Attention, Learning, and the Value of Information

Abstract

Despite many studies on selective attention, fundamental questions remain about its nature and neural mechanisms. Here I draw from the animal and machine learning fields that describe attention as a mechanism for active learning and uncertainty reduction and explore the implications of this view for understanding visual attention and eye movement control. I propose that a closer integration of these different views has the potential greatly to expand our understanding of oculomotor control and our ability to use this system as a window into high level but poorly understood cognitive functions, including the capacity for curiosity and exploration and for inferring internal models of the external world