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A Psychometric PDP Model of Temporal Structure in Story Recall
Abstract
A new parallel distributed processing (PDP) model possessing a statistical interpretation is proposed for ex- tracting critical psychological regularities from the tem- poral structure of human free recall data. The model is essentially a non-linear five parameter Jordan sequen- tial network for predicting categorical time-series data. T h e model consists of five parameters: an episodic strength parameter (t/), a causal strength parameter {0), a shared causal/episodic strength parameter (7), a work- ing memory span parameter (//), and a number of items recalled parameter (A). T h e "psychological validity" of the model's parameter estimates were then evaluated with respect to the existing experimental literature us- ing children and adult free recall data from four stories. The model's parameter estimates replicated and ex- tended several previously known experimental findings. In particular, the model showed: (i) effects of causal structure /3, (ii) showed a decrease in (7/4-7) while /? remained constant as retention interval increased, and (iii) an increase in {r]+y) whileftremained constant as subject age increased.
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