Attention, learning, and the value of information.
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.
Department of Neuroscience, Columbia University, New York, NY 10032, USA. jg2141@columbia.edu
Jacqueline
J
Gottlieb
D000818:Animals; D001185:Artificial Intelligence; D001288:Attention / Q000502:physiology*; D001921:Brain / Q000166:cytology*; D005133:Eye Movements / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology*; D008606:Mental Processes / Q000502:physiology; D009474:Neurons / Q000502:physiology*