Claudia Casellato

In a mouse whole-brain co-simulation with a spiking olivocerebellar network, cutting mossy-fiber input to cerebellar nuclei lowers M1-S1 gamma coherence, while removing Purkinje inhibition raises it.

This study uses brain digital twins to compare network changes in congenital and slowly progressive cerebellar ataxias, finding distinct patterns in network topology and dynamics that correlate with clinical symptoms.

The paper introduces Auto-MFM, a tool that automatically derives mean field models from spiking neural networks, accurately reproducing population dynamics and enabling exploration of physiological and pathological brain circuits.

This paper develops a region-specific mean field model for the cerebellum, improving virtual brain simulations of local and global dynamics compared to standard oscillators.

The paper uses mesoscale simulations to show that synergistic plasticity in cerebellar circuits is essential for classical eyeblink conditioning.

The paper introduces BSB, a framework for modeling brain microcircuits, and applies it to reconstruct and simulate the mouse cerebellar cortex at cellular resolution.

This paper develops a spiking neural network model of the cerebellum with dual STDP processes to explain how saccadic eye movements are controlled for accuracy and vigor.

The paper benchmarks two neuromorphological simulators, NEURON and Arbor, on CPUs and GPUs, showing Arbor can be 60-400x faster and 100x more energy efficient.

The paper develops a scaffold model of the cerebellar network to simulate neuronal dynamics and test structural-functional hypotheses.

The paper introduces the E-GLIF neuron model, which can reproduce complex electroresponsive properties of Golgi cells using a simplified framework.