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Bihan-Poudec, Y.

Publications and source records attributed to Bihan-Poudec, Y..

3 recordsLinked to original sources

Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

neuroscience↗

A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI : an application to the ventriclar junctions

BackgroundKnowledge of the normal myocardial-myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented. MethodsThree explanted sheep (ovine) hearts (size ~12x8x6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy ...) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template. ResultsThe template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 m and 600 m respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition. ConclusionsA new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.

biophysics↗

Prefrontal attentional saccades explore space at an alpha rhythm

Recent studies suggest that attention samples space rhythmically through oscillatory interactions in the frontoparietal network. However, the precise mechanism through which the prefrontal cortex, at the source of attention control signals, organizes this rhythmic exploration of space remains unknown. We show that, when decoded at a high spatial (0.1{degrees}) and temporal resolution (50ms), the prefrontal covert attentional spotlight, aka the minds eye, continuously explores space at an alpha 7-12 Hz rhythm. When sensory events are presented at a specific optimal phase (resp. anti-phase) with respect to this rhythm, sensory encoding and behavioral report are accurate (resp. poor). We propose that this rhythmic prefrontal attentional spotlight dynamics corresponds to a continuous overt exploration of space via alpha-clocked attentional saccades. These attentional saccades are highly flexible, their pattern of space exploration depending both on within-trial and across-task contingencies. These results are discussed in the context of exploration and exploitation strategies and prefrontal top-down attentional control.\n\nHighlightsO_LIThe decoded prefrontal attentional spotlight samples visual space in rhythmic cycles\nC_LIO_LIThis rhythmic attentional exploration predicts neuronal sensory processing accuracy\nC_LIO_LIThis rhythmic attentional exploration predicts overt behavioral accuracy\nC_LIO_LIThese rhythmic cycles define alpha-clocked attentional saccades\nC_LIO_LISpace exploration by attentional saccades is highly flexible and under top-down control\nC_LI

neuroscience↗