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Paper on attentional tracking published

Published: 2009-10-21 14:46:32

A Journal of Vision paper by graduate student Wei Huang and myself just appeared in Journal of Vision: http://journalofvision.org/9/11/3/

It is called "No capacity limit in attentional tracking: Evidence for probabilistic inference under a resource constraint". We address the problem of how well people do in track multiple items simultaneously. Daily-life examples include a teacher tracking children on a playground, a radar operator tracking airplanes on a screen, or a basketball coach tracking his players. The usual way of studying this is by asking the question "HOW MANY ITEMS can someone track?" We argue that asking the question this way is already committing yourself to one model, namely that there is a limit on the number of items you can track. In the paper we propose an alternative theoretical framework, in which each item is tracked, but the more items there are, the worse the noise it gets. The brain then does the best it can based on the noisy evidence. This type of model is called "probabilistic inference". We find that this model describes the data a lot better than the old model. This could have large implications for how scientists understand attention.

Matlab code is available on http://neuro.bcm.edu/malab/index.php?m=static&id=16.