Overshadowing between visual and tactile stimulus elements in an object recognition task

•Human participants recognized objects more readily at test after having had unimodal, rather than multimodal, training.•Human participants perform better on object recognition when given a visual, rather than haptic, test.•Results correspond to the well-established learning phenomenon of overshadow...

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Bibliographic Details
Published inBehavioural processes Vol. 157; pp. 102 - 105
Main Authors Stahlman, W. David, McWaters, Mercedes, Christian, Erica, Knapp, Eric, Fritch, Andrea, Mailloux, Jennifer R.
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.12.2018
Elsevier Science Ltd
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Summary:•Human participants recognized objects more readily at test after having had unimodal, rather than multimodal, training.•Human participants perform better on object recognition when given a visual, rather than haptic, test.•Results correspond to the well-established learning phenomenon of overshadowing. In recent decades there has been great progress in discovering the conditions under which cue competition occurs during animal learning. In humans, however, the evidence remains equivocal regarding the degree to which stimuli compete with one another for behavioral control. We report here the results of a single experiment wherein thirty-nine college students completed a novel cue competition task with visual and tactile stimuli. Participants visually and/or haptically examined a series of novel objects. They were then asked to select the objects with which they had interacted from a larger pool of both novel and familiar objects. Potentiation (or facilitation) by simultaneous visual and haptic inspection was possible. Alternatively, stimulus elements may have competed with one another (i.e., overshadowing), which would present as poorer recognition at test for objects to which participants had simultaneous, dual-modality training exposure. We report the latter effect. We situate these findings in the broader context of associative learning and suggest that our data is relevant to applied settings.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0376-6357
1872-8308
DOI:10.1016/j.beproc.2018.08.008