NDRA: A single route model of response times in the reading aloud task based on discriminative learning.

Peter Hendrix,Harald Baayen,Michael Ramscar,Claudio Mulatti

doi:10.1371/journal.pone.0218802

Abstract

We present the Naive Discriminative Reading Aloud (ndra) model. The ndra differs from existing models of response times in the reading aloud task in two ways. First, a single lexical architecture is responsible for both word and non-word naming. As such, the model differs from dual-route models, which consist of both a lexical route and a sub-lexical route that directly maps orthographic units onto phonological units. Second, the linguistic core of the ndra exclusively operates on the basis of the equilibrium equations for the well-established general human learning algorithm provided by the Rescorla-Wagner model. The model therefore does not posit language-specific processing mechanisms and avoids the problems of psychological and neurobiological implausibility associated with alternative computational implementations. We demonstrate that the single-route discriminative learning architecture of the ndra captures a wide range of effects documented in the experimental reading aloud literature and that the overall fit of the model is at least as good as that of state-of-the-art dual-route models.

Highlights

Both Coltheart et al [1] and Perry et al [2] open what have become canonical papers in the reading literature with the observation that tremendous advances have been made in the development of reading models over the last decades
Naive Discriminative Reading Aloud (NDRA): A single route model of reading aloud based on discriminative learning than that proposed by Seidenberg et al [84], in the sense that we considered non-word pronunciations as correct if and only if the orthography-to-phonology mapping for the onset, vowel and coda existed for a monosyllabic word in CELEX
We presented the NDRA, a single-route model of response times in the reading aloud task based on the fundamental principles of discriminative learning

Summary

Introduction

Both Coltheart et al [1] and Perry et al [2] open what have become canonical papers in the reading literature with the observation that tremendous advances have been made in the development of reading models over the last decades. They note that early cognitive models in psychology provided mainly verbal descriptions of hypothesized cognitive architectures These models took the form of flowchart diagrams in which boxes were used to depict mental representations, which were manipulated by cognitive processes represented as arrows that connected the various boxes (see Morton [3] for an application of box-and-arrow models to reading). Such “verbal” models provide descriptions of behavioral data, their lack of specificity meant that they could only be related to the psychological and neurobiological reality of language processing at a very abstract level.

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