Abstract:
Human reinforcement learning (RL) has been known to utilize two distinctive learning strategies, model-based (MB) and model-free (MF) RL. The process of arbitration betwe...Show MoreMetadata
Abstract:
Human reinforcement learning (RL) has been known to utilize two distinctive learning strategies, model-based (MB) and model-free (MF) RL. The process of arbitration between MB and MF is thought to be located in the ventrolateral prefrontal cortex and frontopolar cortex. These loci are near the cortex, so we expect the related information can be represented in EEG signals. However, EEG signal patterns considering the arbitration of RL has not been investigated. In this paper, we tested a EEG-based classification model to separate these two different types of trials, each of which is meant to promote MB and MF RL. We found, for the first time, firm evidence to indicate that information pertaining to learning strategies is represented in prefrontal EEG signals.
Date of Conference: 15-17 January 2018
Date Added to IEEE Xplore: 12 March 2018
ISBN Information:
Electronic ISSN: 2572-7672
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- IEEE Keywords
- Index Terms
- Learning Strategies ,
- Model-free Reinforcement Learning ,
- EEG-based Classification ,
- Arbitration ,
- EEG Signals ,
- Trial Type ,
- Ventrolateral Prefrontal Cortex ,
- Anterior Prefrontal Cortex ,
- Model-based Reinforcement Learning ,
- Different Types Of Trials ,
- Classification Accuracy ,
- Support Vector Machine ,
- Frequency Band ,
- Specific Goals ,
- Independent Component Analysis ,
- EEG Recordings ,
- Geodesic ,
- Low Uncertainty ,
- Event-related Potentials Analysis ,
- Channel Positions
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Learning Strategies ,
- Model-free Reinforcement Learning ,
- EEG-based Classification ,
- Arbitration ,
- EEG Signals ,
- Trial Type ,
- Ventrolateral Prefrontal Cortex ,
- Anterior Prefrontal Cortex ,
- Model-based Reinforcement Learning ,
- Different Types Of Trials ,
- Classification Accuracy ,
- Support Vector Machine ,
- Frequency Band ,
- Specific Goals ,
- Independent Component Analysis ,
- EEG Recordings ,
- Geodesic ,
- Low Uncertainty ,
- Event-related Potentials Analysis ,
- Channel Positions
- Author Keywords