Paolo Avesani

This paper develops a framework to distinguish radial and tangential fiber components in human superficial white matter and examines their microstructural and functional properties.

The paper uses tractography to show that FEF connects to dorsal visual streams and IFJ to ventral visual streams, supporting their roles in spatial and non-spatial processing.

This paper evaluates transfer learning for adapting a deep learning model trained on healthy data to segment white matter bundles in glioma patients, finding performance drops due to domain shift and partial success of transfer learning.

This study investigates whether transfer learning can improve segmentation of white matter bundles in glioma patients by addressing domain shift between healthy and patient data.

This study uses fMRI meta-analysis to determine the localization and coactivation patterns of the Frontal Eye Field and Inferior Frontal Junction, revealing their functional connectivity and behavioral roles.

This work evaluates how white matter registration methods affect tractogram alignment using homologous fiber structures as a benchmark.

This study uses TMS and tractography to show that the SFG and IFG have opposite roles in predictive/reactive strategies, mediated by the FAT.

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 different analysis workflows by 70 teams on the same fMRI dataset led to varied results, but meta-analysis found consensus in activated regions.