Computational Modeling of Visual Selective Attention Based on Correlation and Synchronization of Neural Activity

Abstract Within the broad area of computational intelligence, it is of great importance to develop new computational models of human behaviour aspects. In this report we look into the recently suggested theory that neural synchronization of activity in different areas of the brain occurs when people attend to external visual stimuli. Furthermore, it is suspected that this cross-area synchrony may be a general mechanism for regulating information flow through the brain. We investigate the plausibility of this hypothesis by implementing a computational model of visual selective attention that is guided by endogenous and exogenous goals (i.e., what is known as top down and bottom-up attention). The theoretical structure of this model is based on the temporal correlation of neural activity that was initially proposed b