Attention in natural scenes: Affective-motivational factors guide gaze independently of visual salience

Abstract

In addition to low-level stimulus characteristics and current goals, our previous experience with stimuli can also guide attentional deployment. It remains unclear, however, if such effects act independently or whether they interact in guiding attention. In the current study, we presented natural scenes including every-day objects that differed in affective-motivational impact. In the first free-viewing experiment, we presented visually-matched triads of scenes in which one critical object was replaced that varied mainly in terms of motivational value, but also in terms of valence and arousal, as confirmed by ratings by a large set of observers. Treating motivation as a categorical factor, we found that it affected gaze. A linear-effect model showed that arousal, valence, and motivation predicted fixations above and beyond visual characteristics, like object size, eccentricity, or visual salience. In a second experiment, we experimentally investigated whether the effects of emotion and motivation could be modulated by visual salience. In a medium-salience condition, we presented the same unmodified scenes as in the first experiment. In a high-salience condition, we retained the saturation of the critical object in the scene, and decreased the saturation of the background, and in a low-salience condition, we desaturated the critical object while retaining the original saturation of the background. We found that highly salient objects guided gaze, but still found additional additive effects of arousal, valence and motivation, confirming that higher-level factors can also guide attention, as measured by fixations towards objects in natural scenes.

Motivational Objects in Natural Scenes (MONS): A Database of >800 Objects

“…Since the exact salience definition to be used may depend on the research question, and the development in the field of salience models is still ongoing (see Borji and Itti, 2013 for a review), we refrained from picking one particular measure to be included with the database. Object eccentricity and object size are additional relevant measures to include ( Schomaker et al, 2017 ).…”

Memory Performance for Everyday Motivational and Neutral Objects Is Dissociable from Attention

“…This database includes >800 pictures of objects taken from natural scenes, each rated by 23–47 observers. Visual characteristics of the stimuli such as size and shape were similar across motivational categories, and a recent study using the MONS database demonstrated motivational effects on eye movements when controlling for visual aspects such as stimulus size and visual contrast (Schomaker et al, 2017). All objects and corresponding demographic and rating data are freely available at http://www.allpsych.uni-giessen.de/mons and will soon be uploaded to a permanent public repository.…”

Characterizing and automatically detecting smooth pursuit in a large-scale ground-truth data set of dynamic natural scenes

“…For example, throughout this manuscript we use the term ''naturalistic'' in order to describe the stimulus scenes in our data set. We use this term in the meaning of ''imitating real life or nature'' in accordance with other literature (Krieger, Rentschler, Hauske, Schill, & Zetzsche, 2000;Torralba, Oliva, Castelhano, & Henderson, 2006;Dorr et al, 2010;Tatler, Hayhoe, Land, & Ballard, 2011;McIlreavy, Fiser, & Bex, 2012;Smith & Mital, 2013;Parks, Borji, & Itti, 2015;Leder, Mitrovic, & Goller, 2016;Ramkumar et al, 2016;Foulsham & Kingstone, 2017;Schomaker, Walper, Wittmann, & Einhäuser, 2017;White et al, 2017). We describe our experimental set-up as naturalistic in part to contrast it with synthetic stimuli with prescribed, isolated eye movements often used for studies involving smooth pursuit (Vidal et al, 2012;Santini et al, 2016): Naturalistic stimuli represent a more complex set of visual inputs that affect oculomotor behavior (Monache, Lacquaniti, & Bosco, 2019), and the idea that the visual system is optimized to efficiently encode the inputs that surrounded our ancestors during evolution is well established (Field, 1987;Atick & Redlich, 1992).…”