In this paper, we suggest that a feedback loop is formed during the chemical plume tracing (CPT) activities of the silkworm moth, Bombyx mori. We demonstrate the formation of this loop by utilizing a novel experiment system called a brain-machine hybrid system (BMHS). We focus on the pheromone source-searching behavior of a silkworm moth. Finding an odor source, referred to as CPT, is a difficult problem for artificial systems. Although a moth has only several million neurons, it can reach a pheromone source, even when it is subjected to the unpredictable dynamics of chemicals. Thus, a moth can adapt to a dynamical environment. In order to investigate this adaptability, we build a BMHS, where the body of a moth is replaced by a mobile robot. By recording the neural activities of the moth’s brain through the BMHS, we investigate its reactions to unexpected motion, in order to identify feedback mechanisms during motion. In this manner, we attempt to solve the CPT problem. The results suggest that a moth utilizes feedback loops during its programmed behavior.