  To solve a navigation task based on experiences, we need a mechanism to
associate places with objects and to recall them along the course of action. In
a reward-oriented task, if the route to a reward location is simulated in mind
after experiencing it once, it might be possible that the reward is gained
efficiently. One way to solve it is to incorporate a biologically plausible
mechanism. In this study, we propose a neural network that stores a sequence of
events associated with a reward. The proposed network recalls the reward
location by tracing them in its mind in order. We simulated a virtual mouse
that explores a figure-eight maze and recalls the route to the reward location.
During the learning period, a sequence of events relating to firing along a
passage was temporarily stored in the heteroassociative network, and the
sequence of events is consolidated in the synaptic weight matrix when a reward
is fed. For retrieval, the sequential activation of conjunctive cue-place cells
toward the reward location is internally generated by an impetus input. In the
figure-eight maze task, the location of the reward was estimated by mind
travel, irrespective of whether the reward is in the counterclockwise or
distant clockwise route. The mechanism of efficiently reaching the goal by mind
travel in the brain based on experiences is beneficial for mobile service
robots that perform autonomous navigation.

Neurons and Cognition