NCCLNov 27, 2016

A theory of interpretive clustering in free recall

arXiv:1611.08928v2
Originality Incremental advance
AI Analysis

This work addresses memory research by providing a model for free-recall phenomena, though it appears incremental as it builds on existing theories and data.

The authors tackled the problem of modeling short-term verbal memory by proposing a stochastic diffusion model on a semantic graph, which predicts a novel relationship between the contiguity effect and syllabic length, confirmed through analysis of archival data.

A stochastic model of short-term verbal memory is proposed, in which the psychological state of the subject is encoded as the instantaneous position of a particle diffusing over a semantic graph with a probabilistic structure. The model is particularly suitable for studying the dependence of free-recall observables on semantic properties of the words to be recalled. Besides predicting some well-known experimental features (contiguity effect, forward asymmetry, word-length effect), a novel prediction is obtained on the relationship between the contiguity effect and the syllabic length of words; shorter words, by way of their wider semantic range, are predicted to be characterized by stronger forward contiguity. A fresh analysis of archival data allows to confirm this prediction.

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