When is a word in good company for learning?

Although identifying the referents of single words is often cited as a key challenge for getting word learning off the ground, it overlooks the fact that young learners consistently encounter words in the context of other words. How does this company help or hinder word learning? Prior investigations into early word learning from children's real-world language input have yielded conflicting results, with some influential findings suggesting an advantage for words that keep a diverse company of other words, and others suggesting the opposite. Here, we sought to triangulate the source of this conflict, comparing different measures of diversity and approaches to controlling for correlated effects of word frequency across multiple languages. The results were striking: while different diversity measures on their own yielded conflicting results, once nonlinear relationships with word frequency were controlled, we found convergent evidence that contextual consistency supports early word learning. RESEARCH HIGHLIGHTS: The words children learn occur in a sea of other words. The company words keep ranges from highly variable to highly consistent and circumscribed. Prior findings conflict over whether variability versus consistency helps early word learning. Accounting for correlated effects of word frequency resolved the conflict across multiple languages. Results reveal convergent evidence that consistency helps early word learning.

Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects.

Theoretical accounts of the N400 are divided as to whether the amplitude of the N400 response to a stimulus reflects the extent to which the stimulus was predicted, the extent to which the stimulus is semantically similar to its preceding context, or both. We use state-of-the-art machine learning tools to investigate which of these three accounts is best supported by the evidence. GPT-3, a neural language model trained to compute the conditional probability of any word based on the words that precede it, was used to operationalize contextual predictability. In particular, we used an information-theoretic construct known as surprisal (the negative logarithm of the conditional probability). Contextual semantic similarity was operationalized by using two high-quality co-occurrence-derived vector-based meaning representations for words: GloVe and fastText. The cosine between the vector representation of the sentence frame and final word was used to derive contextual cosine similarity estimates. A series of regression models were constructed, where these variables, along with cloze probability and plausibility ratings, were used to predict single trial N400 amplitudes recorded from healthy adults as they read sentences whose final word varied in its predictability, plausibility, and semantic relationship to the likeliest sentence completion. Statistical model comparison indicated GPT-3 surprisal provided the best account of N400 amplitude and suggested that apparently disparate N400 effects of expectancy, plausibility, and contextual semantic similarity can be reduced to variation in the predictability of words. The results are argued to support predictive coding in the human language network.

Ignoring the alternatives: The N400 is sensitive to stimulus preactivation alone.

The N400 component of the event-related brain potential is a neural signal of processing difficulty. In the language domain, it is widely believed to be sensitive to the degree to which a given word or its semantic features have been preactivated in the brain based on the preceding context. However, it has also been shown that the brain often preactivates many words in parallel. It is currently unknown whether the N400 is also affected by the preactivations of alternative words other than the stimulus that is actually presented. This leaves a weak link in the derivation chain-how can we use the N400 to understand the mechanisms of preactivation if we do not know what it indexes? This study directly addresses this gap. We estimate the extent to which all words in a lexicon are preactivated in a given context using the predictions of contemporary large language models. We then directly compare two competing possibilities: that the amplitude of the N400 is sensitive only to the extent to which the stimulus is preactivated, and that it is also sensitive to the preactivation states of the alternatives. We find evidence of the former. This result allows for better grounded inferences about the mechanisms underlying the N400, lexical preactivation in the brain, and language processing more generally.

Do Large Language Models Know What Humans Know?

Humans can attribute beliefs to others. However, it is unknown to what extent this ability results from an innate biological endowment or from experience accrued through child development, particularly exposure to language describing others' mental states. We test the viability of the language exposure hypothesis by assessing whether models exposed to large quantities of human language display sensitivity to the implied knowledge states of characters in written passages. In pre-registered analyses, we present a linguistic version of the False Belief Task to both human participants and a large language model, GPT-3. Both are sensitive to others' beliefs, but while the language model significantly exceeds chance behavior, it does not perform as well as the humans nor does it explain the full extent of their behavior-despite being exposed to more language than a human would in a lifetime. This suggests that while statistical learning from language exposure may in part explain how humans develop the ability to reason about the mental states of others, other mechanisms are also responsible.

Word meaning is both categorical and continuous.

