This study challenges the conventional psycholinguistic view that the distinction between nouns and verbs is pivotal in understanding language impairments in neurological disorders. Traditional views link frontal brain region damage with verb processing deficits and posterior temporoparietal damage with noun difficulties. However, this perspective is contested by findings from patients with Alzheimer’s disease (pwAD), who show impairments in both word classes despite their typical temporoparietal atrophy. Notably, pwAD tend to use semantically lighter verbs in their speech than healthy individuals. By examining English-speaking pwAD and comparing them with Persian-speaking pwAD, this research aims to demonstrate that language impairments in Alzheimer’s disease (AD) stem from the distributional properties of words within a language rather than distinct neural processing networks for nouns and verbs. We propose that the primary deficit in AD language production is an overreliance on high-frequency words. English has a set of particularly high-frequency verbs that surpass most nouns in usage frequency. Since pwAD tend to use high-frequency words, the byproduct of this word distribution in the English language would be an over-usage of high-frequency verbs. In contrast, Persian features complex verbs with an overall distribution lacking extremely high-frequency verbs like those found in English. As a result, we hypothesize that Persian-speaking pwAD would not have a bias toward the overuse of high-frequency verbs.

The current study marries two important observations. First, there is a growing recognition that word meanings need to be flexibly extended in new ways as new contexts arise. Second, as evidenced primarily within the perceptual domain, autistic individuals tend to find generalization more challenging while showing stronger veridical memory in comparison to their neurotypical peers. Here we report that a group of 80 autistic adults finds it more challenging to flexibly extend the meanings of familiar words in new ways than a group of 80 neurotypical peers, while the autistic individuals outperform the neurotypicals on a novel word-learning task that does not require flexible extension. Results indicate that recognized differences in generalization present an ongoing challenge for autistic adults in the domain of language, separate from social cognition, executive function, or the ability to assign single fixed meanings to new words.

The constructionist framework is more relevant than ever, due to efforts by a broad range of researchers across the globe, a steady increase in the use of corpus and experimental methods among linguists, consistent findings from laboratory phonology and sociolinguistics, and striking advances in transformer- based large language models. These advances promise exciting developments and a great deal more clarity over the next decade. The constructionist approach rests on two interrelated but distinguishable tenets: a recognition that constructions pair form with function at varying levels of specificity and abstraction, and the recognition that our knowledge and use of language are dynamic and usage based.

Adults learning a new language tend to judge unconventional utterances more leniently than fluent speakers do; ratings on acceptable utterances, however, tend to align more closely with fluent speakers. This asymmetry raises a question as to whether unconventional utterances can be statistically preempted by conventional utter- ances for adult learners. We report a preregistered study that provided undergraduates in Spanish classes with three days of exposure to conventional Spanish sentences without feedback. Judgment data reveal a significant effect of statistical preemption, particularly on intermediate learners, as predicted: Repeatedly witnessing conventional sentences led learners to subsequently judge as significantly lower the corresponding unconven- tional formulations in comparison to unrelated unconventional sentences. Current find- ings indicate that adult learners can take advantage of statistical preemption to learn the unacceptability of unconventional sentences from repeated exposure to acceptable alternatives, without explicit instruction or feedback.

Languages are powerful solutions to coordination problems: They provide stable, shared expectations about how the words we say correspond to the beliefs and intentions in our heads. Yet, language use in a variable and nonstationary social environment requires linguistic representations to be flexible: Old words acquire new ad hoc or partner-specific meanings on the fly. In this article, we introduce continual hierarchical adaptation through inference (CHAI), a hierarchical Bayesian theory of coordination and convention formation that aims to reconcile the long-standing tension between these two basic observations. We argue that the central computational problem of communication is not simply transmission, as in classical formulations, but continual learning andadaptation over multiple timescales. Partner-specific common ground quickly emerges from social inferences within dyadic interactions, while community-wide social conventions are stable priors that have been abstracted away from interactions with multiple partners. We present new empirical data alongside simulations showing how our model provides a computational foundation for several phenomena that have posed a challenge for previous accounts: (a) the convergence to more efficient referring expressions across repeated interaction with the same partner, (b) the gradual transfer of partner-specific common ground to strangers, and (c) the influence of communicative context on which conventions eventually form.

