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/}
}