Most words have multiple meanings, but there are foundationally distinct accounts for this. Categorical theories posit that humans maintain discrete entries for distinct word meanings, as in a dictionary. Continuous ones eschew discrete sense representations, arguing that word meanings are best characterized as trajectories through a continuous state space. Both kinds of approach face empirical challenges. In response, we introduce two novel "hybrid" theories, which reconcile discrete sense representations with a continuous view of word meaning. We then report on two behavioral experiments, pairing them with an analytical approach relying on neural language models to test these competing accounts. The experimental results are best explained by one of the novel hybrid accounts, which posits both distinct sense representations and a continuous meaning space. This hybrid account accommodates both the dynamic, context-dependent nature of word meaning, as well as the behavioral evidence for category-like structure in human lexical knowledge. We further develop and quantify the predictive power of several computational implementations of this hybrid account. These results raise questions for future research on lexical ambiguity, such as why and when discrete sense representations might emerge in the first place. They also connect to more general questions about the role of discrete versus gradient representations in cognitive processes and suggest that at least in this case, the best explanation is one that integrates both factors: Word meaning is both categorical and continuous. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Role of Prosody in Disambiguating English Indirect Requests.

Ambiguity pervades language. The sentence "My office is really hot" could be interpreted as a complaint about the temperature or as an indirect request to turn on the air conditioning. How do comprehenders determine a speaker's intended interpretation? One possibility is that speakers and comprehenders exploit prosody to overcome the pragmatic ambiguity inherent in indirect requests. In a pre-registered behavioral experiment, we find that human listeners can successfully determine whether a given utterance was intended as a request at a rate above chance (55%), above and beyond the prior probability of a given sentence being interpreted as a request. Moreover, we find that a classifier equipped with seven acoustic features can detect the original intent of an utterance with 65% accuracy. Finally, consistent with past work, the duration, pitch, and pitch slope of an utterance emerge both as significant correlates of a speaker's original intent and as predictors of comprehenders' pragmatic interpretation. These results suggest that human and machine comprehenders alike can use prosody to enrich the meaning of ambiguous utterances, such as indirect requests.

Sentence-based mental simulations: Evidence from behavioral experiments using garden-path sentences.

Language comprehenders activate mental representations of sensorimotor experiences related to the content of utterances they process. However, it is still unclear whether these sensorimotor simulations are driven by associations with words or by a more complex process of meaning composition into larger linguistic expressions, such as sentences. In two experiments, we investigated whether comprehenders indeed create sentence-based simulations. Materials were constructed such that simulation effects could only emerge from sentence meaning and not from word-based associations alone. We additionally asked when during sentence processing these simulations are constructed, using a garden-path paradigm. Participants read either a garden-path sentence (e.g., "As Mary ate the egg was in the fridge") or a corresponding unambiguous control with the same meaning and words (e.g., "The egg was in the fridge as Mary ate"). Participants then judged whether a depicted entity was mentioned in the sentence or not. In both experiments, picture response times were faster when the picture was compatible (vs. incompatible) with the sentence-based interpretation of the target entity (e.g., both for garden-path and control sentence: an unpeeled egg), suggesting that participants created simulations based on the sentence content and only operating over the sentence as a whole.

Spontaneous, controlled acts of reference between friends and strangers.

Speakers enjoy considerable flexibility in how they refer to a given referent--referring expressions can vary in their form (e.g., "she" vs. "the cat"), their length (e.g., "the (big) (orange) cat"), and more. What factors drive a speaker's decisions about how to refer, and how do these decisions shape a comprehender's ability to resolve the intended referent? Answering either question presents a methodological challenge; researchers must strike a balance between experimental control and ecological validity. In this paper, we introduce the SCARFS (Spontaneous, Controlled Acts of Reference between Friends and Strangers) Database: a corpus of approximately 20,000 English nominal referring expressions (NREs), produced in the context of a communication game. For each NRE, the corpus lists the concept the speaker was trying to convey (from a set of 471 possible target concepts), formal properties of the NRE (e.g., its length), the relationship between the interlocutors (i.e., friend vs. stranger), and the communicative outcome (i.e., whether the expression was successfully resolved). Researchers from diverse disciplines may use this resource to answer questions about how speakers refer and how comprehenders resolve their intended referent--as well as other fundamental questions about dialogic speech, such as whether and how speakers tailor their utterances to the identity of their interlocutor, how second-degree associations are generated, and the predictors of communicative success. Supplementary Information: The online version contains supplementary material available at 10.1007/s10579-022-09619-y.

