Journal article

Likelihood ratio sequential sampling models of recognition memory

AF Osth, S Dennis, A Heathcote

Cognitive Psychology | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2017

Abstract

The mirror effect – a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates – is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance. Despite its central place in theorising about ..

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University of Melbourne Researchers

Grants

Awarded by Australian Research Council


Funding Acknowledgements

We would like to thank Jeff Starns and Amy Criss for generously providing their data, Matthew Gretton for coding up a Python wrapper for fast-DM, Brandon Turner for some indispensable advice on achieving convergence with hierarchical models, and Caren Rotello and two anonymous reviewers for providing very helpful comments on a previous version of this manuscript. This work was supported by a grant from the Australian Research Council, ARC DP150100272, awarded to Simon Dennis, Andrew Heathcote, and Vladimir Sloutsky.