Stimulus variability and task relevance modulate binding-learning

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dc.contributor.author George, Nithin
dc.contributor.author Egner, Tobias
dc.coverage.spatial Switzerland
dc.date.accessioned 2012-09-26T07:22:35Z
dc.date.available 2012-09-26T07:22:35Z
dc.date.issued 2021-07
dc.identifier.citation George, Nithin and Egner, Tobias, "Stimulus variability and task relevance modulate binding-learning", Attention, Perception, & Psychophysics, DOI: 10.3758/s13414-021-02338-6, Jul. 2021. en_US
dc.identifier.issn 1943-3921
dc.identifier.issn 1943-393X
dc.identifier.uri https://doi.org/10.3758/s13414-021-02338-6
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/6750
dc.description.abstract Classical theories of attention posit that integration of features into object representation (or feature binding) requires engagement of focused attention. Studies challenging this idea have demonstrated that feature binding can happen outside of the focus of attention for familiar objects, as well as for arbitrary color-orientation conjunctions. Detection performance for arbitrary feature conjunction improves with training, suggesting a potential role of perceptual learning mechanisms in the integration of features, a process called “binding-learning”. In the present study, we investigate whether stimulus variability and task relevance, two critical determinants of visual perceptual learning, also modulate binding-learning. Transfer of learning in a visual search task to a pre-exposed color-orientation conjunction was assessed under conditions of varying stimulus variability and task relevance. We found transfer of learning for the pre-exposed feature conjunctions that were trained with high variability (Experiment 1). Transfer of learning was not observed when the conjunction was rendered task-irrelevant during training due to pop-out targets (Experiment 2). Our findings show that feature binding is determined by principles of perceptual learning, and they support the idea that functions traditionally attributed to goal-driven attention can be grounded in the learning of the statistical structure of the environment.
dc.description.statementofresponsibility by Nithin George and Tobias Egner
dc.language.iso en_US en_US
dc.publisher Springer Nature en_US
dc.subject Feature binding en_US
dc.subject Perceptual learning en_US
dc.subject Habitual attention en_US
dc.subject Visual search en_US
dc.subject Variability en_US
dc.title Stimulus variability and task relevance modulate binding-learning en_US
dc.type Article en_US
dc.relation.journal Attention, Perception, and Psychophysics


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