Investigating neural mechanisms underlying bias towards statistical regularities

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dc.contributor.advisorBouwkamp, Floortje
dc.contributor.advisorLange, de, Floris
dc.contributor.authorBleser, Anna
dc.date.issued2022-08-29
dc.description.abstractThe world is highly regular. Humans are particularly skilled in extracting and learning these regularities to subsequently use them to their benefit. Previous research has shown that regularities themselves seem to draw attention facilitating the statistical learning process. The present study investigated the neural mechanisms behind such an attentional bias using rapid invisible frequency tagging (RIFT). Participants watched two rapidly presented streams of images (one structured, one random) which were tagged at different frequencies. Statistical learning was assessed using both behavioral measures as well as an online frequency tagging measure. Participants did not show an attentional bias towards structure and there was no indication of statistical learning at the neural level nor in the behavioral data showing that attention is necessary but not sufficient for learning to take place. Keywords: Statistical learning, Rapid Invisible Frequency tagging, attentional capture, spatial attention
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/14764
dc.language.isoen
dc.thesis.facultyFaculteit der Sociale Wetenschappen
dc.thesis.specialisationspecialisations::Faculteit der Sociale Wetenschappen::Researchmaster Cognitive Neuroscience::Researchmaster Cognitive Neuroscience
dc.thesis.studyprogrammestudyprogrammes::Faculteit der Sociale Wetenschappen::Researchmaster Cognitive Neuroscience
dc.thesis.typeResearchmaster
dc.titleInvestigating neural mechanisms underlying bias towards statistical regularities
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