Revisiting mixture models of memory

Blaire Dube and Julie D. Golomb ()
Additional contact information
Blaire Dube: The Ohio State University
Julie D. Golomb: The Ohio State University

Nature Human Behaviour, 2020, vol. 4, issue 11, 1098-1099

Abstract: Probabilistic mixture models have contributed significantly to advancements in visual working memory research in recent decades. In a new paper, Schurgin and colleagues revisit the basic assumptions of mixture models and suggest that we cannot understand memory without first considering perception.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41562-020-00947-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nathum:v:4:y:2020:i:11:d:10.1038_s41562-020-00947-z

Ordering information: This journal article can be ordered from
https://www.nature.com/nathumbehav/

DOI: 10.1038/s41562-020-00947-z

Access Statistics for this article

Nature Human Behaviour is currently edited by Stavroula Kousta

More articles in Nature Human Behaviour from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().