Attentional Templates Are Sharpened through Differential Signal Enhancement, Not Differential Allocation of Attention

Abstract

In visual search, the internal representation of the target feature is referred to as attentional template. The attentional template can be broad or precise depending on the task requirements. In singleton search, the attentional template is broad because the target is the only colored element in the display. In feature search, a precise attentional template is required because the target is in a specific color in an array of varied colors. To measure the precision of the attentional template, we used a cue-target paradigm where cueing benefits decrease when the cue color differs from the target color. Consistent with broad and precise attentional templates, the decrease of cueing effects was stronger in feature than in singleton search. Measurements of ERPs showed that the N2pc elicited by the cue decreased with increasing color difference, suggesting that attention was more strongly captured by cues that were similar to the target. However, the cue-elicited N2pc did not differ between feature and singleton search, making it unlikely to reflect the mechanism underlying attentional template precision. Furthermore, there was no evidence for attentional suppression as there was no cue-elicited PD, even in conditions where the cueing benefit turned into a same-location cost. However, an index of signal enhancement, the contralateral positivity, reflected attention template precision. In general, there was sensory enhancement of the stimulus appearing at the cued location in the search display. With broad attentional templates, any stimulus at the cued location was enhanced, whereas enhancement was restricted to target-matching colors with precise attentional templates.

Guidance of visual search by negative attentional templates depends on task demands.

“…Thus, the worse performance at the cued location (i.e., same-location costs) was not caused by attentional suppression of the spatial cue. Rather, Kerzel and Huynh Cong (2021) found that spatial cues resulting in same-location costs reduced subsequent signal enhancement for stimuli at the cued location. Signal enhancement at the cued location is indexed by the CP component (Livingstone et al, 2017).…”

“…That is, signal enhancement at the cued location may have been selectively inhibited if the spatial cue was in the color of the negative template. The inhibition of signal enhancement may explain why there were pronounced same location costs for nonmatching spatial cues with negative templates (see also Kerzel & Huynh Cong, 2021). Thus, we suggest that negative templates are implemented as a two-stage process where spatial cues are initially attended independently of their color, but subsequent inhibition reduces the signal enhancement at the location of spatial cues in the color of the negative template.…”

“…Event-related responses to the cue display showed that spatial cues in the target-matching color elicit an N2pc, suggesting that attention was deployed to the cue, whereas there was no N2pc to spatial cues in the nonmatching color (Eimer & Kiss, 2008; Lien et al, 2008, 2010). Concerning search tasks where nonmatching spatial cues produced same-location costs, recent studies found no evidence for attentional suppression of the cue as indexed by a P D (Kerzel & Huynh Cong, 2021; Schönhammer et al, 2020). Thus, the worse performance at the cued location (i.e., same-location costs) was not caused by attentional suppression of the spatial cue.…”

Target templates and the time course of distractor location learning

“…In contrast, when searching for a shape singleton target, the shape of the target and the distractor changes unpredictably, which rules out using a feature-specific target template (Lamy et al, 2006). Similarly, in tasks where target and distractor swap colours across trials (Hickey et al, 2006;Theeuwes, 1991;van Moorselaar et al, 2021;Wang & Theeuwes, 2018b) observers cannot use a feature-specific target template (Geng et al, 2017;Kerzel & Huynh Cong, 2020). Under these search conditions, observers adopt a singleton-detection mode (Bacon & Egeth, 1994) to find the target, and down-weighting features or dimensions is no longer a viable strategy for distractor handling.…”

Attentional priority is determined by predicted feature distributions.

“…For example, if the friend you are searching for wears only warm colored shirts, but pants of any color, prioritizing the low-variability distribution of shirt colors over the high-variability distribution of paint colors will maximize predictive information in the target template (i.e., minimize target uncertainty). Target features encoded into working memory are known to be remarkably sensitive to the task-relevance of information (Becker et al, 2010; Boettcher et al, 2020; Geng & Witkowski, 2019; Nobre & Stokes, 2019; Rajsic et al, 2020), and it has been shown that object features are flexibly removed or compressed so that only the most informative features are used to guide attention (Bravo & Farid, 2012, 2016; Kerzel & Cong, 2021; Reeder et al, 2017; Woodman & Vogel, 2008; Zivony & Lamy, 2016). Previous work has also shown that when sensory information differs in reliability, perception is optimally weighted toward the most reliable cue (Fetsch et al, 2012; Hillis et al, 2004), resulting in a “push-pull” dynamic for attentional priority (Foley et al, 2017; Kozyrev et al, 2019; Mehrpour et al, 2020; Pinsk et al, 2004).…”