still lack of anatomical tools to overcome controversial situations and to investigate the fibers reconstruction within gyri. In this work, we propose a non-generative global spin-glass tractography approach using anatomical priors to constrain the tracking process by integrating the pial surface knowledge to manage sharp turns of fibers approaching the cortical mantel according to its normal direction. The optimum configuration is obtained using a stochastic optimization of the global framework energy, resulting from a trade-off between a first term measuring the discrepancy between the spin glass directions and the underlying field of orientation distribution functions (ODF) or mean apparent propagators (MAP) estimated from the DWI data, and a second term related to the curvature of the generated fibers. The method was tested on a synthetic \(90^{\circ }\) crossing phantom and on a real brain postmortem sample.

In this work, we investigated the link between the blood-oxygen-level dependant (BOLD) effect observed using functional magnetic resonance imaging (fMRI) and the neurite density inferred from the Neurite Orientation Dispersion and Density Imaging (NODDI) model in some well-known lateralized cortical areas. We found a strong colocalization between those two parameters in lateralized areas such as the primary motor cortex, the language network, but also the primary visual cortex, which might indicate a strong link between microstructure and functional activity.

We present new diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models. The phantom design permits the application of imaging parameters that are typically employed in studies of the human brain. The phantoms were made of small-diameter acrylic fibers, chosen for their high hydrophobicity and flexibility that ensured good control of the phantom geometry. The polyurethane medium was filled under vacuum with an aqueous solution that was previously degassed, doped with gadolinium-tetraazacyclododecanetetraacetic acid (Gd-DOTA), and treated by ultrasonic waves. Two versions of such phantoms were manufactured and tested. The phantom's applicability was demonstrated on an analytical Q-ball model. Numerical simulations were performed to assess the accuracy of the phantom. The phantom data will be made accessible to the community with the objective of analyzing various HARDI models.

Diffusion magnetic resonance imaging (dMRI) has become an established research tool for the investigation of tissue structure and orientation. In this paper, we present a method for real-time processing of diffusion tensor and Q-ball imaging. The basic idea is to use Kalman filtering framework to fit either the linear tensor or Q-ball model. Because the Kalman filter is designed to be an incremental algorithm, it naturally enables updating the model estimate after the acquisition of any new diffusion-weighted volume. Processing diffusion models and maps during ongoing scans provides a new useful tool for clinicians, especially when it is not possible to predict how long a subject may remain still in the magnet. First, we introduce the general linear models corresponding to the two diffusion tensor and analytical Q-ball models of interest. Then, we present the Kalman filtering framework and we focus on the optimization of the diffusion orientation sets in order to speed up the convergence of the online processing. Last, we give some results on a healthy volunteer for the online tensor and the Q-ball model, and we make some comparisons with the conventional offline techniques used in the literature. We could achieve full real-time for diffusion tensor imaging and deferred time for Q-ball imaging, using a single workstation.

International audience; The fine spatial resolution and novel contrasts offered by high-field magnetic resonance allow in vivo detection of histological layers in the cerebral cortex. This opens the way to in vivo analysis of cortical lamination, but the comparison of lamination profiles has proved challenging because the layers’ geometry is strongly influenced by cortical curvature. This paper introduces a model of the micro-structural organization of the cortex, which can compensate for the effect of cortical curvature. Layers are modelled by an equivolumic principle, while the vertical structure of the cortex is represented with a Laplacian model. In this framework, lamination profiles can be represented in a way that preserves the original voxel sampling of the acquisition. This model is validated on a magnetic resonance image of a post-mortem human brain acquired on a human 7 T scanner at 0.35 mm resolution.

