Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review - Shaojia Huang; Tao Xu; Jiaqing Chen; Jiajia Huang; Zhikun Wang; Ya Ke; Wing Ho Yung (IEEE Access)
The cerebellum plays a crucial role in motor learning and memory, and recent studies have proposed various cerebellar models to investigate these functions. This review examines the literature on different levels of cerebellar modeling, including animal models, neuronal and synaptic plasticity models, relevant artificial intelligence (AI) paradigms, and real-time applications. The development of cerebellar models is discussed, from simple to complex and from theory to application. Optimization methods used in AI for optimizing cerebellar neuronal electrophysiology parameters are also highlighted, allowing for the prediction of difficult-to-observe neuronal features. Combining neuroscience and computer science-oriented neural networks, such as the spiking neural network (SNN) and the artificial neural network (ANN), can enable the cerebellar model to adapt to various applications, including robotic control, neurological disease simulation, and drug delivery simulation. This review provides a useful guide for future research on cerebellar modeling.