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Conference Paper

Load and Attentional Bayes

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Citation

Dayan, P. (2009). Load and Attentional Bayes. In D. Koller, D. Schuurmans, Y. Bengio, & L. Bottou (Eds.), Advances in neural information processing systems 21 (pp. 370-377). Red Hook, NY, USA: Curran.


Cite as: https://hdl.handle.net/21.11116/0000-0002-DE4F-D
Abstract
Selective attention is a most intensively studied psychological phenomenon, rife
with theoretical suggestions and schisms. A critical idea is that of limited capacity,
the allocation of which has produced continual conflict about such phenomena
as
early
and
late
selection. An influential resolution of this debate is based on
the notion of perceptual load (Lavie, 2005), which suggests that low-load, easy
tasks, because they underuse the total capacity of attention, mandatorily lead to
the processing of stimuli that are irrelevant to the current attentional set; whereas
high-load, difficult tasks grab all resources for themselves, leaving distractors high
and dry. We argue that this theory presents a challenge to Bayesian theories of
attention, and suggest an alternative, statistical, account of key supporting data.