The goal of this work was to investigate iron deposition in the basal ganglia and thalamus in symptomatic and asymptomatic leucine-rich repeat kinase 2 (LRRK2) and Parkin-associated Parkinson's disease (PD), using R2* relaxometry rate.Twenty subjects with genetic PD (four symptomatic and two asymptomatic Parkin subjects, nine symptomatic and five asymptomatic LRRK2 subjects) were compared with 20 patients with idiopathic PD (IPD) and 20 healthy subjects. Images were obtained at 3 teslas, using multi-echo T2 and T2* sequences. R2 and R2* values were calculated in the substantia nigra (SN), the striatum, the globus pallidus, and the thalamus.The R2* values in the SN were increased in IPD and mutation-carrying patients as compared with controls and in mutation-carrying patients as compared with IPD. Asymptomatic mutation carriers showed higher R2* values than controls and did not differ from IPD patients. No changes were seen in the other structures or in R2 values.These results are consistent with increased iron load in LRRK2- and Parkin-mutation carriers. The increased R2* in asymptomatic PD-mutation carriers suggests that iron deposition occurs early during the preclinical phase of the disease. R2* measurements may be used as markers for investigating nigrostriatal damage in preclinical mutation-carrying patients.

Object. High-frequency stimulation of the subthalamic nucleus (STN) is effective for treating refractory idiopathic Parkinson disease (PD). In stereotactic conditions magnetic resonance (MR) imaging is used by many teams to perform preoperative targeting of the STN. The goal of this study was to analyze and correct the geometrically observed MR imaging acquisitions used for targeting of the STN. Methods. A dedicated phantom of known geometry was used. The authors calculated existing shifts between measured points and theoretically defined points on the same T1- and T2-weighted sequences used to target the STN. A shifting volume was built to correct the phantom images and images acquired preoperatively in 13 patients with PD. A quantitative study of the correction was conducted using the phantom images and acquisitions acquired in these patients. To quantify the distortion corrections, the authors segmented the lateral ventricles and calculated the overlap of the corrected and uncorrected values between T1 and T2 segmentation. The authors found that the distortions were greater in the direction of slice selection and frequency encoding and weaker on three-dimensional T1-weighted acquisitions. On T2-weighted acquisitions, the maximum shifts were 2.19 mm in the frequency-encoding direction and 3.81 mm in slice selection. The geometrical distortion was significantly reduced and smaller than pixel size after distortion correction. Assessment of the patients' scans showed that the mean ventricular overlap was 76% before and 94% after correction. Conclusions. The authors found that significant distortions can be observed on T2-weighted images used to demonstrate the STN. These distortions can be corrected using appropriate software.

International audience; The present study aimed at determining the three-dimensional organization of striatal activation during foot, hand, face and eye movements. Seven right-handed, healthy volunteers were studied at 1.5 T using blood oxygen level dependent (BOLD) contrast. The tasks consisted of self-paced flexion/extension of the right and left fingers and right toes, contraction of the lips and saccadic eye movements. For foot, hand and face movements, striatal activation was mainly found in the putamen with a somatotopical organization, the foot area being dorsal, the face area more ventral and medial, the hand area in between. Overlap between somatotopic territories was present, more prominent for hand-face than for foot-face or foot-hand areas. In the putamen, the activated areas of the ipsi- and contralateral hand areas were not identical, suggesting a partial segregation of the ipsi- and contralateral striatal sensorimotor projections. For saccadic eye movements, bilateral activation was observed at the junction between the body and the head of the caudate nucleus and in the right putamen. These data present evidence for a somatotopic organization of the human striatum which corresponds with the topography of corticostriatal projections described in the non-human primates.

