Ensemble coding of memory strength in recognition tests

4Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Recent work by Benjamin and colleagues (Psychological Review, 116 (1), 84-115, 2009; Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(5), 1601-1608, 2013) suggests that recognition memory decisions are corrupted by random variability in decision criteria. This conclusion, which explains several anomalies in the recognition literature, was based on fits of the Noisy Decision Theory of Signal Detection (NDT) to a novel task: ensemble recognition. In the ensemble task, participants make Old/New decisions to ensembles of items rather than single items. The NDT assumption that criteria are fixed across ensembles was criticized by Kellen, Klauer, and Singmann (Psychological Review, 119 (3), 457-479, 2012), and defended by Benjamin (Psychological Review, 120, 720-726, 2013). Little attention, however, has been paid to the assumption of the best-fitting NDT model that participants solve the ensemble task by calculating the average memory strength of items in the probe display. We review evidence of summary statistical representation in visual perception and short-term memory that suggests the aggregation hypothesis is plausible, and hold it up to test in three experiments using the direct ratings procedure. Although we conclude that participants can produce estimates of average probe memory strength at test, in line with the assumptions of NDT, the mechanisms and strategies used to produce such estimates remain unclear.

Cite

CITATION STYLE

APA

Dubé, C., Tong, K., Westfall, H., & Bauer, E. (2019). Ensemble coding of memory strength in recognition tests. Memory and Cognition, 47(5), 936–953. https://doi.org/10.3758/s13421-019-00912-w

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free