Languages are efficient, but for whom?

Human languages evolve to make communication more efficient. But efficiency creates trade-offs: what is efficient for speakers is not always efficient for comprehenders. How do languages balance these competing pressures? We focus on Zipf's meaning-frequency law, the observation that frequent wordforms have more meanings. On the one hand, this law could reflect a speaker-oriented pressure to reuse frequent wordforms. Yet human languages still maintain thousands of distinct wordforms, suggesting a countervailing, comprehender-oriented pressure. What balance of these pressures produces Zipf's meaning-frequency law? Using a neutral baseline, we find that frequent wordforms in real lexica have fewer homophones than predicted by their phonotactic structure: real lexica favor a comprehender-oriented pressure to reduce the cost of frequent disambiguation. These results help clarify the evolutionary drive for efficiency: human languages are subject to competing pressures for efficient communication, the relative magnitudes of which reveal how individual-level cognitive constraints shape languages over time.

A pre-registered, multi-lab non-replication of the action-sentence compatibility effect (ACE).

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

Why do human languages have homophones?

Human languages are replete with ambiguity. This is most evident in homophony--where two or more words sound the same, but carry distinct meanings. For example, the wordform "bark" can denote either the sound produced by a dog or the protective outer sheath of a tree trunk. Why would a system evolved for efficient, effective communication display rampant ambiguity? Some accounts argue that ambiguity is actually a design feature of human communication systems, allowing languages to recycle their most optimal wordforms (those which are short, frequent, and phonotactically well-formed) for multiple meanings. We test this claim by constructing five series of artificial lexica matched for the phonotactics and distribution of word lengths found in five real languages (English, German, Dutch, French, and Japanese), and comparing both the quantity and concentration of homophony across the real and artificial lexica. Surprisingly, we find that the artificial lexica exhibit higher upper-bounds on homophony than their real counterparts, and that homophony is even more likely to be found among short, phonotactically plausible wordforms in the artificial than in the real lexica. These results suggest that homophony in real languages is not directly selected for, but rather, that it emerges as a natural consequence of other features of a language. In fact, homophony may even be selected against in real languages, producing lexica that better conform to other requirements of humans who need to use them. Finally, we explore the hypothesis that this is achieved by "smoothing" out dense concentrations of homophones across lexical neighborhoods, resulting in comparatively more minimal pairs in real lexica.

Do gestures retain mental associations with their iconic origins, even after they become emblematic? An analysis of the middle-finger gesture among American English speakers.

What concepts and words do communicative gestures activate in the minds of people who view them? It's widely believed that many gestures grow from iconic origins-they look like what they mean-but also that at some point they may become emblematic-conventionalized as culturally agreed-upon symbols. How long do links between physical movements of the body and the things in the world they denote persist in the minds of gesture-users? A pair of experiments asks this question for the Middle-Finger, a cross-culturally recognized obscene gesture. The prevailing view is that the gesture originates in a phallic symbol. Yet it is now predominantly used as an emblematic gesture displaying contempt (among other things). It is currently unknown whether the iconic origins of gestures persist through the emblematic stage in the minds of gesture users. Two experiments tested the hypothesis that viewing the Middle-Finger primes thoughts about penises or the word penis. The results showed that the Middle-Finger induced no priming of penis compared with control, unlike another obscene penis-representing gesture (Finger-Bang), which did. This suggests that the Middle-Finger no longer activates thoughts of penises in the minds of contemporary American English speakers. Emblematic gestures with iconic origins may undergo historical change not just in the functions they serve but also in the effects they have on the minds of people who use them.

Do Metaphors Move From Mind to Mouth? Evidence From a New System of Linguistic Metaphors for Time.

Languages around the world use a recurring strategy to discuss abstract concepts: describe them metaphorically, borrowing language from more concrete domains. We "plan ahead" to the future, "count up" to higher numbers, and "warm" to new friends. Past work has found that these ways of talking have implications for how we think, so that shared systems of linguistic metaphors can produce shared conceptualizations. On the other hand, these systematic linguistic metaphors might not just be the cause but also the effect of shared, non-linguistic ways of thinking. Here, we present a case study of a variety of American English in which a shared, non-linguistic conceptualization of time has become crystallized as a new system of linguistic metaphors. Speakers of various languages, including English, conceptualize time as a lateral timeline, with the past leftward and the future rightward. Until now, this conceptualization has not been documented in the speech of any language. In two studies, we document how members of the U.S. military, but not U.S. civilians, talk about time using conventionalized lateral metaphors (e.g., "move the meeting right" to mean "move the meeting later"). We argue that, under the right cultural circumstances, implicit mental representations become conventionalized metaphors in language.