See Jackson (doi:10.1093/brain/awu338) for a scientific commentary on this article. The neural substrate of Gilles de la Tourette syndrome is unknown. Worbe et al. use probabilistic tractography to demonstrate widespread structural abnormalities in cortico-striato-pallido-thalamic white matter pathways—likely arising from abnormal brain development—in patients with this syndrome., Gilles de la Tourette syndrome is a childhood-onset syndrome characterized by the presence and persistence of motor and vocal tics. A dysfunction of cortico-striato-pallido-thalamo-cortical networks in this syndrome has been supported by convergent data from neuro-pathological, electrophysiological as well as structural and functional neuroimaging studies. Here, we addressed the question of structural integration of cortico-striato-pallido-thalamo-cortical networks in Gilles de la Tourette syndrome. We specifically tested the hypothesis that deviant brain development in Gilles de la Tourette syndrome could affect structural connectivity within the input and output basal ganglia structures and thalamus. To this aim, we acquired data on 49 adult patients and 28 gender and age-matched control subjects on a 3 T magnetic resonance imaging scanner. We used and further implemented streamline probabilistic tractography algorithms that allowed us to quantify the structural integration of cortico-striato-pallido-thalamo-cortical networks. To further investigate the microstructure of white matter in patients with Gilles de la Tourette syndrome, we also evaluated fractional anisotropy and radial diffusivity in these pathways, which are both sensitive to axonal package and to myelin ensheathment. In patients with Gilles de la Tourette syndrome compared to control subjects, we found white matter abnormalities in neuronal pathways connecting the cerebral cortex, the basal ganglia and the thalamus. Specifically, striatum and thalamus had abnormally enhanced structural connectivity with primary motor and sensory cortices, as well as paracentral lobule, supplementary motor area and parietal cortices. This enhanced connectivity of motor cortex positively correlated with severity of tics measured by the Yale Global Tics Severity Scale and was not influenced by current medication status, age or gender of patients. Independently of the severity of tics, lateral and medial orbito-frontal cortex, inferior frontal, temporo-parietal junction, medial temporal and frontal pole also had enhanced structural connectivity with the striatum and thalamus in patients with Gilles de la Tourette syndrome. In addition, the cortico-striatal pathways were characterized by elevated fractional anisotropy and diminished radial diffusivity, suggesting microstructural axonal abnormalities of white matter in Gilles de la Tourette syndrome. These changes were more prominent in females with Gilles de la Tourette syndrome compared to males and were not related to the current medication status. Taken together, our data showed widespread structural abnormalities in cortico-striato-pallido-thalamic white matter pathways in patients with Gilles de la Tourette, which likely result from abnormal brain development in this syndrome.

The striatum including the caudate and putamen nuclei is involved in numerous functional tasks. It ensures senso-rimotor, associative and limbic functions supported by sensorimo-tor, associative and limbic sub-territories directly connected to the cortex and that may overlap. Damage to the striatum results in movement disorders like in Parkinson's disease or Huntington's disease. In this study, we propose to measure the proportion of each associative, limbic and sensorimotor subterritory inside each nucleus of the striatum using its connectivity to homologeous cortical regions. We then compare these proportions between healthy subjects and Huntington patients in order to better characterize the distribution of the atrophy inside each of the striatum nuclei.

L'essor des techniques d'imagerie fonctionnelle depuis une quinzaine d'annees a profondement modifie la maniere d'aborder la cartographie fonctionnelle du cerveau humain. Il a conduit a l'emergence de vastes projets confrontes a la manipulation d'enormes quantites de donnees anatomo-fonctionnelles. Ces projets impliquent la possibilite de comparer des individus et de thesauriser les resultats obtenus en matiere de localisation anatomique par rapport a un referentiel.

We propose a novel real-time non central χ (nc-χ) noise correction method for diffusion-weighted MR data that are known to be particularly sensitive to noise, especially at high b-values. This technique aims to be real-time during the acquisition to get any map stemming from the Diffusion Tensor Imaging (DTI) and the High Angular Resolution Diffusion Imaging (HARDI) models corrected from nc-χ noise. The method is based on a Parallel Kalman Filter which is well adapted for non-Gaussian noise distributions, and which is as suitable for real time purposes as the standard Kalman filter (KF). The results on simulated and real HARDI data show that it outperforms the standard KF approach since non-Gaussian noise distributions are directly embedded in the process through their Gaussian mixture approximation.

Parallel MRI leads to magnitude data corrupted by noise described in most cases as following a Rician or a non central chi distribution. And yet, very few correction methods perform a non central chi noise removal. However, this correction step, adapted to the correct noise model, is of very much importance, especially when working with Diffusion Weighted MR data yielding a low SNR. We propose an extended Linear Minimum Mean Square Error estimator (LMMSE), which is adapted to deal with non central chi distributions. We demonstrate on simulated and real data that the extended LMMSE outperforms the original LMMSE on images corrupted by a non central chi noise.

