Reducing Noise from Competing Neighbours: Word Retrieval with Lateral Inhibition in Multilink
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2019-11-06
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en
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Abstract
Multilink is a computational model for word retrieval in monolingual and multilingual individuals
under different task circumstances (Dijkstra et al., 2018). In the present study, we added lateral inhibition
to Multilink’s lexical network. Parameters were fit on the basis of reaction times from the
English, British, and Dutch Lexicon Projects. We found a maximum correlation of 0.643 (N=1,205)
on these data sets as a whole. Futhermore, the simulations themselves became faster as a result of
adding lateral inhibition. We tested the fitted model to stimuli from a neighbourhood study (Mulder
et al., 2018). Lateral inhibition was found to improve Multilink’s correlations for this study, yielding
an overall correlation of 0.67.
Next, we explored the role of lateral inhibition as part of the model’s task/decision system by
running simulations on data from two studies concerning interlingual homographs (Vanlangendonck
et al., in press; Goertz, 2018). We found that, while lateral inhibition plays a substantial part in the
word selection process, this alone is not enough to result in a correct response selection. To solve
this problem, we added a new task component to Multilink, especially designed to account for the
translation process of interlingual homographs, cognates, and language-specific control words. The
subsequent simulation results showed patterns remarkably similar to those in the Goertz study. The
isomorphicity of the simulated data to the empirical data was further attested by an overall correlation
of 0.538 (N=254) between reaction times and simulated model cycle times, as well as a condition
pattern correlation of 0.853 (N=8).
We conclude that Multilink yields an excellent fit to empirical data, particularly when a taskspecific
setting of the inhibition parameters is allowed.
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Faculteit der Sociale Wetenschappen