Research Group: Egidio D’Angelo, Claudia Casellato, Stefano Masoli, Stefano Casali

The research strategy of this group aims to elucidate the computational bases of cerebellar neurons and circuits using mathematical models and to understand their implications for disease and neurorehabilitation. The techniques include neuronal and microcircuit modeling using NEURON, large-scale network modeling using NEST, and behavioral modeling using simulated robotic environments.
Mathematical models are important for understanding how neurons and circuits operate and allow predictions about cellular mechanisms and their behavioral consequences. We have first developed model of neurons and circuits at different levels of complexity and applied them to explain the fundamental physiological functions of the cerebellum. For further details <http://www-5.unipv.it/dangelo/>. A PhD student will have the possibility to choose different specific projects: 1. modeling single neuron properties (e.g. deep cerebellar nuclear cells and molecular layer interneurons). 2. Modeling cerebellar local microcircuits (the granular and molecular layer). 3. Modeling large-scale networks connecting the cerebellum to other brain regions (specifically the neocortex). There will be the possibility to apply the study to pathological cases, especially autism, with the aim of identifying strategies for neurorehabilitation. The data will be strictly bound to experimental research in order to understand the integrative implication of neuronal and synaptic properties (like plasticity) for brain integrative functions.
Students have the possibility to spend part of their research activity in collaboration with research groups in Holland and Switzerland. The works are developed within the collaborative framework of the Human Brain Project, of which the group is one of the leading units <https://www.humanbrainproject.eu/en/>.

Recent Publications:

• D’Angelo E., Nieus T., Maffei A., Armano S., Rossi P., Taglietti V., Fontana A., Naldi G. (2001) Theta-frequency bursting and resonance in cerebellar granule cells: experimental evidence and modeling of a slow K+-dependent mechanism. J. Neurosci. 21, pp. 759-770.
• Sergio Solinas, Thierry Nieus, and Egidio D’Angelo (2010). A realistic large-scale model of the cerebellum granular layer predicts circuit spatio-temporal filtering properties. Frontiers in Cellular Neuroscience. April 2010, volume 4, article 12.
• S. Masoli, S. Solinas, E. D’Angelo. (2015) Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization. Front. Cell. Neurosci.
• Geminiani A, Casellato C, Antonietti A, D’Angelo E, Pedrocchi A. Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies. Int J Neural Syst. 2017 Jan 10:1750017.