Advanced Neuroimaging Techniques and Applications

Anatomically informed multi-level fiber tractography

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.

Superficial white matter across the lifespan: volume, thickness, change, and relationship with cortical features

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.

Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density

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.

Age-related Macular Degeneration is associated with faster rates of structural brain changes and widespread differences in connectivity

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

Structural covariance and heritability of the optic tract and primary visual cortex in living human brains

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

Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

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: a memory-efficient R package for statistical analysis of fixel data

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

FiberNeat: Unsupervised White Matter Tract Filtering

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

Surface-based tracking for short association fibre tractography

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.

Identifying microstructural changes in diffusion MRI; How to circumvent parameter degeneracy

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

Auto-encoded Latent Representations of White Matter Streamlines for Quantitative Distance Analysis

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.

A new cortical parcellation based on systematic review of primate anatomical tracing studies on corticostriatal projections

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.

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping

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 Brain/MINDS Marmoset Connectivity Atlas: Exploring bidirectional tracing and tractography in the same stereotaxic space

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

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

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

Predicting age and clinical risk from the neonatal connectome

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.

The length of the thalamo-cortical white matter fibers brings insight into sex differences in sleep spindle frequency

Probabilistic Tracking U-fiber on the Superficial White Matter Surface

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.

Comparison of CPU and GPU Bayesian Estimates of Fibre Orientations from Diffusion MRI

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

Building a Tissue-unbiased Brain Template of Fibre Orientation Distribution and Tractography with Multimodal Registration

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

Calibration allows accurate estimation of the axonal volume fraction with diffusion MRI

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

Hypervoxels: A Multidimensional Framework For The Representation And Analysis Of Neuroimaging Data

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.

Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain

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.

Dissecting brain grey and white matter microstructure: a novel clinical diffusion MRI protocol

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.

Enabling complex fibre geometries using 3D printed axon-mimetic phantoms

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.

Mapping brain-wide excitatory projectome of primate prefrontal cortex at submicron resolution: relevance to diffusion tractography

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 missing pathway in current visuospatial processing models

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.

Microstructural alterations in tract development in college football: a longitudinal diffusion MRI study

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.

Viability of AMURA biomarkers from single-shell diffusion MRI in Migraine Clinical Studies

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.

General factors of white matter microstructure from DTI and NODDI in the developing brain

The paper uses DTI and NODDI metrics from 16 white matter tracts in preterm and term infants to identify general factors that capture shared variance and predict preterm birth outcomes.