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Mastering how to convey meanings using language is perhaps the main challenge facing any language learner. However, satisfactory accounts of how this is achieved, and even of what it is for a linguistic item to have meaning, are hard to come by. Nick Chater was one of the pioneers involved in the early development of one of the most successful methodologies within the cognitive science of language for discovering meaning: distributional semantics. In this article, we review this approach and discuss its successes and shortcomings in capturing semantic phenomena. In particular, we discuss what we dub the "distributional paradox:" how can models that do not implement essential dimensions of human semantic processing, such as sensorimotor grounding, capture so many meaning-related phenomena? We conclude by providing a preliminary answer, arguing that distributional models capture the statistical scaffolding of human language acquisition that allows for communication, which, in line with Nick Chater's more recent ideas, has been shaped by the features of human cognition on the timescale of cultural evolution., (© 2024 Cognitive Science Society LLC.)

Advances in research on language processing have originally come from group-level comparisons, but there is now a growing interest in individual differences. To investigate individual differences, tasks that have shown robust group-level differences are often used with the implicit assumption that they will also be reliable when used as an individual differences measure. Here, we examined whether one of the primary tasks used in psycholinguistic research on language processing, the self-paced reading task, can reliably measure individual differences in relative clause processing. We replicated the well-established effects of relative clauses at the group level, with object relative clauses being more difficult to process than subject relative clauses. However, when using difference scores, the reliability of the size of the relative clause effect was close to zero because the self-paced reading times for the different relative clause types were highly correlated within individuals. Nonetheless, we found that the self-paced reading task can be used to reliably capture individual differences in overall reading speed as well as key sentence regions when the two types of relative clause sentences are considered separately. Our results indicate that both the reliability and validity of different sentence regions need to be assessed to determine whether and when self-paced reading can be used to examine individual differences in language processing., (© 2024. The Psychonomic Society, Inc.)

Literacy is in decline in many parts of the world, accompanied by drops in associated cognitive skills (including IQ) and an increasing susceptibility to fake news. It is possible that the recent explosive growth and widespread deployment of Large Language Models (LLMs) might exacerbate this trend, but there is also a chance that LLMs can help turn things around. We argue that cognitive science is ideally suited to help steer future literacy development in the right direction by challenging and informing current educational practices and policy. Cognitive scientists have the right interdisciplinary skills to study, analyze, evaluate, and change LLMs to facilitate their critical use, to encourage turn-taking that promotes rather than hinders literacy, to support literacy acquisition in diverse and equitable ways, and to scaffold potential future changes in what it means to be literate. We urge cognitive scientists to take up this mantle-the future impact of LLMs on human literacy skills is too important to be left to the large, predominately U.S.-based tech companies., (© 2024 Cognitive Science Society LLC.)

Background: Several studies have been conducted with the 1.0 version of the Hospital Survey on Patient Safety Culture (HSOPSC) in Norway and globally. The 2.0 version has not been translated and tested in Norwegian hospital settings. This study aims to 1) assess the psychometrics of the Norwegian version (N-HSOPSC 2.0), and 2) assess the criterion validity of the N-HSOPSC 2.0, adding two more outcomes, namely 'pleasure of work' and 'turnover intention'., Methods: The HSOPSC 2.0 was translated using a sequential translation process. A convenience sample was used, inviting hospital staff from two hospitals (N = 1002) to participate in a cross-sectional questionnaire study. Data were analyzed using Mplus. The construct validity was tested with confirmatory factor analysis (CFA). Convergent validity was tested using Average Variance Explained (AVE), and internal consistency was tested with composite reliability (CR) and Cronbach's alpha. Criterion related validity was tested with multiple linear regression., Results: The overall statistical results using the N-HSOPSC 2.0 indicate that the model fit based on CFA was acceptable. Five of the N-HSOPSC 2.0 dimensions had AVE scores below the 0.5 criterium. The CR criterium was meet on all dimensions except Teamwork (0.61). However, Teamwork was one of the most important and significant predictors of the outcomes. Regression models explained most variance related to patient safety rating (adjusted R 2  = 0.38), followed by 'turnover intention' (adjusted R 2  = 0.22), 'pleasure at work' (adjusted R 2  = 0.14), and lastly, 'number of reported events' (adjusted R 2= 0.06)., Conclusion: The N-HSOPSC 2.0 had acceptable construct validity and internal consistency when translated to Norwegian and tested among Norwegian staff in two hospitals. Hence, the instrument is appropriate for use in Norwegian hospital settings. The ten dimensions predicted most variance related to 'overall patient safety', and less related to 'number of reported events'. In addition, the safety culture dimensions predicted 'pleasure at work' and 'turnover intention', which is not part of the original instrument., (© 2024. The Author(s).)

