According to so-called saliency-based attention models, attention during free viewing of visual scenes is particularly allocated to physically salient image regions. In the present study, we assumed that social features in complex naturalistic scenes would be processed preferentially irrespective of their physical saliency. Therefore, we expected worse prediction of gazing behavior by saliency-based attention models when social information is present in the visual field. To test this hypothesis, participants freely viewed color photographs of complex naturalistic social (e.g., including heads, bodies) and non-social (e.g., including landscapes, objects) scenes while their eye movements were recorded. In agreement with our hypothesis, we found that social features (especially heads) were heavily prioritized during visual exploration. Correspondingly, the presence of social information weakened the influence of low-level saliency on gazing behavior. Importantly, this pattern was most pronounced for the earliest fixations indicating automatic attentional processes. These findings were further corroborated by a linear mixed model approach showing that social features (especially heads) add substantially to the prediction of fixations beyond physical saliency. Taken together, the current study indicates gazing behavior for naturalistic scenes to be better predicted by the interplay of social and physically salient features than by low-level saliency alone. These findings strongly challenge the generalizability of saliency-based attention models and demonstrate the importance of considering social influences when investigating the driving factors of human visual attention.

Saliency-based models of visual attention postulate that, when a scene is freely viewed, attention is predominantly allocated to those elements that stand out in terms of their physical properties. However, eye-tracking studies have shown that saliency models fail to predict gaze behavior accurately when social information is included in an image. Notably, gaze pattern analyses revealed that depictions of human beings are heavily prioritized independent of their low-level physical saliency. What remains unknown, however, is whether the prioritization of such social features is a reflexive or a voluntary process. To investigate the early stages of social attention in more detail, participants viewed photographs of naturalistic scenes with and without social features (i.e., human heads or bodies) for 200 ms while their eye movements were being recorded. We observed significantly more first eye movements to regions containing social features than would be expected from a chance level distribution of saccades. Additionally, a generalized linear mixed model analysis revealed that the social content of a region better predicted first saccade direction than its saliency suggesting that social features partially override the impact of low-level physical saliency on gaze patterns. Given the brief image presentation time that precluded visual exploration, our results provide compelling evidence for a reflexive component in social attention. Moreover, the present study emphasizes the importance of considering social influences for a more coherent understanding of human attentional selection.

The detection of a face in a visual scene is the first stage in the face processing hierarchy. Although all subsequent, more elaborate face processing depends on the initial detection of a face, surprisingly little is known about the perceptual mechanisms underlying face detection. Recent evidence suggests that relatively hard-wired face detection mechanisms are broadly tuned to all face-like visual patterns as long as they respect the typical spatial configuration of the eyes above the mouth. Here, we qualify this notion by showing that face detection mechanisms are also sensitive to face shape and facial surface reflectance properties. We used continuous flash suppression (CFS) to render faces invisible at the beginning of a trial and measured the time upright and inverted faces needed to break into awareness. Young Caucasian adult observers were presented with faces from their own race or from another race (race experiment) and with faces from their own age group or from another age group (age experiment). Faces matching the observers’ own race and age group were detected more quickly. Moreover, the advantage of upright over inverted faces in overcoming CFS, i.e., the face inversion effect (FIE), was larger for own-race and own-age faces. These results demonstrate that differences in face shape and surface reflectance influence access to awareness and configural face processing at the initial detection stage. Although we did not collect data from observers of another race or age group, these findings are a first indication that face detection mechanisms are shaped by visual experience with faces from one’s own social group. Such experience-based fine-tuning of face detection mechanisms may equip in-group faces with a competitive advantage for access to conscious awareness.