This paper is published in the 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI). In this paper, the focus is on developing the system that can relate a brain state to target identification and analysis in an RSVP. In this research, the P300 event occurred due to the shift in attention is analyzed and captured using the electroencephalogram (EEG). A model called Cortically-Coupled Generative Adversarial Network is proposed using this analysis. This model identifies and retrieves the target image in RSVP events. The evaluation of the proposed model demonstrates the combination of EEG signals and cortically-coupled GAN could effectively use to develop a smart way to retrieve the visual data of interest.