Exploring Dynamic Changes due to Ataxia Through Virtual Brain Models

Brain modeling has become an indispensable tool to better understand the intricate details of the brain's structure, which necessitate innovative approaches to fully comprehend the underlying mechanisms at play. Specifically, placing emphasis on reproducing brain dynamics and their variations in various pathologies is essential, and brain modeling provides an excellent platform for such investigations, including conditions like ataxia. Various software platforms, both general and specific-purpose, have been developed for the construction and simulation of neural and brain networks. The Virtual Brain (TVB) stands out among these, serving as a computational framework tailored for simulating and modeling whole brain network dynamics. In this thesis, TVB is used in conjunction with the Allen Mouse Brain Atlas as a foundational structural connectivity reference. The aim of this thesis is to explore brain modeling in mice, starting from experimental data coming from resting-state mice fMRI, as in Pagani et al. (2021). From these dataset, we fine tuned the parameters of a mouse brain model in TVB, with a more specific focus on the cerebellar nodes, to computationally reproduce the brain dynamics in healthy mice subjects. The second step was then to extend these investigations into an ataxic model, by varying the parameters of the model in the cerebellar nodes, in order to reproduce experimental evidence of ataxic changes in mice. These changes aim to reproduce the changes that happen due to cell degeneration in ataxia. This thesis underscores the significance of brain modeling, utilizing The Virtual Brain framework to simulate and fine-tune mouse brain dynamics. The research not only advances our understanding of healthy brain function but also offers a promising avenue for investigating potential therapies, like TMS, of neurological disorders, such as ataxia, through computational modeling.