Literature DB >> 22527527

A power-law model of psychological memory strength in short- and long-term recognition.

Chris Donkin1, Robert M Nosofsky.   

Abstract

A classic law of cognition is that forgetting curves are closely approximated by power functions. This law describes relations between different empirical dependent variables and the retention interval, and the precise form of the functional relation depends on the scale used to measure each variable. In the research reported here, we conducted a recognition task involving both short- and long-term probes. We discovered that formal memory-strength parameters from an exemplar-recognition model closely followed a power function of the lag between studied items and a test probe. The model accounted for rich sets of response time (RT) data at both individual-subject and individual-lag levels. Because memory strengths were derived from model fits to choices and RTs from individual trials, the psychological power law was independent of the scale used to summarize the forgetting functions. Alternative models that assumed different functional relations or posited a separate fixed-strength working memory store fared considerably worse than the power-law model did in predicting the data.

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Mesh:

Year:  2012        PMID: 22527527     DOI: 10.1177/0956797611430961

Source DB:  PubMed          Journal:  Psychol Sci        ISSN: 0956-7976


  11 in total

Review 1.  The structure of short-term memory scanning: an investigation using response time distribution models.

Authors:  Chris Donkin; Robert M Nosofsky
Journal:  Psychon Bull Rev       Date:  2012-06

2.  Real and implied motion at the center of gaze.

Authors:  Alper Açik; Andreas Bartel; Peter König
Journal:  J Vis       Date:  2014-01-06       Impact factor: 2.240

3.  Location-based errors in change detection: A challenge for the slots model of visual working memory.

Authors:  Chris Donkin; Sophia Chi Tran; Mike Le Pelley
Journal:  Mem Cognit       Date:  2015-04

4.  Discrete-slots models of visual working-memory response times.

Authors:  Christopher Donkin; Robert M Nosofsky; Jason M Gold; Richard M Shiffrin
Journal:  Psychol Rev       Date:  2013-09-09       Impact factor: 8.934

5.  Item frequency in probe-recognition memory search: Converging evidence for a role of item-response learning.

Authors:  Rui Cao; Richard M Shiffrin; Robert M Nosofsky
Journal:  Mem Cognit       Date:  2018-04

6.  Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons.

Authors:  Sanjeev Kumar Sharma; Argha Mondal; Arnab Mondal; Ranjit Kumar Upadhyay; Chittaranjan Hens
Journal:  J R Soc Interface       Date:  2020-06-24       Impact factor: 4.118

7.  Working memory retrieval as a decision process.

Authors:  Benjamin Pearson; Julius Raskevicius; Paul M Bays; Yoni Pertzov; Masud Husain
Journal:  J Vis       Date:  2014-02-03       Impact factor: 2.240

Review 8.  Memory as Perception of the Past: Compressed Time inMind and Brain.

Authors:  Marc W Howard
Journal:  Trends Cogn Sci       Date:  2018-02       Impact factor: 20.229

9.  Time-conjunctive representations of future events.

Authors:  Stuart W Babcock; Marc W Howard; Joseph T McGuire
Journal:  Mem Cognit       Date:  2020-05

10.  Quantitative linking hypotheses for infant eye movements.

Authors:  Daniel Yurovsky; Shohei Hidaka; Rachel Wu
Journal:  PLoS One       Date:  2012-10-26       Impact factor: 3.240

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