Advanced Neuroimaging Techniques and Applications

This paper estimates axial diffusivity in the NODDI model using high b-value data and shows the impact of noise assumptions on parameter estimates.

This paper introduces a novel fiber tractography method that improves the reconstruction of the corticospinal tract by incorporating anatomical priors and multi-level fiber orientation analysis.

This study quantifies superficial white matter volume and thickness across the lifespan using large datasets, finding unique age-related changes and relationships with cortical features.

The paper finds that retinal ganglion cell endowment correlates with optic tract cross section, not density, and that anatomical variations are locally correlated along the visual pathway.

This study examines structural brain changes and connectivity differences in AMD patients compared to controls using MRI diffusion data over two years.

The paper examines the structural covariance and heritability between the optic tract and primary visual cortex in living humans using neuroimaging data.

This paper develops a deep learning method for individualized thalamic parcellation using diffusion MRI, combining group atlas guidance with single-subject data to improve accuracy and reproducibility.

ModelArray is an R package for efficient statistical analysis of fixel data, supporting linear and nonlinear models with reduced memory usage.

FiberNeat filters false positive and implausible streamlines from tractograms using unsupervised methods, improving tract quality and tractometry.

This paper develops a surface-based tractography method for short association fibres in the human brain, showing it produces longer streamlines and high cortical coverage but with limited reliability and repeatability.

This paper introduces BENCH, a Bayesian framework to infer parameter changes in biophysical models despite parameter degeneracies, applied to diffusion MRI data.

The paper introduces an atlas-free method using a deep recurrent auto-encoder to parcellate tractograms by learning latent streamline embeddings for unsupervised clustering and sub-bundle analysis.

This paper develops a new human cortical parcellation atlas based on primate anatomical tracing studies and validates it using diffusion tractography to identify corticostriatal subcircuits.

This paper introduces a model-free method to detect task-evoked BOLD signal synchrony in white matter using fiber-architecture-informed spatial windows and modified PCA, showing reliable detection in fMRI data.

The paper introduces the Brain/MINDS Marmoset Connectivity Atlas, providing a resource for exploring neuronal tracer data and tractography in a common stereotaxic space.

The paper evaluates tractography methods using a macaque dataset to determine optimal approaches for mapping brain pathways from multi-shell diffusion MRI.

This paper uses machine learning to predict neonatal brain age and clinical risk from structural connectomes, finding thalamocortical connections are key predictors of developmental outcomes.

This paper introduces a surface-based probabilistic tractography method for reconstructing U-fibers in the superficial white matter, showing improved accuracy compared to volume-based and other surface-based methods.

This study compares CPU and GPU implementations of bedpostx for estimating fibre orientations in diffusion MRI, finding minimal statistically significant differences.

This paper develops a tissue-unbiased FOD brain template using multimodal registration to improve white matter analysis and tractography alignment with grey matter structures.

The paper improves axonal volume fraction estimation in diffusion MRI by introducing linear calibration parameters, validated using ex-vivo mouse data and electron microscopy.

This paper introduces hypervoxels to improve neuroimaging analysis by integrating spatial and anatomical information from diffusion MRI data, enhancing detection of white matter effects in ALS.

This study investigates how resolution and b value affect structural connectome in ex vivo mouse brains, finding that higher angular resolution and b value improve tractography and connectome stability.

This paper introduces a clinical diffusion MRI protocol to enable SANDI modeling in 10 minutes, demonstrating its feasibility and potential impact on multiple sclerosis patients.

This paper introduces 3D-printed axon-mimetic phantoms to evaluate diffusion MRI models under complex fibre orientations, finding that Bingham-NODDI best captures planar fibre dispersion.

The paper maps excitatory axonal projections from the macaque ventrolateral prefrontal cortex to the whole brain at submicron resolution, revealing discrepancies with diffusion tractography.

The paper identifies a novel white matter pathway, the medial occipital longitudinal tract, connecting the parahippocampal place area to early visual cortex, suggesting it supports early visuospatial information encoding.

This study uses longitudinal diffusion MRI to examine microstructural changes in brain tracts of college football and volleyball players, finding divergent developmental patterns between the groups.

This study compares AMURA and DTI diffusion measures in migraine patients and controls, finding AMURA detects more regions and shows better discriminative power despite lower stability.