Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review
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 model...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10613816/ |
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| _version_ | 1846159836229664768 |
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| author | Shaojia Huang Tao Xu Jiaqing Chen Jiajia Huang Zhikun Wang Ya Ke Wing Ho Yung |
| author_facet | Shaojia Huang Tao Xu Jiaqing Chen Jiajia Huang Zhikun Wang Ya Ke Wing Ho Yung |
| author_sort | Shaojia Huang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a8fdcfac13054dc4bffa8834dbcdffe6 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-a8fdcfac13054dc4bffa8834dbcdffe62024-11-23T00:01:40ZengIEEEIEEE Access2169-35362024-01-011217072117074010.1109/ACCESS.2024.343514110613816Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive ReviewShaojia Huang0Tao Xu1https://orcid.org/0000-0003-0996-9953Jiaqing Chen2Jiajia Huang3Zhikun Wang4Ya Ke5Wing Ho Yung6School of Intelligent Manufacturing and Aeronautics, Zhuhai College of Science and Technology, Zhuhai, ChinaDepartment of Biomedical Engineering, Shantou University, Shantou, ChinaJiangmen Central Hospital, Jiangmen, ChinaSchool of Biomedical Science, The Chinese University of Hong Kong, Hong Kong, SAR, ChinaDepartment of Neuroscience, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, SAR, ChinaSchool of Biomedical Science, The Chinese University of Hong Kong, Hong Kong, SAR, ChinaDepartment of Neuroscience, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, SAR, ChinaThe 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.https://ieeexplore.ieee.org/document/10613816/Cerebellar modelingmotor learningsynaptic plasticityrobotic controlartificial intelligence |
| spellingShingle | Shaojia Huang Tao Xu Jiaqing Chen Jiajia Huang Zhikun Wang Ya Ke Wing Ho Yung Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review IEEE Access Cerebellar modeling motor learning synaptic plasticity robotic control artificial intelligence |
| title | Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review |
| title_full | Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review |
| title_fullStr | Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review |
| title_full_unstemmed | Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review |
| title_short | Advancements in Cerebellar Modeling and Its Practical Applications: A Comprehensive Review |
| title_sort | advancements in cerebellar modeling and its practical applications a comprehensive review |
| topic | Cerebellar modeling motor learning synaptic plasticity robotic control artificial intelligence |
| url | https://ieeexplore.ieee.org/document/10613816/ |
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