The spatial alignment of time: Differences in alignment of deictic and sequence time along the sagittal and lateral axes.

People use space in a variety of ways to structure their thoughts about time. The present report focuses on the different ways that space is employed when reasoning about deictic (past/future relationships) and sequence (earlier/later relationships) time. In the first study, we show that deictic and sequence time are aligned along the lateral axis in a manner consistent with previous work, with past and earlier events associated with left space and future and later events associated with right space. However, the alignment of time with space is different along the sagittal axis. Participants associated future events and earlier events-not later events-with the space in front of their body and past and later events with the space behind, consistent with the sagittal spatial terms (e.g., ahead, in front of) that we use to talk about deictic and sequence time. In the second study, we show that these associations between sequence time and sagittal space are sensitive to person-perspective. This suggests that the particular space-time associations observed in English speakers are influenced by a variety of different spatial properties, including spatial location and perspective.

Acidification and warming affect prominent bacteria in two seasonal phytoplankton bloom mesocosms.

In contrast to clear stimulatory effects of rising temperature, recent studies of the effects of CO2 on planktonic bacteria have reported conflicting results. To better understand the potential impact of predicted climate scenarios on the development and performance of bacterial communities, we performed bifactorial mesocosm experiments (pCO2 and temperature) with Baltic Sea water, during a diatom dominated bloom in autumn and a mixed phytoplankton bloom in summer. The development of bacterial community composition (BCC) followed well-known algal bloom dynamics. A principal coordinate analysis (PCoA) of bacterial OTUs (operational taxonomic units) revealed that phytoplankton succession and temperature were the major variables structuring the bacterial community whereas the impact of pCO2 was weak. Prokaryotic abundance and carbon production, and organic matter concentration and composition were partly affected by temperature but not by increased pCO2 . However, pCO2 did have significant and potentially direct effects on the relative abundance of several dominant OTUs; in some cases, these effects were accompanied by an antagonistic impact of temperature. Our results suggest the necessity of high-resolution BCC analyses and statistical analyses at the OTU level to detect the strong impact of CO2 on specific bacterial groups, which in turn might also influence specific organic matter degradation processes.

How Language Programs the Mind.

Many animals can be trained to perform novel tasks. People, too, can be trained, but sometime in early childhood people transition from being trainable to something qualitatively more powerful-being programmable. We argue that such programmability constitutes a leap in the way that organisms learn, interact, and transmit knowledge, and that what facilitates or enables this programmability is the learning and use of language. We then examine how language programs the mind and argue that it does so through the manipulation of embodied, sensorimotor representations. The role language plays in controlling mental representations offers important insights for understanding its origin and evolution.

Zonation of bacterioplankton communities along aging upwelled water in the northern Benguela upwelling.

Upwelling areas are shaped by enhanced primary production in surface waters, accompanied by a well-investigated planktonic succession. Although bacteria play an important role in biogeochemical cycles of upwelling systems, little is known about bacterial community composition and its development during upwelling events. The aim of this study was to investigate the succession of bacterial assemblages in aging upwelled water of the Benguela upwelling from coastal to offshore sites. Water from the upper mixed layer at 12 stations was sampled along two transects from the origin of the upwelling to a distance of 220 km. 16S rRNA gene amplicon sequencing was then used in a bacterial diversity analysis and major bacterial taxa were quantified by catalyzed reporter deposition-fluorescence in situ hybridization. Additionally, bacterial cell numbers and bacterial production were assessed. Community statistical analysis revealed a reproducible zonation along the two transects, with four clusters of significantly different microbial assemblages. Clustering was mainly driven by phytoplankton composition and abundance. Similar to the temporal succession that occurs during phytoplankton blooms in temperate coastal waters, operational taxonomic units (OTUs) affiliated with Bacteroidetes and Gammaproteobacteria were dominant during algal blooming whereas "Pelagibacterales" were highly abundant in regions with low algal abundance. The most dominant heterotrophic OTU (9% of all reads) was affiliated with "Pelagibacterales" and showed a strong negative correlation with phytoplankton. By contrast, the second most abundant heterotrophic OTU (6% of all reads) was affiliated with the phylum Verrucomicrobia and correlated positively with phytoplankton. Together with the close relation of bacterial production and phytoplankton abundance, our results showed that bacterial community dynamics is strongly driven by the development and composition of the phytoplankton community.

