Encoding specificity instead of online integration of real-world spatial regularities for objects in working memory
Liu, X., Liu, R., Guo, L., Astikainen, P., & Ye, C. (2022). Encoding specificity instead of online integration of real-world spatial regularities for objects in working memory. Journal of Vision, 22(9), Article 8. https://doi.org/10.1167/jov.22.9.8
Published inJournal of Vision
© 2022 the Authors
Most objects show high degrees of spatial regularity (e.g. beach umbrellas appear above, not under, beach chairs). The spatial regularities of real-world objects benefit visual working memory (VWM), but the mechanisms behind this spatial regularity effect remain unclear. The “encoding specificity” hypothesis suggests that spatial regularity will enhance the visual encoding process but will not facilitate the integration of information online during VWM maintenance. The “perception-alike” hypothesis suggests that spatial regularity will function in both visual encoding and online integration during VWM maintenance. We investigated whether VWM integrates sequentially presented real-world objects by focusing on the existence of the spatial regularity effect. Throughout five experiments, we manipulated the presentation (simultaneous vs. sequential) and regularity (with vs. without regularity) of memory arrays among pairs of real-world objects. The spatial regularity of memory objects presented simultaneously, but not sequentially, improved VWM performance. We also examined whether memory load, verbal suppression and masking, and memory array duration hindered the spatial regularity effect in sequential presentation. We found a stable absence of the spatial regularity effect, suggesting that the participants were unable to integrate real-world objects based on spatial regularities online. Our results support the encoding specificity hypothesis, wherein the spatial regularity of real-world objects can enhance the efficiency of VWM encoding, but VWM cannot exploit spatial regularity to help organize sampled sequential information into meaningful integrations. ...
PublisherAssociation for Research in Vision and Ophthalmology (ARVO)
Dataset(s) related to the publicationhttps://osf.io/ctmpr/
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Postdoctoral Researcher, AoF
Additional information about fundingSupported by grants from the National Natural Science Foundation of China (NSFC 31700948), and the Academy of Finland (no. 333649 to Chaoxiong Ye).
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