An Interference Model for Visual and Verbal Working Memory

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Bibliographic Details
Title: An Interference Model for Visual and Verbal Working Memory
Language: English
Authors: Klaus Oberauer (ORCID 0000-0003-3902-7318), Hsuan-Yu Lin
Source: Journal of Experimental Psychology: Learning, Memory, and Cognition. 2024 50(6):858-888.
Availability: American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org
Peer Reviewed: Y
Page Count: 31
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, College Students, Short Term Memory, Visual Learning, Verbal Learning, Interference (Learning), Recall (Psychology), Serial Ordering, Sample Size
Geographic Terms: Switzerland
DOI: 10.1037/xlm0001303
ISSN: 0278-7393
1939-1285
Abstract: Research on working memory (WM) has followed two largely independent traditions: One concerned with memory for sequentially presented lists of discrete items, and the other with short-term maintenance of simultaneously presented arrays of objects with simple, continuously varying features. Here we present a formal model of WM, the interference model (IM), that explains benchmark findings from both traditions: The shape of the error distribution from continuous reproduction of visual features, and how it is affected by memory set size; the effects of serial position for sequentially presented items, the effect of output position, and the intrusion of nontargets as a function of their distance from the target in space and in time. We apply the model to two experiments combining features of popular paradigms from both traditions: Lists of colors (Experiment 1) or of nonwords (Experiment 2) are presented sequentially and tested through selection of the target from a set of candidates, ordered by their similarity. The core assumptions of the IM are: Contents are encoded into WM through temporary bindings to contexts that serve as retrieval cues to access the contents. Bindings have limited precision on the context and the content dimension. A subset of the memory set--usually one item and its context--is maintained in a focus of attention with high precision. Successive events in an episode are encoded with decreasing strength, generating a primacy gradient. With each encoded event, automatic updating of WM reduces the strength of preceding memories, creating a recency gradient and output interference.
Abstractor: As Provided
Notes: https://osf.io/znqmw
Entry Date: 2024
Accession Number: EJ1430668
Database: ERIC
Description
Abstract:Research on working memory (WM) has followed two largely independent traditions: One concerned with memory for sequentially presented lists of discrete items, and the other with short-term maintenance of simultaneously presented arrays of objects with simple, continuously varying features. Here we present a formal model of WM, the interference model (IM), that explains benchmark findings from both traditions: The shape of the error distribution from continuous reproduction of visual features, and how it is affected by memory set size; the effects of serial position for sequentially presented items, the effect of output position, and the intrusion of nontargets as a function of their distance from the target in space and in time. We apply the model to two experiments combining features of popular paradigms from both traditions: Lists of colors (Experiment 1) or of nonwords (Experiment 2) are presented sequentially and tested through selection of the target from a set of candidates, ordered by their similarity. The core assumptions of the IM are: Contents are encoded into WM through temporary bindings to contexts that serve as retrieval cues to access the contents. Bindings have limited precision on the context and the content dimension. A subset of the memory set--usually one item and its context--is maintained in a focus of attention with high precision. Successive events in an episode are encoded with decreasing strength, generating a primacy gradient. With each encoded event, automatic updating of WM reduces the strength of preceding memories, creating a recency gradient and output interference.
ISSN:0278-7393
1939-1285
DOI:10.1037/xlm0001303