Each grammatical construction serves a function, such as conveying that part an utterance is at-issue or is backgrounded. When multiple constructions combine to produce an utterance, their functions must be compatible. This preregistered study (N = 680) addresses the enigmatic case of “syntactic island constraints”: Long-distance dependency constructions (LDDs) do not combine equally well with all base constructions. While widely presumed to require unlearned syntactic constraints, we test the idea that it is infelicitous to make an element both prominent (via an LDD construction) and backgrounded (via the base construction). Using 10 base constructions of English (144 base stimuli), results confirm two independent measures of backgroundedness strongly correlate with acceptability ratings on each of three LDD constructions. Results indicate that “island” constraints arise from a clash between the functions of the constructions being combined.

Our ability to comprehend and produce language is one of humans’ most impressive skills, but it is not flawless. We must convey and interpret messages via a noisy channel in ever-changing contexts and we sometimes fail to access an optimal combination of words and grammatical constructions. Here, we extend the notion of good-enough (GN) comprehension to GN production, which allows us to unify a wide range of phenomena including overly vague word choices, agreement errors, resumptive pronouns, transfer effects, and children’s overextensions and regularizations. We suggest these all involve the accessing and production of a ‘GN’ option when a more-optimal option is inaccessible. The role of accessibility highlights the need to relate memory encoding and retrieval processes to language comprehension and production.

The current work tests the hypothesis that the island status of clausal adjuncts, as determined by judgments on wh-questions, are predicted by the degree of “backgroundedness” of the adjuncts, as determined by a separate negation task. Results of two experiments support the hypothesis that acceptability of extraction from adjuncts in wh-questions is inversely correlated with the degree to which the adjunct is backgrounded in discourse. Taken together, results show that temporal clausal adjuncts (headed by before, after, while) are stronger islands than adjuncts that are causal (here, headed by to or by). This demonstrates that adjuncts differ in degree of island status, depending on their meaning, despite parallel syntactic structure.

Accessibility plays a major role in speech production. Here we investigate and measure four factors that influence speakers to produce one word over another more optimal word form. Three experiments asked participants to label images of insects and instruments. Participants were incentivized to produce an accurate specific label (e.g., bee), over a more general label (e.g., insect), so that specific labels were more optimal. Each of three experiments manipulated a different factor that could influence accessibility – word frequency, priming, and interference – and all experiments additionally varied whether labels had to be produced under time pressure or not. Results showed that each variable significantly influenced the accessibility of labels: participants produced more specific labels when those labels were higher frequency, when they were primed, when a visually-similar label had not been primed, and when participants were unconstrained by time pressure. These findings demonstrate that multiple factors influence the accessibility of familiar words during production, regularly leading participants to rely on “good-enough” rather than optimal options to convey their message.

Speakers use different language to communicate with partners in different communities. But how do we learn and represent which conventions to use with which partners? In this paper, we argue that solving this challenging computational problem requires speakers to supplement their lexical representations with knowledge of social group structure. We formalize this idea by extending a recent hierarchical Bayesian model of convention formation with an intermediate layer explicitly representing the latent communities each partner belongs to, and derive predictions about how conventions formed within a group ought to extend to new in-group and out-group members. We then present evidence from two behavioral experiments testing these predictions using a minimal group paradigm. Taken together, our findings provide a first step toward a formal framework for understanding the interplay between language use and social group knowledge.

The constructionist approach argues that communication is central to language learning, language use, and language change. We argue that the approach provides a useful perspective on how autistic children learn language, as it anticipates variable outcomes and suggests testable predictions. First, a reduced ability and interest in tracking the attention and intentions of others should negatively impact early language development, and a wealth of evidence indicates that it does. Second, and less discussed until recently, a hyperfocus on specifics at the expense of generalizations, common among people on the spectrum, should also negatively impact language development, and recent evidence suggests this is also the case. Pace Kissine's 2021 target article, it is unsurprising that children can learn some second language from watching videos, and it is unclear how an appeal to 'innate' language-specific knowledge could explain the range of outcomes of individuals on the autism spectrum.

Conventional metaphors (e.g., a firm grasp on an idea) are extremely common. A possible explanation for their ubiquity is that they are more engaging, evoking more focused attention, than their literal paraphrases (e.g., a good understanding of an idea). To evaluate whether, when, and why this may be true, we created a new database of 180 English sentences consisting of conventional metaphors, literal paraphrases, and concrete descriptions (e.g., a firm grip on a doorknob). Extensive norming matched differences across sentence types in complexity, plausibility, emotional valence, intensity, and familiarity of the key phrases. Then, using pupillometry to study the time course of metaphor processing, we predicted that metaphors would elicit greater event-evoked pupil dilation compared to other sentence types. Results confirmed the predicted increase beginning at the onset of the key phrase and lasting seconds beyond the end of the sentence. When metaphorical and literal sentences were compared directly in survey data, participants judged metaphorical sentences to convey “richer meaning,” but not more information. We conclude that conventional metaphors are more engaging than literal paraphrases or concrete sentences in a way that is irreducible to difficulty or ease, amount of information, short-term lexical access, or downstream inferences.

