62 research outputs found

    Data-science ready, multisite, human diffusion MRI whitematter- tract statistics

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    Published 30 November 2020The white matter tracts in the living human brain are critical for healthy function, and the diffusion MRI measured in these tracts is correlated with diverse behavioral measures. The technical skills required to analyze diffusion MRI data are complex: data acquisition requires MRI sequence development and acquisition expertise, analyzing raw-data into meaningful summary statistics requires computational neuroimaging and neuroanatomy expertise. The human white matter study field will advance faster if the tract summaries are available in plain data-science-ready format for non-diffusion MRI experts, such as statisticians, computer graphic researchers or data scientists in general. Here, we share a curated and processed dataset from three different MRI centers in a format that is data-science ready. The multisite data we share include measures of within and between MRI center variation in white-matter-tract diffusion measurements. Along with the dataset description and summary statistics, we describe the state-of-the-art computational system that guarantees reproducibility and provenance from the original scanner output.This work was supported by a Marie Sklodowska-Curie (H2020-MSCA-IF-2017-795807-ReCiModel) grant to G.L.-U. We thank the Simons Foundation Autism Research Initiative and Weston Havens foundation for support

    The Encoding of Temporally Irregular and Regular Visual Patterns in the Human Brain

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    In the work reported here, we set out to study the neural systems that detect predictable temporal patterns and departures from them. We used functional magnetic resonance imaging (fMRI) to locate activity in the brains of subjects when they viewed temporally regular and irregular patterns produced by letters, numbers, colors and luminance. Activity induced by irregular sequences was located within dorsolateral prefrontal cortex, including an area that was responsive to irregular patterns regardless of the type of visual stimuli producing them. Conversely, temporally regular arrangements resulted in activity in the right frontal lobe (medial frontal gyrus), in the left orbito-frontal cortex and in the left pallidum. The results show that there is an abstractive system in the brain for detecting temporal irregularity, regardless of the source producing it

    Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer

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    As screening methods for colorectal cancer (CRC) are limited by uptake and adherence, further options are sought. A blood test might increase both, but none has yet been tested in a screening setting

    Modeling Magnification and Anisotropy in the Primate Foveal Confluence

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    A basic organizational principle of the primate visual system is that it maps the visual environment repeatedly and retinotopically onto cortex. Simple algebraic models can be used to describe the projection from visual space to cortical space not only for V1, but also for the complex of areas V1, V2 and V3. Typically a conformal (angle-preserving) projection ensuring local isotropy is regarded as ideal and primate visual cortex is often regarded as an approximation of this ideal. However, empirical data show systematic deviations from this ideal that are especially relevant in the foveal projection. The aims of this study were to map the nature of anisotropy predicted by existing models, to investigate the optimization targets faced by different types of retino-cortical maps, and finally to propose a novel map that better models empirical data than other candidates. The retino-cortical map can be optimized towards a space-conserving homogenous representation or a quasi-conformal mapping. The latter would require a significantly enlarged representation of specific parts of the cortical maps. In particular it would require significant enlargement of parafoveal V2 and V3 which is not supported by empirical data. Further, the recently published principal layout of the foveal singularity cannot be explained by existing models. We suggest a new model that accurately describes foveal data, minimizing cortical surface area in the periphery but suggesting that local isotropy dominates the most foveal part at the expense of additional cortical surface. The foveal confluence is an important example of the detailed trade-offs between the compromises required for the mapping of environmental space to a complex of neighboring cortical areas. Our models demonstrate that the organization follows clear morphogenetic principles that are essential for our understanding of foveal vision in daily life

    The Human Connectome Project's neuroimaging approach

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    Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

    P2SF: Physically-based Point Spread Function for digital image processing

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    Abstract: P2SF is a tool aimed at estimating the spatially variant point spread function based on the ray-tracing computation of the pupil function. Only 6 parameters are required to describe a monochromatic PSF
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