Broekaert, JB orcid.org/0000-0002-4039-8514 and Busemeyer, JR (2019) Episodic Source Memory over Distribution by Quantum-Like Dynamics – A Model Exploration. In: Coecke, B and Lambert-Mogiliansky, A, (eds.) Lecture Notes in Computer Science. 11th International Symposium on Quantum Interaction (QI 2018), 03-05 Sep 2018, Nice, France. Springer Nature , pp. 63-75. ISBN 978-3-030-35894-5
Abstract
In source memory studies, a decision-maker is concerned with identifying the context in which a given episodic experience occurred. A common paradigm for studying source memory is the ‘three-list’ experimental paradigm, where a subject studies three lists of words and is later asked whether a given word appeared on one or more of the studied lists. Surprisingly, the sum total of the acceptance probabilities generated by asking for the source of a word separately for each list (‘list 1?’, ‘list 2?’, ‘list 3?’) exceeds the acceptance probability generated by asking whether that word occurred on the union of the lists (‘list 1 or 2 or 3?’). The episodic memory for a given word therefore appears over distributed on the disjoint contexts of the lists. A quantum episodic memory model [QEM] was proposed by Brainerd, Wang and Reyna [8] to explain this type of result. In this paper, we apply a Hamiltonian dynamical extension of QEM for over distribution of source memory. The Hamiltonian operators are simultaneously driven by parameters for re-allocation of gist-based and verbatim-based acceptance support as subjects are exposed to the cue word in the first temporal stage, and are attenuated for description-dependence by the querying probe in the second temporal stage. Overall, the model predicts well the choice proportions in both separate list and union list queries and the over distribution effect, suggesting that a Hamiltonian dynamics for QEM can provide a good account of the acceptance processes involved in episodic memory tasks.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2019. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Recognition memory; Over distribution; Quantum modeling; Word list; Verbatim; Gist |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Choice Modelling |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Mar 2020 13:49 |
Last Modified: | 11 Mar 2020 08:32 |
Status: | Published |
Publisher: | Springer Nature |
Identification Number: | 10.1007/978-3-030-35895-2_5 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158176 |