Intuitive inference and logical inference are two types of inference for human, and many models have been proposed. However, most of them supposed the intuitive inference and the logical inference are realized by different processes. However, no brain area is known yet for the logical inference and few neural model are proposed that can clearly explain its macroscopic process. So, in this study, we propose an integrated model in which the intuitive inference is represented as a search process of in a continuous and distributed associative memory, and is switched to a symbolic inference mode that biases an associative gain when it find values during the intuitive inference search. In this study, we discuss its computational model by an associative memory and show its simulation results.