Modelling Emotional Memory in Children with Tensor Networks
Organizations: Quantum Group, School of Computing, Newcastle University, Science Square, Newcastle upon Tyne, NE4 5TG, UK · School of Psychology, Newcastle University, Wallace Street, Newcastle upon Tyne, NE2 4DR, UK · Biosciences Institute, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
Abstract
We demonstrate how emotional valence influences the order-dependent structure of children's recognition memory: correct recall of a sequence of emotionally-valenced toys depended not just on the valence of a given toy itself, but also on the valence of the toys shown before and after it. Whilst standard psychological models confirm that order-dependence differs across an event (a set of toys shown in sequence), accuracy is low and the model does not reflect how memory for an emotional object influences others in the set. A classical tensor network model factoring in valence is able to achieve a 77.98% accuracy in modelling the results of the study. While not strictly a ``quantum cognition'' model, this massive increase in accuracy shows the value of quantum-inspired methods for modelling order-dependent phenomena, such as emotional memory. Further, the task protocol we introduce presents a novel, real-world tool for exploring emotional temporal memory in children for analysis using classical and quantum-like models of cognition.