Early work on attention models is done by Itti, Koch, and Niebur. [1,2]. It's called "saliency" and I think Denny would consider this more along the lines of wh

Early work on attention models is done by Itti, Koch, and Niebur. [1,2]. It's called "saliency" and I think Denny would consider this more along the lines of what the concept of "attention" should be (considering his own words/reservations in using the term). Koch is currently studying neural correlates, Itti is still working on this topic though. Niebur is into the neuroscience part of it (nematode expert). There is a lot of neuroscientific work on attention, really a lot! Overt and covert attention. Microsaccades, very small eye movements, with already a bunch of possible functional roles. Almost everything we know about the brains of little kids is by studying where they look at and where they pay attention to. Structure-wise attention models can be quite simple. The structure that is often seen is a WTA (winner-take-all) network with subsequent serial inhibition. The first winner is inhibited, so the next winner can come on stage. This is the same system as Baars has in his global workspace theory [3]. It is also the same method as in mundane RANSAC models [4]. That's a workhorse of computer vision in which a consensus/voting model can be used to have data points voting for higher-level structures. When one structure is detected, votes for it are removed, and the next most salient structure can be voted for. [1] http://ilab.usc.edu/bu/ http://ilab.usc.edu/bu/ [2] http://cns-alumni.bu.edu/~yazdan/pdf/Itti_etal98pami.pdf http://cns-alumni.bu.edu/~yazdan/pdf/Itti_etal98pami.pdf [3] https://en.wikipedia.org/wiki/Global_Workspace_Theory https://en.wikipedia.org/wiki/Global_Workspace_Theory [4] https://en.wikipedia.org/wiki/RANSAC https://en.wikipedia.org/wiki/RANSAC