P061 A Multi-Scale Virtual Mouse Brain for Investigating Cerebellar-Related Ataxic Alterations
Marialaura De Grazia1∗, Elen Bergamo1, Dimitri Rodarie1, Alberto A. Vergani1, Egidio D’Angelo1,2, Claudia Casellato1
1Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy 2Digital Neuroscience Center IRCCS Mondino Foundation, Pavia, Italy ∗Email:marialaura.degrazia01@universitadipavia.it
Introduction Ataxias are neurodegenerative disorders commonly associated with cerebellar dysfunction, often resulting from impaired Purkinje cell (PC) function and progressive loss. In this project, we employed a spiking neural network (SNN) of a mouse olivocerebellar microcircuit, in which we incorporated key PC ataxia- related alterations. We investigated the effect of reduced dendritic arborization, cell shrinkage, and cell loss. These modifications lead to abnormal dynamics within the deep cerebellar nuclei (DCN), which project to the cerebral cortex. Our aim is to create a multiscale framework that integrates cerebellar SNNs with a virtual mouse brain model to investigate the effects of ataxic alterations on whole-brain dynamics (Fig.1A).
Methods We built a virtual mouse brain network [2] using Allen Mouse Connectome [3] to link neural mass models (a Wong-Wang two-population model per node) on The Virtual Brain (TVB) platform (Fig.1B). Network parameters were tuned employing resting-state fMRI of 20 mice [4]. We are testing a TVB co-simulation framework [5] by replacing each cerebellar node with a cerebellar SNN. For cerebellar network reconstruction and simulation, we used the Brain Scaffold Builder (BSB) [1], which integrates the NEST simulator (Fig.1C). After validating healthy dynamics, we introduced ataxia-related alterations (reduced PC dendritic complexity, shrinkage, and density) and tested various stimulation protocols (e.g. Poisson inputs to mossy fibers from 4 to 100 Hz).
Results The results indicate that as PC density, dendritic complexity index (DCI) and size decrease, the DCN become increasingly disinhibited due to reduced inhibitory input from PCs. The mildest network dysfunction occurs with DCI reduction alone, while more pronounced changes emerge when PCs also shrink. However, the most substantial disruptions in cerebellar dynamics arise with progressive PC density reduction (Fig.1D).Additionally, TVB global coupling and Wong-Wang model parameters were optimized for each resting-state network to maximize the match between experimental and simulated functional connectivity matrices. TVB simulations are in progress.
Discussion Next steps will consist in further investigation of the dynamics of the ataxic cerebellar SNN, with a particular focus on exploring the electrophysiological changes within the PC model.Moreover, we are testing a TVB-NEST co-simulation framework and tuning the proxy nodes, the interface nodes between the two simulators, that enable the bidirectional conversion between spike-based and rate-coded information. This multiscale model will enhance our ability to predict and analyze alterations in large-scale brain activity and functional networks under ataxic conditions. Furthermore, it may serve as a computational tool for evaluating neuromodulation protocols (e.g. Transcranial Magnetic Stimulation) for treating cerebellar ataxias.
Figure 1. Figure 1: A. Multiscale framework for cerebellar SNN-neural mass interaction. B. TVB integrates Mouse Connectome with Wong-Wang models. C. Cerebellar network built by BSB maps SNN placement and connectivity. D. Simulating ataxia: reduced PC DCI affects granule cells to PC (via pf: parallel fibers) connectivity, PC loss impacts PC-DCNp connectivity. Testing: mossy fibers input vs. DCNp firing rate. Acknowledgements
PRIN project 20228B2HN5 “cerebellar NEuromodulation in ATaxia: digital cerebellar twin to predict the MOVEment rescue (NEAT-MOVE)” (CUP master: F53D23005950006310) References