The current work suggests that two factors conspire to make vocabulary learning challenging for youth on the Autism spectrum: (1) a tendency to focus on specifics rather than on relationships among entities, and (2) up to 80% of words are associated with distinct but related meanings (e.g. a baseball cap, pen cap, bottle cap). Neurotypical (NT) children find it easier to learn multiple related meanings of words (polysemy) in comparison to multiple unrelated meanings (homonymy). We exposed 60 NT children and 40 verbal youth on the Autism spectrum to novel words. The groups’ performance learning homonyms was comparable, but unlike their NT peers, youth on the spectrum did not display the same advantage for learning polysemous words compared to homonyms.

This article argues that a usage-based construction (a conventional pairing of form and function) is required to account for a certain pattern of English exemplified by e.g., it’s nice of you to read this. Contemporary corpus and survey data reveal that the construction is strongly associated with certain adjectives (e.g., nice, good) over others, while diachronic data demonstrate that the construction’s overall frequency has systematically waxed and waned over the past century. The construction’s unique function – namely to concisely convey a judgment regarding how an action reflects on the agent of the action – enables us to predict many observations about its distribution without stipulation. These include restrictions on the interpretation of adjectives that occur in the construction, its infinitive complement, the modal verbs that may appear in it and its ability to be embedded. We further observe that certain conventional fragments of the construction evoke the semantics of the entire construction. Finally, we situate the construction within a network of related constructions, as part of a speaker’s construct-i-con.

There are times when a curiously odd relic of language presents us with a thread, which when pulled, reveals deep and general facts about human language. This paper unspools such a case. Prior to 1930, English speakers uniformly preferred male-before-female word order in conjoined nouns such as uncles and aunts; nephews and nieces; men and women. Since then, at least a half dozen items have systematically reversed their preferred order (e.g., aunts and uncles, nieces and nephews) while others have not (men and women). We review evidence that the unusual reversals began with mother and dad(dy) and spread to semantically and morphologically related binomials over a period of decades. The present work proposes that three aspects of cognitive accessibility combine to quantify the probability of A&B order: 1) the relative accessibility of the A and B terms individually, 2) competition from B&A order, and critically, 3) cluster strength (i.e., similarity to related A’& B’ cases). The emergent cluster of female-first binomials highlights the influence of semantic neighborhoods in memory retrieval. We suggest that cognitive accessibility can be used to predict the word order of both familiar and novel binomials generally, as well as the diachronic change focused on here.

Native speakers strongly disprefer novel formulations when a conventional alternative expresses the same intended message, presumably because the more conventional form competes with the novel form. In five studies, second language (L2) speakers were less influenced by competing alternatives than native speakers. L2 speakers accepted novel interpretable sentences more readily than native speakers, and were somewhat less likely to offer competing alternatives as paraphrases or to prefer competing alternatives in forced‐choice tasks. They were unaffected by exposure to competing alternatives immediately before judgments. Reduced sensitivity to competing alternatives was confirmed by L2 speakers’ greater divergence from native speakers on judgments for novel formulations compared to familiar ones. Reduced sensitivity to competing alternatives also predicts noisier linguistic representations; consistent with this, L2 speakers performed worse on a verbatim recognition task, with performance correlating with more nativelike judgments. Proficiency was a modest predictor of judgments, but transfer effects were not.

The present study aims to investigate the neural correlates of processing conventional figurative language in non-native speakers in a comparison with native speakers. Italian proficient L2 learners of German and German native speakers read conventional metaphorical statements as well as literal paraphrases that were comparable on a range of psycholinguistic variables. Results confirm previous findings that native speakers show increased activity for metaphorical processing, and left amygdala activation increases with increasing Metaphoricity. At the whole-brain level, L2 learners showed the expected overall differences in activation when compared to native speakers (in the fronto-temporal network). But L2 speakers did not show any distinctive activation outside the caudate nucleus as Metaphoricity increased, suggesting that the L2 speakers were less affected by increasing Metaphoricity than native speakers were. With small volume correction, only a single peak in the amygdala reached threshold for L2 speakers as Metaphoricity increased. The findings are consistent with the view that metaphorical language is more engaging for native speakers but not necessarily for L2 speakers.

