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    This study introduces a novel double diffeomorphism model to analyze brain structure changes in neurodevelopmental disorders. The method effectively identifies and visualizes anomalies in neural circuits, outperforming traditional single diffeomorphism techniques in distinguishing patients with Gilles de la Tourette syndrome (GTS).

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    Area of Science:

    • Neuroscience
    • Medical Imaging
    • Computational Anatomy

    Background:

    • Brain neural circuits comprise grey matter and white matter tracts.
    • Neurodevelopmental disorders present complex morphological and organizational alterations.
    • Existing shape analysis methods struggle to capture these combined changes effectively.

    Purpose of the Study:

    • To introduce a novel 'double diffeomorphism' deformation model for analyzing neural circuit alterations.
    • To integrate this model into a Bayesian framework for constructing brain atlases.
    • To evaluate the model's efficacy in identifying and quantifying pathological anomalies in neurodevelopmental disorders.

    Main Methods:

    • Development of a 'double diffeomorphism' model combining two diffeomorphisms to capture connectivity and morphology.
    • Integration of the model within a Bayesian framework for atlas construction.
    • Application and evaluation on 3D neural circuit structures from patients with Gilles de la Tourette syndrome (GTS).

    Main Results:

    • The double diffeomorphism model successfully localizes, quantifies, and visualizes pathological anomalies in neural circuits.
    • The proposed model demonstrates superior discrimination between controls and GTS patients compared to single diffeomorphism methods.
    • This approach offers a comprehensive analysis of both structural connectivity and global morphology.

    Conclusions:

    • The double diffeomorphism model provides an advanced tool for understanding neurodevelopmental disorders.
    • This method enhances the ability to detect and characterize brain abnormalities in conditions like GTS.
    • The findings suggest a significant improvement in analyzing complex brain structure alterations.