Abstract
Perceptual processes quickly extract information from the environment to facilitate object identification and appropriate action (e.g. Tipper et al., 2006). Fluent stimulus processing can result in positive affect that is then attributed to the stimulus itself (e.g. in contrast, priming and presentation duration (Reber et al., 1998), symmetry, (e.g., Rhodes et al., 1999), and contour extraction (Erle et al., 2017, Flavell et al., 2017)). Fluent object motion can also lead to affect transfer, at least where the motion is directly assessed (e.g., Stevanov et al., 2012). However, there is little published research on the effects of motion fluency on object preference in situations where the motion judgement itself is not a task requirement. Our studies investigated four questions. 1) Does motion fluency (how smooth and predictable motion is) implicitly influence object preference? 2) Can object-fluency association be learnt from repeated exposure? 3) Do learnt associations generalise to situations where the object is rated following a static presentation (no motion cues). These questions around learning have real-world consequences. For example, a product advertised with high fluency might be preferred at the time but this preference might not transfer to seeing the object on a shelf. In seven experiments we examined motion fluency effects on object preference. We demonstrate that 1) fluent objects are preferred over disfluent objects, 2) object-motion associations can be learnt, and 3) learnt associations do not transfer easily to situations where the object is rated following static presentation. Episodic accounts of memory retrieval predict that emotional states experienced at encoding might be retrieved along with the stimulus properties. Though object-motion associations were learnt, there was little evidence for emotional reinstatement when the stimuli were stationary. This indicates that the retrieval processes is a critical limiting factor when considering visuomotor fluency effects on behaviour.
Meeting abstract presented at VSS 2018