Threat stimuli are considered to be processed with higher priority due to an automatic threat detection system that enables rapid shifts of attention. However, direct evidence is still missing. The present study used the face-in-the-crowd task and event-related potentials to find evidence for the functionality of attention shifts in threat detection. The threat detection advantage was replicated in the behavioral results. An N2pc was observed that was more pronounced and earlier for angry compared to happy faces, suggesting differential attention allocation underlying the threat detection advantage. A larger sustained posterior contralateral negativity indicated that angry faces also gained more enhanced subsequent processing. An early posterior negativity observed 160 ms after stimulus onset revealed early emotion-specific processing that may have caused differences in attention allocation toward threatening stimuli.

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

An angry face is expected to be detected faster than a happy face because of an early, stimulus-driven analysis of threat-related properties. However, it is unclear to what extent results from the visual search approach-the face-in-the-crowd task-mirror this automatic analysis. The paper outlines a model of automatic threat detection that combines the assumption of a neuronal system for threat detection with contemporary theories of visual search. The model served as a guideline for the development of a new face-in-the-crowd task. The development involved three preliminary studies that provided a basis for the selection of angry and happy facial stimuli resembling each other in respect to perceptibility, homogeneity, and intensity. With these stimuli a signal detection version of the search task was designed and tested. For crowds composed of neutral faces, the sensitivity measure d' proved the expected detection advantage of angry faces compared to happy faces. However, the emotional expression made no difference if a neutral face had to be detected in crowd composed of either angry or happy faces. Results are in line with the assumption of a stimulus-driven shift of attention giving rise to the superior detection of angry target faces.

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