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Dynamical, self-organizing models of sentence processing predict "digging-in" effects: The more committed the parser becomes to a wrong syntactic choice, the harder it is to reanalyze. Experiment 1 replicates previous grammaticality judgment studies (F. Ferreira & J. M. Henderson, 1991b, 1993), revealing a deleterious effect of lengthening the ambiguous region of a garden-path sentence. The authors interpret this result as a digging-in effect. Experiment 2 finds a corresponding effect on reading times. Experiment 3 finds that making 2 wrong attachments is worse than making 1. Non-self-organizing models require multiple stipulations to predict both kinds of effects. The authors show that, under an appropriately formulated self-organizing account, both results stem from self-reinforcement of node and link activations, a feature that is needed independently. An implemented model is given.

This study is part of a broader project aimed at developing cognitive and neurocognitive profiles of adolescent and young adult readers whose educational and occupational prospects are constrained by their limited literacy skills. We explore the relationships among reading-related abilities in participants ages 16 to 24 years spanning a wide range of reading ability. Two specific questions are addressed: (a) Does the simple view of reading capture all nonrandom variation in reading comprehension? (b) Does orally assessed vocabulary knowledge account for variance in reading comprehension, as predicted by the lexical quality hypothesis? A comprehensive battery of cognitive and educational tests was employed to assess phonological awareness, decoding, verbal working memory, listening comprehension, reading comprehension, word knowledge, and experience with print. In this heterogeneous sample, decoding ability clearly played an important role in reading comprehension. The simple view of reading gave a reasonable fit to the data, although it did not capture all of the reliable variance in reading comprehension as predicted. Orally assessed vocabulary knowledge captured unique variance in reading comprehension even after listening comprehension and decoding skill were accounted for. We explore how a specific connectionist model of lexical representation and lexical access can account for these findings.

Gough and Tunmer’s (1986) simple view of reading (SVR) proposed that reading comprehension (RC) is a function of language comprehension (LC) and word recognition/decoding. Braze et al. (2007) presented data suggesting an extension of the SVR in which knowledge of vocabulary (V) affected RC over and above the effects of LC. Tunmer and Chapman (2012) found a similar independent contribution of V to RC when the data were analyzed by hierarchical regression. However, additional analysis by factor analysis and structural equation modeling indicated that the effect of V on RC was, in fact, completely captured by LC itself and there was no need to posit a separate direct effect of V on RC. In the present study, we present new data from young adults with sub-optimal reading skill (N = 286). Latent variable and regression analyses support Gough and Tunmer’s original proposal and the conclusions of Tunmer and Chapman that V can be considered a component of LC and not an independent contributor to RC.

Long-distance verb-argument dependencies generally require the integration of a fronted argument when the verb is encountered for sentence interpretation. Under a parsing model that handles long-distance dependencies through a cue-based retrieval mechanism, retrieval is hampered when retrieval cues also resonate with non-target elements (retrieval interference). However, similarity-based interference may also stem from interference arising during the encoding of elements in memory (encoding interference), an effect that is not directly accountable for by a cue-based retrieval mechanism. Although encoding and retrieval interference are clearly distinct at the theoretical level, it is difficult to disentangle the two on empirical grounds, since encoding interference may also manifest at the retrieval region. We report two self-paced reading experiments aimed at teasing apart the role of each component in gender and number subject-verb agreement in Italian and English object relative clauses. In Italian, the verb does not agree in gender with the subject, thus providing no cue for retrieval. In English, although present tense verbs agree in number with the subject, past tense verbs do not, allowing us to test the role of number as a retrieval cue within the same language. Results from both experiments converge, showing similarity-based interference at encoding, and some evidence for an effect at retrieval. After having pointed out the non-negligible role of encoding in sentence comprehension, and noting that Lewis and Vasishth’s (2005) ACT-R model of sentence processing, the most fully developed cue-based retrieval approach to sentence processing does not predict encoding effects, we propose an augmentation of this model that predicts these effects. We then also propose a self-organizing sentence processing model (SOSP), which has the advantage of accounting for retrieval and encoding interference with a single mechanism.

Functional magnetic resonance imaging (fMRI) was used to investigate the impact of literacy skills in young adults on the distribution of cerebral activity during comprehension of sentences in spoken and printed form. The aim was to discover where speech and print streams merge, and whether their convergence is affected by the level of reading skill. The results from different analyses all point to the conclusion that neural integration of sentence processing across speech and print varies positively with the reader's skill. Further, they identify the inferior frontal region as the principal site of speech-print integration and a major focus of reading comprehension differences. The findings provide new evidence of the role of the inferior frontal region in supporting supramodal systems of linguistic representation.

Psycholinguistic research spanning a number of decades has produced diverging results with regard to the nature of constraint integration in online sentence processing. For example, evidence that language users anticipatorily fixate likely upcoming referents in advance of evidence in the speech signal supports rapid context integration. By contrast, evidence that language users activate representations that conflict with contextual constraints, or only indirectly satisfy them, supports non-integration or late integration. Here, we report on a self-organizing neural network framework that addresses one aspect of constraint integration: the integration of incoming lexical information (i.e., an incoming word) with sentence context information (i.e., from preceding words in an unfolding utterance). In two simulations, we show that the framework predicts both classic results concerned with lexical ambiguity resolution (Swinney, 1979; Tanenhaus, Leiman, & Seidenberg, 1979), which suggest late context integration, and results demonstrating anticipatory eye movements (e.g., Altmann & Kamide, 1999), which support rapid context integration. We also report two experiments using the visual world paradigm that confirm a new prediction of the framework. Listeners heard sentences like “The boy will eat the white…,” while viewing visual displays with objects like a white cake (i.e., a predictable direct object of “eat”), white car (i.e., an object not predicted by “eat,” but consistent with “white”), and distractors. Consistent with our simulation predictions, we found that while listeners fixated white cake most, they also fixated white car more than unrelated distractors in this highly constraining sentence (and visual) context.