A mathematical model of planning in the prefrontal cortex

The prefrontal cortex (PFC) is involved in many complex cognitive functions such as problem-solving, planning, reasoning, and decision-making. However, the biological mechanisms of these computations are not clear. To understand these mechanisms, we theoretically consider the experimental result of a path-planning task by Mushiake et al. using a mathematical model referred to as the potential network model. The simulation results show that our model can take the correct path in most trials, regardless of the goal positions and the block patterns in the task. Furthermore, our model reproduces the characteristics of the neuronal activity in both the PFC and the primary motor cortex. This study reveals that although the potential network model is abstract, it can be useful in modelling higher brain functions. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007