Reward Based Motor Adaptation Mediated by Basal Ganglia
| Autor: | Yaroslav I. Molkov, Taegyo Kim, Robert A. Capps, Ilya A. Rybak, William H. Barnett, Elizaveta M. Latash, Dmitry Todorov, Khaldoun C. Hamade, Sergey N. Markin |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
reinforcement learning Neuroscience (miscellaneous) Sensory system Gating Action selection 03 medical and health sciences Cellular and Molecular Neuroscience 0302 clinical medicine Basal ganglia motor adaptation medicine Premovement neuronal activity Reinforcement learning Original Research dopaminergic reward reaching movement Dopaminergic Spinal cord 030104 developmental biology medicine.anatomical_structure basal ganglia Psychology Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | Frontiers in Computational Neuroscience |
| ISSN: | 1662-5188 |
| DOI: | 10.3389/fncom.2017.00019 |
| Popis: | It is widely accepted that the basal ganglia (BG) play a key role in action selection and reinforcement learning. However, despite considerable number of studies, the BG architecture and function are not completely understood. Action selection and reinforcement learning are facilitated by the activity of dopaminergic neurons, which encode reward prediction errors when reward outcomes are higher or lower than expected. The BG are thought to select proper motor responses by gating appropriate actions, and suppressing inappropriate ones. The direct striato-nigral (GO) and the indirect striato-pallidal (NOGO) pathways have been suggested to provide the functions of BG in the two-pathway concept. Previous models confirmed the idea that these two pathways can mediate the behavioral choice, but only for a relatively small number of potential behaviors. Recent studies have provided new evidence of BG involvement in motor adaptation tasks, in which adaptation occurs in a non-error-based manner. In such tasks, there is a continuum of possible actions, each represented by a complex neuronal activity pattern. We extended the classical concept of the two-pathway BG by creating a model of BG interacting with a movement execution system, which allows for an arbitrary number of possible actions. The model includes sensory and premotor cortices, BG, a spinal cord network, and a virtual mechanical arm performing 2D reaching movements. The arm is composed of 2 joints (shoulder and elbow) controlled by 6 muscles (4 mono-articular and 2 bi-articular). The spinal cord network contains motoneurons, controlling the muscles, and sensory interneurons that receive afferent feedback and mediate basic reflexes. Given a specific goal-oriented motor task, the BG network through reinforcement learning constructs a behavior from an arbitrary number of basic actions represented by cortical activity patterns. Our study confirms that, with slight modifications, the classical two-pathway BG concept is consistent with results of previous studies, including non-error based motor adaptation experiments, pharmacological manipulations with BG nuclei, and functional deficits observed in BG-related motor disorders. |
| Databáze: | OpenAIRE |
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