In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab-based experiments, using artificial languages, many of the cues and features that are part of real-world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language-like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in Experiment 2. Finally, Experiment 3 explored the impact of mixed probabilistic feedback (33% positive, 33% negative, 33% no feedback). The results showed that cross-situational learning of words was observed without feedback, but participants were able to learn structural regularities of the miniature language only when feedback was provided. Interestingly, the presence of positive feedback was particularly helpful for the learner, promoting more in-depth learning of the artificial language., (© 2024 Cognitive Science Society LLC.)

This study compared the acoustic properties of 26 (100% female, 100% monolingual) Danish caregivers' spontaneous speech addressed to their 11- to 24-month-old infants (infant-directed speech, IDS) and an adult experimenter (adult-directed speech, ADS). The data were collected between 2016 and 2018 in Aarhus, Denmark. Prosodic properties of Danish IDS conformed to cross-linguistic patterns, with a higher pitch, greater pitch variability, and slower articulation rate than ADS. However, an acoustic analysis of vocalic properties revealed that Danish IDS had a reduced or similar vowel space, higher within-vowel variability, raised formants, and lower degree of vowel discriminability compared to ADS. None of the measures, except articulation rate, showed age-related differences. These results push for future research to conduct theory-driven comparisons across languages with distinct phonological systems., (© 2023 The Authors. Child Development published by Wiley Periodicals LLC on behalf of Society for Research in Child Development.)

Establishing and maintaining mutual understanding in everyday conversations is crucial. To do so, people employ a variety of conversational devices, such as backchannels, repair, and linguistic entrainment. Here, we explore whether the use of conversational devices might be influenced by cross-linguistic differences in the speakers' native language, comparing two matched languages-Danish and Norwegian-differing primarily in their sound structure, with Danish being more opaque, that is, less acoustically distinguished. Across systematically manipulated conversational contexts, we find that processes supporting mutual understanding in conversations vary with external constraints: across different contexts and, crucially, across languages. In accord with our predictions, linguistic entrainment was overall higher in Danish than in Norwegian, while backchannels and repairs presented a more nuanced pattern. These findings are compatible with the hypothesis that native speakers of Danish may compensate for its opaque sound structure by adopting a top-down strategy of building more conversational redundancy through entrainment, which also might reduce the need for repairs. These results suggest that linguistic differences might be met by systematic changes in language processing and use. This paves the way for further cross-linguistic investigations and critical assessment of the interplay between cultural and linguistic factors on the one hand and conversational dynamics on the other., (© 2023 Cognitive Science Society LLC.)

Rapid individual cognitive phenotyping holds the potential to revolutionize domains as wide-ranging as personalized learning, employment practices, and precision psychiatry. Going beyond limitations imposed by traditional lab-based experiments, new efforts have been underway toward greater ecological validity and participant diversity to capture the full range of individual differences in cognitive abilities and behaviors across the general population. Building on this, we developed Skill Lab, a novel game-based tool that simultaneously assesses a broad suite of cognitive abilities while providing an engaging narrative. Skill Lab consists of six mini-games as well as 14 established cognitive ability tasks. Using a popular citizen science platform (N = 10,725), we conducted a comprehensive validation in the wild of a game-based cognitive assessment suite. Based on the game and validation task data, we constructed reliable models to simultaneously predict eight cognitive abilities based on the users' in-game behavior. Follow-up validation tests revealed that the models can discriminate nuances contained within each separate cognitive ability as well as capture a shared main factor of generalized cognitive ability. Our game-based measures are five times faster to complete than the equivalent task-based measures and replicate previous findings on the decline of certain cognitive abilities with age in our large cross-sectional population sample (N = 6369). Taken together, our results demonstrate the feasibility of rapid in-the-wild systematic assessment of cognitive abilities as a promising first step toward population-scale benchmarking and individualized mental health diagnostics., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

In conversation, individuals work together to achieve communicative goals, complementing and aligning language and body with each other. An important emerging question is whether interlocutors entrain with one another equally across linguistic levels (e.g., lexical, syntactic, and semantic) and modalities (i.e., speech and gesture), or whether there are complementary patterns of behaviors, with some levels or modalities diverging and others converging in coordinated fashions. This study assesses how kinematic and linguistic entrainment interact with one another across levels of measurement, and according to communicative context. We analyzed data from two matched corpora of dyadic interaction between-respectively-Danish and Norwegian native speakers engaged in affiliative conversations and task-oriented conversations. We assessed linguistic entrainment at the lexical, syntactic, and semantic level, and kinetic alignment of the head and hands using video-based motion tracking and dynamic time warping. We tested whether-across the two languages-linguistic alignment correlates with kinetic alignment, and whether these kinetic-linguistic associations are modulated either by the type of conversation or by the language spoken. We found that kinetic entrainment was positively associated with low-level linguistic (i.e., lexical) entrainment, while negatively associated with high-level linguistic (i.e., semantic) entrainment, in a cross-linguistically robust way. Our findings suggest that conversation makes use of a dynamic coordination of similarity and complementarity both between individuals as well as between different communicative modalities, and provides evidence for a multimodal, interpersonal synergy account of interaction., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

