Sentence comprehension before and after 1970: Topics, debates and techniques

[EN] Language Down the Garden Path traces the lines of research that grew out of Bever's classic paper. Leading scientists review over 40 years of debates on the factors at play in language comprehension, production, and acquisition (the role of prediction, grammar, working memory, prosody, abstractness, syntax and semantics mapping); the current status of universals and narrow syntax; and virtually every topic relevant in psycholinguistics since 1970. Written in an accessible and engaging style, the book will appeal to all those interested in understanding the questions that shaped, and are still shaping, this field and the ways in which linguists, cognitive scientists, psychologists, and neuroscientists are seeking to answer them

Some , And Possibly All, Scalar Inferences Are Not Delayed: Evidence For Immediate Pragmatic Enrichment

Scalar inferences are commonly generated when a speaker uses a weaker expression rather than a stronger alternative, e.g., John ate some of the apples implies that he did not eat them all. This article describes a visual-world study investigating how and when perceivers compute these inferences. Participants followed spoken instructions containing the scalar quantifier some directing them to interact with one of several referential targets (e.g., Click on the girl who has some of the balloons). Participants fixated on the target compatible with the implicated meaning of some and avoided a competitor compatible with the literal meaning prior to a disambiguating noun. Further, convergence on the target was as fast for some as for the non-scalar quantifiers none and all. These findings indicate that the scalar inference is computed immediately and is not delayed relative to the literal interpretation of some. It is argued that previous demonstrations that scalar inferences increase processing time are not necessarily due to delays in generating the inference itself, but rather arise because integrating the interpretation of the inference with relevant information in the context may require additional time. With sufficient contextual support, processing delays disappear

Multiple code activation in word recognition: Evidence from rhyme monitoring

Seidenberg and Tanenhaus (1979) reported that orthographically similar rhymes were detected more rapidly than dissimilar rhymes in a rhyme monitoring task with auditory stimulus presentation. The present experiments investigated the hypothesis that these results were due to a rhyme production-frequency bias in favor of similar rhymes that was present in their materials. In three experiments, subjects monitored short word lists for the word that rhymed with a cue presented prior to each list. All stimuli were presented auditorily. Cue-target rhyme production frequency was equated for orthographically similar and dissimilar rhymes. Similar rhymes were detected more rapidly in all three experiments, indicating that orthographic information was accessed in auditory word recognition. The results suggest that multiple codes are automatically accessed in word recognition. This entails a reinterpretation of phonological "recoding" in visual word recognition

Weak definites as a form of definiteness: experimental investigations

Definite noun phrases typically refer to entities that are uniquely identifiable in the speaker and addressee’s common ground. However, some definite noun phrases (e.g. the hospital in Mary had to go the hospital and John did too) seem to violate uniqueness. We discuss a series of experiments that seek to understand some of the properties of this class of definites. We consider most carefully the hypothesis that these “weak definite” interpretations arise in implicitly “incorporated” constructions, attempting to provide a sketch of this hypothesis’ motivation and potential consequences. In our experiments we found that compared to regular definites, the weak definites need not refer uniquely, and readily trigger semantically enriched readings that compete effectively with normal inferences one might draw from a sentence. Perhaps the most surprising finding in the experiments is that nouns that could occur as weak definites, also seemed to retain some of these “weak” properties even when expressed as indefinites. We try and make sense of this within the “incorporation” framework.De façon typique, les groupes nominaux définis réfèrent à une entité identifiable et unique, appartenant au Common Ground du locuteur et de l’interlocuteur. Cependant, il y a des groupes nominaux définis (comme l’hôpital dans Marie est allée à l’hôpital et Jean aussi) qui semblent violer la contrainte d’unicité. Nous présentons une série d’expériences qui portent sur cette classe de définis. Nous considérons très attentivement l’hypothèse selon laquelle les interprétations « faibles » apparaissent dans des constructions implicitement « incorporés » et nous tentons de donner un début d’explication pour motiver cette hypothèse et mesurer ses conséquences. Nos expériences montrent que, comparés aux définis standard, les définis faibles n’ont pas besoin de référer de façon unique et sont très facilement associés à une lecture enrichie sémantiquement qui entre en concurrence avec les inférences normales qu’on pourrait tirer d’une telle phrase. Le résultat sans doute le plus surprenant de nos expériences est que les noms qui peuvent donner lieu à des lectures faibles semblent conserver certaines des propriétés caractéristiques des lectures faibles même quand ils sont utilisés dans des groupes nominaux indéfinis. Nous essayons d’expliquer cela en termes d’incorporation

Effects of Probabilistic Contingencies on Word Processing in an Artificial Lexicon

Artificial lexicons have been used with eye-tracking to study the integration of contextual (top-down) and bottom-up information in lexical processing. The present study utilized these techniques to study the role of probabilistic information in lexical processing. Participants were trained to associate novel nouns and modifiers, with certain combinations occurring more frequently than others. Participants heard a modifier-noun phrase and were asked to select the words in a display. We predicted that participants would make anticipatory eye movements to nouns based on the probabilities they previously learned. While no anticipatory effects were found, delayed effects consistent with our predictions were found

Autoreceptor Control of Peptide/Neurotransmitter Corelease from PDF Neurons Determines Allocation of Circadian Activity in Drosophila

SummaryDrosophila melanogaster flies concentrate behavioral activity around dawn and dusk. This organization of daily activity is controlled by central circadian clock neurons, including the lateral-ventral pacemaker neurons (LNvs) that secrete the neuropeptide PDF (pigment dispersing factor). Previous studies have demonstrated the requirement for PDF signaling to PDF receptor (PDFR)-expressing dorsal clock neurons in organizing circadian activity. Although LNvs also express functional PDFR, the role of these autoreceptors has remained enigmatic. Here, we show that (1) PDFR activation in LNvs shifts the balance of circadian activity from evening to morning, similar to behavioral responses to summer-like environmental conditions, and (2) this shift is mediated by stimulation of the Gα,s-cAMP pathway and a consequent change in PDF/neurotransmitter corelease from the LNvs. These results suggest another mechanism for environmental control of the allocation of circadian activity and provide new general insight into the role of neuropeptide autoreceptors in behavioral control circuits

Inferring Difficulty: Flexibility in the Real-time Processing of Disfluency

Upon hearing a disfluent referring expression, listeners expect the speaker to refer to an object that is previously-unmentioned, an object that does not have a straightforward label, or an object that requires a longer description. Two visual-world eye-tracking experiments examined whether listeners directly associate disfluency with these properties of objects, or whether disfluency attribution is more flexible and involves situation-specific inferences. Since in natural situations reference to objects that do not have a straightforward label or that require a longer description is correlated with both production difficulty and with disfluency, we used a mini artificial lexicon to dissociate difficulty from these properties, building on the fact that recently-learned names take longer to produce than existing words in one’s mental lexicon. The results demonstrate that disfluency attribution involves situation-specific inferences; we propose that in new situations listeners spontaneously infer what may cause production difficulty. However, the results show that these situation-specific inferences are limited in scope: listeners assessed difficulty relative to their own experience with the artificial names, and did not adapt to the assumed knowledge of the speaker

Acquiring and processing verb argument structure : distributional learning in a miniature language

Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings