Episodic source memory over distribution by quantum-like dynamics -- a model exploration
Jan Broekaert, Jerome Busemeyer

TL;DR
This paper extends a quantum-like model of episodic source memory using Hamiltonian dynamics to explain over distribution effects observed in memory experiments, accurately predicting acceptance probabilities.
Contribution
It introduces a Hamiltonian dynamical extension to the quantum episodic memory model, capturing the over distribution phenomenon in source memory tasks.
Findings
Model predicts acceptance probabilities accurately
Explains over distribution in source memory
Aligns with experimental data
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 (2013) to explain this type of result. In this paper, we apply…
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