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1- Amol University of Special Modern Technologies, Amol, Iran.
2- Islamic Azad University, Ayatollah Amoli, Amol, Iran.
Abstract:  
One of the big concern in neuroscience is problem solving and decision-making. In this domain, everything could be more complex when events occurred sequentially. One of the experienced methods for handling the complexity of brain function is to create an empirical model. Model predictive control (MPC) is dominated as a powerful mathematical based tool which often using within industrial environments. We proposed MPC and its algorithm as a part of the functionalities of the brain in order to improve the performance of the decision-making process. It well known that the decision process results in communication between prefrontal cortex (working memory) and hippocampus (long-term memory). Although the other regions of the brain play an important role to construct decisions, which their mechanisms still are unknown. In this study, we modeled those mechanisms with MPC. We showed that MPC controlled the stream of data between prefrontal cortex and hippocampus in the closed-loop system to correct actions.
Type of Study: Original | Subject: Computational Neuroscience
Received: 2019/05/13 | Accepted: 2019/08/17

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