Attention, learning and the value of information
By Jacqueline Gottlieb. 2012
232 citations recorded by the source corpus.
Despite many studies on selective attention, fundamental questions remain about its nature and neural mechanisms. 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. 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 curiosity and exploration and inferring internal models of the external world.
Subfields: Cognitive Neuroscience, Molecular Biology
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In Cognitive Neuroscience
- Lien Van Eylen
- Lee H. de-Wit
- R. Van der Hallen
- Kris Evers
- Bart Boets
- Johan Wagemans
- Sander Van de Cruys
Citations in the corpus
- Precise minds in uncertain worlds: predictive coding in autism. (2014, background): “Setting precision consequently relies on a form of metalearning: learning what is learnable (Gottlieb, 2012) or estimating the predictability of new contingencies.”