• Jeffrey Schall, Neural Control of Visual Search

This presentation will survey performance, neural and computational findings demonstrating that gaze is guided during visual search through the operation of distinct stages of visual selection and saccade preparation. These stages can be selectively manipulated though target-distractor similarity, stimulus-response mapping rules, and unexpected perturbation of the visual array. Such manipulations indicate that they are instantiated in different neural populations with distinct connectivity and functional properties. Race and accumulator models provide a comprehensive account of the saccade preparation stage and of the conversion of salience evidence into saccade commands.


  • Steven J. Luck, Mechanisms for the Suppression of Irrelevant Objects during Visual Search

We have long known that attention can be directed toward items containing task-relevant feature values.  But can attention also be directed away from irrelevant features (i.e., features indicating than an item is a nontarget)?  In this presentation, I will review recent studies indicating that items containing distinctive nontarget feature values can be suppressed so that they attract attention less than “neutral” items.  This mechanism can be used to suppress salient singletons, as assessed with psychophysics, eye tracking, and ERPs (with significant correlations among these measures, suggesting that they all reflect the same underlying mechanism). This mechanism can also be used to suppress nonsalient distractor items. However, the suppression mechanism does not appear to be under direct voluntary control.  First, if observers are cued to avoid a specific color, the first eye movement tends to be directed to the to-be-avoided color.  Second, the suppression appears to build up over trials. Third, if automatic priming from the previous trial is put into competition with explicit cuing of the to-be-avoided color, priming wins and suppression loses. The emerging picture is that explicit goals can direct attention toward but not away from specific feature values, but goal-driven experience with target and distractor features can lead to automatic suppression of to-be-avoided features.


Statistical learning drives visual selection

Jan TheeuwesVrije Universiteit Amsterdam, The Netherlands

Lingering biases of attentional selection affect the deployment of attention above and beyond top-down and bottom-up control. In this talk I will present an overview of recent studies investigating how statistical learning regarding the distractor determines attentional control. In all these experiments we used the classic additional singleton task in which participants searched for a salient shape singleton while ignoring a color distractor singleton. The distractor singleton was presented more often in one location than in all other locations. Even though observers were not aware of the statistical regularities, we show that the location of the distractor was suppressed relative to all other locations. Moreover, we show that this learning in highly flexible and adaptive. We argue that selection history modulates the topographical landscape of spatial ‘priority’ maps, such that attention is biased towards locations having a high activation and biased away from locations that are suppressed.