A key property of linguistic conventions is that they hold over an entire community of speakers, allowing us to communicate efficiently even with people we have never met before. At the same time, much of our language use is partner-specific: we know that words may be understood differently by different people based on local common ground. This poses a challenge for accounts of convention formation. Exactly how do agents make the inferential leap to community-wide expectations while maintaining partner-specific knowledge? We propose a hierarchical Bayesian model of convention to explain how speakers and listeners abstract away meanings that seem to be shared across partners. To evaluate our model's predictions, we conducted an experiment where participants played an extended natural-language communication game with different partners in a small community. We examine several measures of generalization across partners, and find key signatures of local adaptation as well as collective convergence. These results suggest that local partner-specific learning is not only compatible with global convention formation but may facilitate it when coupled with a powerful hierarchical inductive mechanism.

There has been a great deal of interest in how generalizations and exceptions are represented and processed, but scant attention has been paid to the following question: do exceptional cases affect generalizations during learning? Here we suggest that they do. Novel words were paired with one of two preceding “classifiers.” Each <classifier+word> was assigned a unique image. Most words for one classifier were paired with images from a generalization semantic category, whereas a subclass of exception words were paired with images from a second category. All words for the second classifier appeared with a third baseline category. After initial exposure, participants used a computer mouse to choose one of two images for each <classifier+word>, in a design repeated over 8 blocks. With deviation over time toward the lure as the dependent measure, results showed that competition led to suppression of a generalization in the context of exceptions, suggesting that the generalization itself was affected by learned exceptions.

Learners preferentially interpret novel nouns at the basic level (“dog”) rather than at a more narrow level (“Labrador”). This “basic-level bias” is mitigated by statistics: children and adults are more likely to interpret a novel noun at a more narrow label if they witness “a suspicious coincidence” — the word applied to 3 exemplars of the same narrow category. Independent work has found that exemplar typicality influences learners’ inferences and category learning. We bring these lines of work together to investigate whether the content (typicality) of a single exemplar affects the level of interpretation of words and whether an atypicality effect interacts with input statistics. Results demonstrate that both 4-5 year olds and adults tend to assign a narrower interpretation to a word if it is exemplified by an atypical category member. This atypicality effect is roughly as strong as, and independent of, the suspicious coincidence effect, which is replicated.

Learning vocabulary is essential to successful communication. Complicating this task is the under-appreciated fact that most common words are associated with multiple senses (are polysemous ) (e.g., baseball capvs. capof a bottle), while other words are homonymous, evoking meanings that are unrelated to one another (e.g., baseball batvs. flying bat ). Models of human word learning have thus far failed to represent this level of naturalistic complexity. We extend a feature-based computational model to allow for multiple meanings, while capturing the gradient distinction between polysemy and homonymy by using structured sets of features. Results confirm that the present model correlates better with human data on novel word learning tasks than the existing feature-based model.

Up to 80% of words have multiple, related meanings (polysemy), yet work on early word learning has almost uniformly assumed one-to-one mappings between form and meaning. Using a looking-while-listening procedure, we present the first evidence that toddlers (n=32) can recognize multiple meanings for common nouns, e.g. collar of a dog, shirt collar. In an English-meaning condition, toddlers were tested on their ability to recognize multiple English meanings for polysemous words such as cap(e.g. a baseball cap and a bottle cap). Another condition prompted them with the same English words (e.g., cap), but target referents instead corresponded to the word’s polysemous extension in an unfamiliar language, (e.g., “lid” is a meaning for Spanish’s “cap”, tapa). Toddlers looked to the correct targets above chance in both trial types, but with greater accuracy on English-meaning trials, demonstrating a recognition of familiar word-meaning pairs and an ability to infer potential new meanings (Spanish-meaning trials).

In 1990, Bock and Loebell found that passives (e.g., The 747 was radioed by the airport’s control tower) can be primed by intransitive locatives (e.g., The 747 was landing by the airport’s control tower). This finding is often taken as strong evidence that structural priming occurs on the basis of a syntactic phrase structure that abstracts across lexical content, including prepositions, and is uninfluenced by the semantic roles of the arguments. However, all of the intransitive locative primes in Bock and Loebell contained the preposition by (by-locatives), just like the passive targets. Therefore, the locative-to-passive priming may have been due to the adjunct headed by by, rather than being a result of purely abstract syntax. The present experiment investigates this possibility. We find that passives and intransitive by-locatives are equivalent primes, but intransitive locatives with other prepositions (e.g., The 747 has landed near the airport control tower) do not prime passives. We conclude that a shared abstract, content-less tree structure is not sufficient for passive priming to occur. We then review the prior results that have been offered in favor of abstract tree priming, and note the range of evidence can be considerably narrowed and possibly eliminated, once effects of animacy, semantic roles, shared morphology, information structure, and rhythm are taken into account.