To what degree can language be acquired from linguistic input alone? This question has vexed scholars for millennia and is still a major focus of debate in the cognitive science of language. The complexity of human language has hampered progress because studies of language-especially those involving computational modeling-have only been able to deal with small fragments of our linguistic skills. We suggest that the most recent generation of Large Language Models (LLMs) might finally provide the computational tools to determine empirically how much of the human language ability can be acquired from linguistic experience. LLMs are sophisticated deep learning architectures trained on vast amounts of natural language data, enabling them to perform an impressive range of linguistic tasks. We argue that, despite their clear semantic and pragmatic limitations, LLMs have already demonstrated that human-like grammatical language can be acquired without the need for a built-in grammar. Thus, while there is still much to learn about how humans acquire and use language, LLMs provide full-fledged computational models for cognitive scientists to empirically evaluate just how far statistical learning might take us in explaining the full complexity of human language., (© 2023 Cognitive Science Society LLC.)

Humans readily engage in idle chat and heated discussions and negotiate tough joint decisions without ever having to think twice about how to keep the conversation grounded in mutual understanding. However, current attempts at identifying and assessing the conversational devices that make this possible are fragmented across disciplines and investigate single devices within single contexts. We present a comprehensive conceptual framework to investigate conversational devices, their relations, and how they adjust to contextual demands. In two corpus studies, we systematically test the role of three conversational devices: backchannels, repair, and linguistic entrainment. Contrasting affiliative and task-oriented conversations within participants, we find that conversational devices adaptively adjust to the increased need for precision in the latter: We show that low-precision devices such as backchannels are more frequent in affiliative conversations, whereas more costly but higher-precision mechanisms, such as specific repairs, are more frequent in task-oriented conversations. Further, task-oriented conversations involve higher complementarity of contributions in terms of the content and perspective: lower semantic entrainment and less frequent (but richer) lexical and syntactic entrainment. Finally, we show that the observed variations in the use of conversational devices are potentially adaptive: pairs of interlocutors that show stronger linguistic complementarity perform better across the two tasks. By combining motivated comparisons of several conversational contexts and theoretically informed computational analyses of empirical data the present work lays the foundations for a comprehensive conceptual framework for understanding the use of conversational devices in dialogue. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

We agree with Heintz & Scott-Phillips that pragmatics does not supplement, but is prior to and underpins, language. Indeed, human non-linguistic communication is astonishingly rich, flexible, and subtle, as we illustrate through the game of charades, where people improvise communicative signals when linguistic channels are blocked. The route from non-linguistic charade-like communication to combinatorial language involves (1) local processes of conventionalization and grammaticalization and (2) spontaneous order arising from mutual constraints between different communicative signals.

Background: Cervical cancer screening participation is suboptimal in most settings. We assessed whether human papillomavirus (HPV) self-sampling may increase screening participation among long-term non-attenders in Norway., Methods: A pragmatic randomised controlled trial with participation as the primary outcome was initiated in the national cervical screening programme in March 2019. A random sample of 6000 women aged 35-69 years who had not attended screening for at least 10 years were randomised 1:1:1 to receive either (i) a reminder to attend regular screening (control), (ii) an offer to order a self-sampling kit (opt-in) for HPV testing or (iii) a self-sampling kit unsolicited (send-to-all) for HPV testing., Results: Total participation was 4.8%, 17.0% and 27.7% among control, opt-in and send-to-all (P < 0.0001; participation difference (%) send-to-all vs. control: 22.9 (95%CI: 20.7, 25.2); opt-in vs. control: 12.3 (95%CI: 10.3, 14.2); send-to-all vs. opt-in: 10.7 (95% CI: 8.0, 13.3)). High-risk HPV was detected in 11.5% of self-samples and 9.2% of clinician-collected samples (P = 0.40). Most women (92.5%) who returned a positive self-sample attended the clinic for triage testing. Of the 933 women screened, 33 (3.5%) had CIN2 + (1.1%, 3.7%, 3.8% among control, opt-in, and send-to-all, respectively), and 11 (1.2%) had cervical cancer (0%, 1.2%, 1.3% among control, opt-in, send-to-all, respectively)., Conclusion: Opt-in and send-to-all self-sampling increased screening participation among long-term, higher-risk non-attenders., Clinical Trial Registration: ClinicalTrials.gov NCT03873376., (© 2022. The Author(s).)

