Alberto Cacciola

This study uses functional connectome fingerprinting to show that individual brain organization remains stable during social interactions, with connectivity patterns linked to social roles and autistic traits.

The paper identifies shared functional organization in pulvinar-cortical and cortico-cortical connectivity through structural and molecular imaging correlates in the human brain.

This study uses machine learning to predict post-surgical structural rearrangements in brain tumors by analyzing preoperative functional and diffusion MRI data.

This study examines gamma oscillations during reaching movements and finds they predict movement velocity and duration.

The paper evaluates how different diffusion signal modeling and segmentation methods affect subthalamic nucleus parcellation, finding that multi-fiber modeling with fiber density thresholding improves between-subject similarity.

This study uses track-weighted dynamic functional connectivity to identify white matter components associated with functional connectivity dynamics and cognitive performance.

This study evaluates parcellation pipelines for identifying the ventral intermediate nucleus (Vim) using tractography, finding that higher-order modeling and threshold-based classification yield the most reliable results despite inter-subject variability.

This paper introduces a novel imaging protocol using short-tracks track-density imaging to identify thalamic nuclei in vivo with high reliability.