Metaphor priming in sentence production: concrete pictures affect abstract language production.

People speak metaphorically about abstract concepts-for instance, a person can be "full of love" or "have a lot of love to give." Over the past decade, research has begun to focus on how metaphors are processed during language comprehension. Much of this work suggests that understanding a metaphorical expression involves activating brain and body systems involved in perception and motor control. However, no research to date has asked whether the same is true while speakers produce language. We address this gap using a sentence production task. Its results demonstrate that visually activating a concrete source domain can trigger the use of metaphorical language drawn from that same concrete domain, even in sentences that are thematically unrelated to the primes, a metaphorical priming effect. This effect suggests that conceptual metaphors play a part in language production. It also shows that activation in the perceptual system that is not part of an intended message can nevertheless influence sentence formulation.

Action verbs are processed differently in metaphorical and literal sentences depending on the semantic match of visual primes.

Language comprehension requires rapid and flexible access to information stored in long-term memory, likely influenced by activation of rich world knowledge and by brain systems that support the processing of sensorimotor content. We hypothesized that while literal language about biological motion might rely on neurocognitive representations of biological motion specific to the details of the actions described, metaphors rely on more generic representations of motion. In a priming and self-paced reading paradigm, participants saw video clips or images of (a) an intact point-light walker or (b) a scrambled control and read sentences containing literal or metaphoric uses of biological motion verbs either closely or distantly related to the depicted action (walking). We predicted that reading times for literal and metaphorical sentences would show differential sensitivity to the match between the verb and the visual prime. In Experiment 1, we observed interactions between the prime type (walker or scrambled video) and the verb type (close or distant match) for both literal and metaphorical sentences, but with strikingly different patterns. We found no difference in the verb region of literal sentences for Close-Match verbs after walker or scrambled motion primes, but Distant-Match verbs were read more quickly following walker primes. For metaphorical sentences, the results were roughly reversed, with Distant-Match verbs being read more slowly following a walker compared to scrambled motion. In Experiment 2, we observed a similar pattern following still image primes, though critical interactions emerged later in the sentence. We interpret these findings as evidence for shared recruitment of cognitive and neural mechanisms for processing visual and verbal biological motion information. Metaphoric language using biological motion verbs may recruit neurocognitive mechanisms similar to those used in processing literal language but be represented in a less-specific way.

Doing arithmetic by hand: hand movements during exact arithmetic reveal systematic, dynamic spatial processing.

Mathematics requires precise inferences about abstract objects inaccessible to perception. How is this possible? One proposal is that mathematical reasoning, while concerned with entirely abstract objects, nevertheless relies on neural resources specialized for interacting with the world-in other words, mathematics may be grounded in spatial or sensorimotor systems. Mental arithmetic, for instance, could involve shifts in spatial attention along a mental "number-line", the product of cultural artefacts and practices that systematically spatialize number and arithmetic. Here, we investigate this hypothesized spatial processing during exact, symbolic arithmetic (e.g., 4 + 3 = 7). Participants added and subtracted single-digit numbers and selected the exact solution from responses in the top corners of a computer monitor. While they made their selections using a computer mouse, we recorded the movement of their hand as indexed by the streaming x, y coordinates of the computer mouse cursor. As predicted, hand movements during addition and subtraction were systematically deflected toward the right and the left, respectively, as if calculation involved simultaneously simulating motion along a left-to-right mental number-line. This spatial-arithmetical bias, moreover, was distinct from-but correlated with-individuals' spatial-numerical biases (i.e., spatial-numerical association of response codes, SNARC, effect). These results are the first evidence that exact, symbolic arithmetic prompts systematic spatial processing associated with mental calculation. We discuss the possibility that mathematical calculation relies, in part, on an integrated system of spatial processes.