Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning
| Autor: | Mohammad Pooyan, Saeed Solouki |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
0301 basic medicine
Structure (mathematical logic) Neurons Relation (database) Recall business.industry Computer science Movement (music) Process (engineering) Movement Supervised learning Models Neurological Semi-supervised learning Modular design 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Neurology Cerebellum Humans Neurology (clinical) Artificial intelligence Supervised Machine Learning business 030217 neurology & neurosurgery |
| Zdroj: | Cerebellum (London, England). 15(3) |
| ISSN: | 1473-4230 |
| Popis: | Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular structure of the cerebellum has been in the core of attention in theoretical and computational modeling. However, most of these models reflect some special features of the cerebellum without regarding the whole motor command computational process. In this paper, we try to make a logical relation between the most significant models of the cerebellum and introduce a new learning strategy to arrange the movement patterns: cerebellar modular arrangement and applying of movement patterns based on semi-supervised learning (CMAPS). We assume here the cerebellum like a big archive of patterns that has an efficient organization to classify and recall them. The main idea is to achieve an optimal use of memory locations by more than just a supervised learning and classification algorithm. Surely, more experimental and physiological researches are needed to confirm our hypothesis. |
| Databáze: | OpenAIRE |
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