September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Visual statistical learning provides scaffolding for emerging object representations
Author Affiliations
  • Jozsef Fiser
    Department of Cognitive Science, Central European University, Hungary
  • Gabor Lengyel
    Department of Cognitive Science, Central European University, Hungary
  • Marton Nagy
    Department of Cognitive Science, Central European University, Hungary
Journal of Vision August 2017, Vol.17, 39. doi:10.1167/17.10.39
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      Jozsef Fiser, Gabor Lengyel, Marton Nagy; Visual statistical learning provides scaffolding for emerging object representations. Journal of Vision 2017;17(10):39. doi: 10.1167/17.10.39.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Although an abundance of studies demonstrated human's abilities for visual statistical learning (VSL), much fewer studies focused on the consequences of VSL. Recent papers reported that attention is biased toward detected statistical regularities, but this observation was restricted to spatial locations and provided no functional interpretation of the phenomenon. We tested the idea that statistical regularities identified by VSL constrain subsequent visual processing by coercing further processing to be compatible with those regularities. Our paradigm used the well-documented fact that within-object processing has an advantage over across-object processing. We combined the standard VSL paradigm with a visual search task in order to assess whether participants detect a target better within a statistical chunk than across chunks. Participants (N=11) viewed 4-4 alternating blocks of "observation" and "search" trials. In both blocks, complex multi-shape visual scenes were presented, which unbeknownst to the participants, were built from pairs of abstract shapes without any clear segmentation cues. Thus, the visual chunks (pairs of shapes) generating the scenes could only be extracted by tracking the statistical contingencies of shapes across scenes. During "observation", participants just passively observed the visual scenes, while during "search", they performed a 3-AFC task deciding whether T letters appearing in the middle of the shapes formed a horizontal or vertical pairs. Despite identical distance between the target letters, participants performed significantly better in trials in which targets appeared within a visual chunk than across two chunks or across a chunk and a single shape. These results suggest that similar to object-defined within/between relations, statistical contingencies learned implicitly by VSL facilitate visual processing of elements that belong to the same statistical chunk. This similarity between the effects of true objects and statistical chunks support the notion that VSL has a central role in the emergence of internal object representations.

Meeting abstract presented at VSS 2017

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