Skip to main content

Towards a competitive learning model of mirror effects in yes/no recognition memory tests

Dietz, Kristina Charlotte, Bowman, Howard, Van Hooff, Johanna C. (2008) Towards a competitive learning model of mirror effects in yes/no recognition memory tests. In: Mayor, J. and Ruh, N. and Plunkett, K., eds. Connectionist models of behaviour and cognition II. Progress in Neural Processing (18). pp. 129-140. World Scientific: London ISBN 978-981-283-422-5. (KAR id:24112)

Language: English
Click to download this file (205kB)
[thumbnail of MirroreffectBowman.pdf]
This file may not be suitable for users of assistive technology.
Request an accessible format


Manipulations of encoding strength and stimulus class can lead to a simultaneous increase in hits and decrease in false alarms for a given condition in a yes/no recognition memory test. Based on signal detection theory, the strength-based `mirror effect' is thought to involve a shift in response criterion/threshold (Type I), whereas the stimulus class effect derives from a specific ordering of the memory strength signals for presented items (Type II). We implemented both suggested mechanisms in a simple, competitive feed-forward neural network model with a learning rule related to Bayesian inference. In a single-process approach to recognition, the underlying decision axis as well as the response criteria/thresholds were derived from network activation. Initial results replicated findings in the literature and are a first step towards a more neurally explicit model of mirror effects in recognition memory tests.

Item Type: Conference or workshop item (Paper)
Additional information: Proceedings of the 11th Neural Computation and Psychology Workshop (NCPW11), University of Oxford, UK, 16--18 July 2008
Uncontrolled keywords: mirror effect, recognition, memory models
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Kristina Dietz
Date Deposited: 29 Mar 2010 12:15 UTC
Last Modified: 16 Nov 2021 10:02 UTC
Resource URI: (The current URI for this page, for reference purposes)
Bowman, Howard:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.