For a full list see below or go to Google Scholar or PubMed. Code is available on our GitHub repo.
Zigiotto, L. et al. (2025). Maximizing Tumor Resection and Managing Cognitive Attentional Outcomes: Measures of Impact of Awake Surgery in Glioma Treatment. Neurosurgery.
DOI: 10.1227/neu.0000000000003591
Garyfallidis, E. et al. (2025). Dissecting white matter pathways: Automatic and semiautomatic approaches. Handbook of Diffusion MR Tractography.
DOI: 10.1016/B978-0-12-818894-1.00013-6
Vavassori, L. et al. (2024). Changing the Paradigm for Tractography Segmentation in Neurosurgery: Validation of a Streamline-Based Approach. Brain Sciences.
DOI: 10.3390/brainsci14121232
Tagliaferri, M. et al. (2024). A revision of the dorsal origin of the frontal aslant tract (FAT) in the superior frontal gyrus: a DWI-tractographic study. Brain Structure and Function.
DOI: 10.1007/s00429-024-02778-4
Coletta, L. et al. (2024). Integrating direct electrical brain stimulation with the human connectome. Brain.
DOI: 10.1093/brain/awad402
Hayashi, S. et al. (2024). brainlife.io: A decentralized and open source cloud platform to support neuroimaging research. Nature Methods.
DOI: 10.1038/s41592-024-02237-2
Zigiotto, L. et al. (2024). Spontaneous unilateral spatial neglect recovery after brain tumour resection: A multimodal diffusion and rs‐fMRI case report. Journal of Neuropsychology.
DOI: 10.1111/jnp.12339
Riccardi, C. et al. (2024). Can Transfer Learning Improve Supervised Segmentation of White Matter Bundles in Glioma Patients?. MICCAI Workshop Computational Diffusion MRI (CDMRI).
Baldauf, D. et al. (2024). ‘What’ and ‘Where’ pathways within prefrontal cortex govern top-down attentional control through their differential connectivity fingerprints. Salzburg Min Brain Annual Meeting (SAMBA), Salzburg, Österreich.
DOI: 10.13140/RG.2.2.15686.89922
Astolfi, P. et al. (2023). Supervised Tractogram Filtering using Geometric Deep Learning. Medical Image Analysis.
DOI: 10.1016/j.media.2023.102893
Tagliaferri, M. et al. (2023). Connectivity by the Frontal Aslant Tract (FAT) explains local functional specialization of the superior and inferior frontal gyri in humans when choosing predictive over reactive strategies: a tractography-guided TMS study. Journal of Neuroscience.
DOI: 10.1523/JNEUROSCI.0406-23.2023
Bedini, M. et al. (2023). Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis. Brain Structure and Function.
DOI: 10.1007/s00429-023-02641-y
Vavassori, L. et al. (2023). The Arcuate Fasciculus: Combining Structure and Function into Surgical Considerations. Brain and Behaviour.
DOI: 10.1002/brb3.3107
Zigiotto, L. et al. (2023). Spontaneous Unilateral Spatial Neglect recovery after brain tumor resection: a multimodal diffusion and rs-fMRI case report. Journal of Neuropsychology.
DOI: 10.1111/jnp.12339
Amorosino, G. et al. (2023). How Does White Matter Registration Affect Tractography Alignment?. IEEE 20th International Symposium on Biomedical Imaging (ISBI).
DOI: 10.1109/ISBI53787.2023.10230615
Amorosino, G. et al. (2022). DBB - A Distorted Brain Benchmark for Automatic Tissue Segmentation in Paediatric Patients. Neuroimage.
DOI: 10.1016/j.neuroimage.2022.119486
Zigiotto, L. et al. (2022). Segregated circuits for phonemic and semantic fluency: A novel patient-tailored disconnection study. Neuroimage Clinical.
DOI: 10.1016/j.nicl.2022.103149
Esposito, R. et al. (2022). An integrated TMS-EEG and MRI approach to explore the interregional connectivity of the default mode network. Brain Structure and Function.
DOI: 10.1007/s00429-022-02453-6
Ali, K. M. & Avesani, P. (2022). The Vertical Superior Longitudinal Fascicle and the Vertical Occipital Fascicle. Journal of Neurosurgical Sciences.
DOI: 10.23736/S0390-5616.21.05368-6
Bertò, G. et al. (2021). Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation. Neuroimage.
DOI: 10.1016/j.neuroimage.2020.117402
Sarubbo, S. et al. (2021). Planning brain tumor resection using a probabilistic atlas of cortical and subcortical structures critical for functional processing: a proof of concept. Operative Neurosurgery.
DOI: 10.1093/ons/opaa396
Botvinik-Nezer R., et al. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature.
DOI: 10.1038/s41586-020-2314-9
Virtanen, P. et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods.
DOI: 10.1038/s41592-019-0686-2
Zigiotto, L. et al. (2020). Effects of supra-total resection in neurocognitive and oncological outcome of high-grade gliomas comparing asleep and awake surgery. Journal of Neuro-Oncology.
DOI: 10.1007/s11060-020-03494-9
Astolfi, P. et al. (2020). Tractogram filtering of anatomically non-plausible fibers with geometric deep learning. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) LNCS.
DOI: 10.1007/978-3-030-59728-3_29
Astolfi, P. et al. (2020). A Stem-Based Dissection of Inferior Fronto-Occipital Fasciculus with A Deep Learning Model. IEEE International Symposium on Biomedical Imaging (ISBI).
DOI: 10.1109/ISBI45749.2020.9098483
Amorosino, G. et al. (2020). Automatic Tissue Segmentation with Deep Learning in Patients with Congenital or Acquired Distortion of Brain Anatomy. in Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, LNCS.
DOI: 10.1007/978-3-030-66843-3_2
Olivetti, E. et al. (2020). Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem. International Workshop on Biomedical Image Registration (WBIR), LNCS.
DOI: 10.1007/978-3-030-50120-4_1
