Load and Attentional Bayes
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 half a century's worth of 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, TICS, 9: 75), 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.
Cite
Text
Dayan. "Load and Attentional Bayes." Neural Information Processing Systems, 2008.Markdown
[Dayan. "Load and Attentional Bayes." Neural Information Processing Systems, 2008.](https://mlanthology.org/neurips/2008/dayan2008neurips-load/)BibTeX
@inproceedings{dayan2008neurips-load,
title = {{Load and Attentional Bayes}},
author = {Dayan, Peter},
booktitle = {Neural Information Processing Systems},
year = {2008},
pages = {369-376},
url = {https://mlanthology.org/neurips/2008/dayan2008neurips-load/}
}