How individuals learn complex regularities in the environment and generalize them to new instances is a key question in cognitive science. Although previous investigations have advocated the idea that learning and generalizing depend upon separate processes, the same basic learning mechanisms may account for both. In language learning experiments, these mechanisms have typically been studied in isolation of broader cognitive phenomena such as memory, perception, and attention. Here, we show how learning and generalization in language is embedded in these broader theories by testing learners on their ability to chunk nonadjacent dependencies-a key structure in language but a challenge to theories that posit learning through the memorization of structure. In two studies, adult participants were trained and tested on an artificial language containing nonadjacent syllable dependencies, using a novel chunking-based serial recall task involving verbal repetition of target sequences (formed from learned strings) and scrambled foils. Participants recalled significantly more syllables, bigrams, trigrams, and nonadjacent dependencies from sequences conforming to the language's statistics (both learned and generalized sequences). They also encoded and generalized specific nonadjacent chunk information. These results suggest that participants chunk remote dependencies and rapidly generalize this information to novel structures. The results thus provide further support for learning-based approaches to language acquisition, and link statistical learning to broader cognitive mechanisms of memory. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Statistical learning is a key concept in our understanding of language acquisition. Ample work has highlighted its role in numerous linguistic functions-yet statistical learning is not a unitary construct, and its consistency across different language properties remains unclear. In a meta-analysis of auditory-linguistic statistical learning research spanning the last 25 years, we evaluated how learning varies across different language properties in infants, children, and adults and surveyed the methodological trends in the literature. We found robust learning across stimuli (syllables, words, etc.) in infants, and across stimuli and structures (adjacent dependencies, non-adjacent dependencies, etc.) in adults, with larger effect sizes when multiple cues were present. However, the analysis also showed significant publication bias and revealed a tendency toward using a narrow range of simplified language properties, including in the strength of the transitional probabilities used during training. Bayes factor analyses revealed prevalent data insensitivity of moderators commonly hypothesized to impact learning, such as the amount of exposure and transitional probability strength, which contradict core theoretical assumptions in the field. Methodological factors, such as the tasks used at test, also significantly impacted effect sizes in adults and children, suggesting that choice of task may critically constrain current theories of how statistical learning operates. Collectively, our results suggest that auditory-linguistic statistical learning has the kind of robustness needed to play a foundational role in language acquisition, but that more research is warranted to reveal its full potential., (© 2022 Cognitive Science Society LLC.)

Statistical learning (SL) is considered a cornerstone of cognition. While decades of research have unveiled the remarkable breadth of structures that participants can learn from statistical patterns in experimental contexts, how this ability interfaces with real-world cognitive phenomena remains inconclusive. These mixed results may arise from the fact that SL is often treated as a general ability that operates uniformly across all domains, typically assuming that sensitivity to one kind of regularity implies equal sensitivity to others. In a preregistered study, we sought to clarify the link between SL and language by aligning the type of structure being processed in each task. We focused on the learning of trigram patterns using artificial and natural language statistics, to evaluate whether SL predicts sensitivity to comparable structures in natural speech. Adults were trained and tested on an artificial language incorporating statistically-defined syllable trigrams. We then evaluated their sensitivity to similar statistical structures in natural language using a multiword chunking task, which examines serial recall of high-frequency word trigrams-one of the building blocks of language. Participants' aptitude in learning artificial syllable trigrams positively correlated with their sensitivity to high-frequency word trigrams in natural language, suggesting that similar computations span learning across both tasks. Short-term SL taps into key aspects of long-term language acquisition when the statistical structures-and the computations used to process them-are comparable. Better aligning the specific statistical patterning across tasks may therefore provide an important steppingstone toward elucidating the relationship between SL and cognition at large., (Copyright © 2022. Published by Elsevier B.V.)

Recent publications have lamented the dominance of psychology in cognitive science. However, this relies on a limited definition of collaboration between fields. We call for a renewed conception of interdisciplinarity as a "mixture of expertise." We describe an information-theoretic measure of interdisciplinarity and apply it to multiauthored published articles. Results suggest that cognitive science journals mix expertise more than topically related journals. We suggest that perceptions of diminishing interdisciplinarity may in part be due to the emergence of different theoretical perspectives and use a semantic model to illustrate this argument. We conclude by describing some benefits of this broader conception., (© 2022 Cognitive Science Society LLC.)

