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Ruosi Wang, Yaoda Xu; Contextual Facilitation of Action-related Object Pairs. Journal of Vision 2016;16(12):1403. doi: 10.1167/16.12.1403.
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© 2017 Association for Research in Vision and Ophthalmology.
Objects rarely appear in isolation, instead, they often appear in pairs in which a meaningful action may be performed between them, such as a pitcher and a cup. Indeed, previous behavioral studies have demonstrated that positioning action-related object pairs in familiar action colocations facilitate recognition in contrast to unfamiliar colocation. And such benefit only appears in contextually congruent but not contextually incongruent pairs. In the current study, we manipulated contextual congruency, colocation, and the action state of one of the objects in the pair. For the congruency manipulation, a pair of objects could be either contextually congruent (e.g. a pitcher and a cup) or incongruent (e.g. a pitcher and a nail). For the colocation manipulation, a pair of objects could appear either in a familiar action colocation (e.g. a pitcher pointed towards a cup), an unfamiliar action colocation (a pitcher pointed away from a cup), and a nonaction colocation (a pitcher and a cup appeared side by side). For the action state manipulation, in some of the object pairs, the action-conducting object could be either active (e.g. a pair of opened scissors) or inactive (e.g. a pair of closed scissors). Behavioral response time on judging whether two objects go together was collected. Preliminary results showed faster judgment time for congruent pairs in familiar action colocations than both congruent pairs in unfamiliar action colocations and nonaction colocations. Additionally, active objects facilitated judgment more than inactive ones. These results replicated and extended previous behavioral findings, suggesting possibly stronger integration between the congruent objects in familiar action colocations. Using fMRI multi-voxel pattern analysis, we will next examine where in the ventral and dorsal visual processing.
Meeting abstract presented at VSS 2016
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