Simulating reaction time for Eureka effect in visual object recognition using artificial neural network
This addresses the challenge of modeling human creativity and object recognition for cognitive science and AI, but it appears incremental as it builds on prior psychological studies.
The authors tackled the problem of simulating human Eureka recognition in visual object recognition by constructing an artificial neural network model based on neural processes of coincidence of multiple stochastic activities, but no concrete results or numbers were provided.
The human brain can recognize objects hidden in even severely degraded images after observing them for a while, which is known as a type of Eureka effect, possibly associated with human creativity. A previous psychological study suggests that the basis of this "Eureka recognition" is neural processes of coincidence of multiple stochastic activities. Here we constructed an artificial-neural-network-based model that simulated the characteristics of the human Eureka recognition.