Franco Pestilli

This paper presents high-resolution diffusion MRI techniques for in vivo and ex vivo macaque brain imaging at 10.5 Tesla, enabling detailed connectivity studies.

This study benchmarks deep learning models for white matter tract segmentation across diverse datasets, finding that CNN-based models perform best within their training domain but degrade under domain shifts, and introduces an ensemble method to mitigate this issue.

The paper investigates how sample size and cohort composition affect the replicability of brain-behaviour associations using Canonical Correlation Analysis on UK Biobank data.

This paper develops a scalable PS-OCT system for whole-brain imaging in rhesus macaques, achieving high-resolution volumetric data with multi-terabyte datasets.

This study tracks brain development and learning in first graders, finding that white matter changes predict math learning but not reading.

The paper aligns white matter tracts with canonical functional brain networks using an atlas and meta-analytic decoding, revealing structural-functional organization.

The paper shows that structural connectivity in the human visual cortex preserves retinotopic organization, revealing a retinotopic wiring principle and systematic perceptual asymmetries in early visual cortex connectivity.

This paper evaluates the diffusion-weighted steady-state free precession (DW-SSFP) sequence for ex vivo macaque brain imaging at 10.5T, showing improved SNR efficiency and geometric distortion reduction.

The paper uses diffusion tractography and machine learning to show that specific white matter tracts predict individual differences in sensorimotor learning outcomes.

Neurodesk provides a portable and reproducible neuroimaging analysis platform using software containers to enable accessible and flexible data analysis pipelines.

This study examines how hippocampal subfield microstructure develops and relates to two types of inference tasks in humans.

This paper introduces a 1D-CNN denoising method for DWI data that improves image quality and microstructural measurements by learning from low-noise datasets.

The paper examines the development of the posterior vertical pathway (PVP) white matter tracts and finds they are more adult-like than dorsal stream tracts but less than ventral stream tracts, and are linked to perceptual task performance in children.

The paper introduces a large-scale 7T fMRI dataset of natural scenes to advance cognitive and computational neuroscience research.

The paper identifies a single-axis association linking brain structure and behavior across the lifespan, showing strong predictive power for age.

The paper uses deep learning to analyze cerebellar morphology across species, finding sex and cannabinoid signaling influence folding patterns.

The paper compares white matter microstructure changes in glaucoma and monocular blindness, finding distinct patterns outside the visual system.

The paper shares a dataset of diffusion MRI data and derivatives from collegiate athletes and non-athletes to study the effects of long-term athletic exposure on brain structure.

Classifyber improves white matter bundle segmentation by combining atlas, connectivity, and geometry data into a linear model, showing robustness across diverse datasets.

The paper shows that white matter fibers connecting area prostriata and the thalamus are retinotopically organized, with distinct pathways for central and peripheral visual fields.

The paper investigates visual cortex plasticity in a rare case of optic chiasm hypoplasia, finding three hemifield maps in one hemisphere and suggesting developmental re-wiring supports their function.

This study assesses the reproducibility of manual segmentation of the pyramidal tract in diffusion MRI tractography across experts and non-experts, finding voxel-wise measures more reproducible than streamline-wise ones.

This paper uses diffusion MRI to detect and quantify crossing fiber abnormalities in the optic chiasm of individuals with albinism, showing improved detection with optimized streamline filtering methods.

This study examines how age-related macular degeneration affects visual acuity and white matter in the optic radiation, showing a correlation between retinal damage and white matter properties.

This paper introduces a framework to encode brain connectomes and diffusion data into multidimensional arrays, enabling efficient storage and analysis of connectome data.