The deep brain nuclei play an important role in many brain functions and particularly motor control. Damage to these structures result in movement disorders such as in Parkinson's disease or Huntington's disease, or behavioural disorders such as Tourette syndrome. In this paper, we propose to study the connectivity profile of the deep nuclei to the motor, associative or limbic areas and we introduce a novel tool to build a probabilistic atlas of these connections to the cortex directly on the surface of the cortical mantel, as it corresponds to the space of functional interest. The tool is then applied on two populations of healthy volunteers and patients suffering from severe Huntington's disease to produce two surface atlases of the connectivity of the basal ganglia to the cortical areas. Finally, robust statistics are used to characterize the differences of that connectivity between the two populations, providing new connectivity-based biomarkers of the pathology.

In this paper we propose a new hybrid segmentation approach of the deep brain structures based on a multi-contrast deformable model of regions in competition, with deformations preserving the topology of the structures, as well as their shape and position, using a probabilistic atlas and some prior morphological information. The accuracy of our method was evaluated by comparing the results obtained on a base of T 1 -weighted data contrast with those of FREESURFER and FSL-FIRST. Besides giving very good results from only one contrast, we show that the multi-contrast aspect of our method allows exploiting the complementary contributions of different contrasts, like T 1 and diffusion tensor (DT) contrasts, in order to provide a more robust segmentation.

The deep brain nuclei play an important role in many brain functions and particularly motor control. Damage to these structures result in movement disorders such as in Parkinson's disease or Huntington's disease, or behavioural disorders such as Tourette syndrome. In this paper, we propose to study the connectivity profile of the deep nuclei to the motor, associative or limbic areas and we introduce a novel tool to build a probabilistic atlas of these connections to the cortex directly on the surface of the cortical mantel, as it corresponds to the space of functional interest. The tool is then applied on two populations of healthy volunteers and patients suffering from severe Huntington's disease to produce two surface atlases of the connectivity of the basal ganglia to the cortical areas. Finally, robust statistics are used to characterize the differences of that connectivity between the two populations, providing new connectivity-based biomarkers of the pathology.

The choice of local HARDI reconstruction technique is crucial for discerning multiple fiber orientations, which is itself of substantial importance for tractography, and reliable and accurate assessment of white matter fiber geometry. Due to the complexity of the diffusion process and its milieu, distinct diffusion compartments can have different frequency signatures, making the HARDI signal spread over multiple frequency bands. Therefore, we put forth the idea of multiscale analysis with localized basis functions, ensuring that different frequency ranges are probed. With the aim of truthful recovery of fiber orientations, we reconstruct the orientation distribution function (ODF), by incorporating a spherical wavelet transform (SWT) into the Funk–Radon transform. First, we apply and validate our proposed SWT method on real physical phantoms emulating fiber bundle crossings. Then, we apply the SWT method to a real brain data set. The analysis of the real data set suggests that different angular frequencies may capture different information, thus stressing the importance of multiscale analysis. For both phantom and real data, we compare the SWT reconstruction with state-of-the-art q-ball imaging and spherical deconvolution reconstruction methods. We demonstrate the algorithm efficiency in diffusion ODF denoising and sharpening that is of particular importance for applications to fiber tracking (especially for probabilistic approaches), and brain connectome mapping. Also, the algorithm results in considerable data compression that could prove beneficial in applications to fiber bundle segmentation, and for HARDI based white matter morphometry methods.

We present new diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models. The phantom design permits the application of imaging parameters that are typically employed in studies of the human brain. The phantoms were made of small-diameter acrylic fibers, chosen for their high hydrophobicity and flexibility that ensured good control of the phantom geometry. The polyurethane medium was filled under vacuum with an aqueous solution that was previously degassed, doped with gadolinium-tetraazacyclododecanetetraacetic acid (Gd-DOTA), and treated by ultrasonic waves. Two versions of such phantoms were manufactured and tested. The phantom's applicability was demonstrated on an analytical Q-ball model. Numerical simulations were performed to assess the accuracy of the phantom. The phantom data will be made accessible to the community with the objective of analyzing various HARDI models.

The idea underpinning the work we present herein is to design robust and objective tools for brain white matter (WM) morphometry. We focus on WM tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (HARDI). The definition of the tract mean line derives directly from the geometry of the tract fibres. We determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average HARDI models along the tract mean lines. This way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.