Traditional accounts of language postulate two basic components: words stored in a lexicon, and rules that govern how they can be combined into meaningful sentences, a grammar. But, although this words-and-rules framework has proven itself to be useful in natural language processing and cognitive science, it has also shown important shortcomings when faced with actual language use. In this article, we review evidence from language acquisition, sentence processing, and computational modeling that shows how multiword expressions such as idioms, collocations, and other meaningful and common units that comprise more than one word play a key role in the organization of our linguistic knowledge. Importantly, multiword expressions straddle the line between lexicon and grammar, calling into question how useful this distinction is as a foundation for our understanding of language. Nonetheless, finding a replacement for the foundational role the words-and-rules approach has played in our theories is not straightforward. Thus, the second part of our article reviews and synthesizes the diverse approaches that have attempted to account for the central role of multiword expressions in language representation, acquisition, and processing., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Contreras Kallens and Christiansen.)

A growing body of research investigates individual differences in the learning of statistical structure, tying them to variability in cognitive (dis)abilities. This approach views statistical learning (SL) as a general individual ability that underlies performance across a range of cognitive domains. But is there a general SL capacity that can sort individuals from 'bad' to 'good' statistical learners? Explicating the suppositions underlying this approach, we suggest that current evidence supporting it is meager. We outline an alternative perspective that considers the variability of statistical environments within different cognitive domains. Once we focus on learning that is tuned to the statistics of real-world sensory inputs, an alternative view of SL computations emerges with a radically different outlook for SL research., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

High frequency words play a key role in language acquisition, with recent work suggesting they may serve both speech segmentation and lexical categorisation. However, it is not yet known whether infants can detect novel high frequency words in continuous speech, nor whether they can use them to help learning for segmentation and categorisation at the same time. For instance, when hearing "you eat the biscuit", can children use the high-frequency words "you" and "the" to segment out "eat" and "biscuit", and determine their respective lexical categories? We tested this in two experiments. In Experiment 1, we familiarised 12-month-old infants with continuous artificial speech comprising repetitions of target words, which were preceded by high-frequency marker words that distinguished the targets into two distributional categories. In Experiment 2, we repeated the task using the same language but with additional phonological cues to word and category structure. In both studies, we measured learning with head-turn preference tests of segmentation and categorisation, and compared performance against a control group that heard the artificial speech without the marker words (i.e., just the targets). There was no evidence that high frequency words helped either speech segmentation or grammatical categorisation. However, segmentation was seen to improve when the distributional information was supplemented with phonological cues (Experiment 2). In both experiments, exploratory analysis indicated that infants' looking behaviour was related to their linguistic maturity (indexed by infants' vocabulary scores) with infants with high versus low vocabulary scores displaying novelty and familiarity preferences, respectively. We propose that high-frequency words must reach a critical threshold of familiarity before they can be of significant benefit to learning., Competing Interests: The authors have declared that no competing interests exist.

Statistical learning (SL) has been a prominent focus of research in developmental and adult populations, guided by the assumption that it is a fundamental component of learning underlying higher-order cognition. In developmental populations, however, there have been recent concerns regarding the degree to which many current tasks reliably measure SL, particularly in younger children. In the current article, we present the results of two studies that measured auditory statistical learning (ASL) of linguistic stimuli in children aged 5-8 years. Children listened to 6 min of continuous syllables comprising four trisyllabic pseudowords. Following the familiarization phase, children completed (a) a two-alternative forced-choice task and (b) a serial recall task in which they repeated either target sequences embedded during familiarization or foils, manipulated for sequence length. Results showed that, although both measures consistently revealed learning at the group level, the recall task better captured learning across the full range of abilities and was more reliable at the individual level. We conclude that, as has also been demonstrated in adults, the method holds promise for future studies of individual differences in ASL of linguistic stimuli., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

Research has suggested that Danish-learning children lag behind in early language acquisition. The phenomenon has been attributed to the opaque phonetic structure of Danish, which features an unusually large number of non-consonantal sounds (i.e., vowels and semivowels/glides). The large number of vocalic sounds in speech is thought to provide fewer cues to word segmentation and to make language processing harder, thus hindering the acquisition process. In this study, we explored whether the presence of vocalic sounds at word boundaries impedes real-time speech processing in 24-month-old Danish-learning children, compared to word boundaries that are marked by consonantal sounds. Using eye-tracking, we tested children's real-time comprehension of known consonant-initial and vowel-initial words when presented in either a consonant-final carrier phrase or in a vowel-final carrier phrase, thus resulting in the four boundary types C#C, C#V, V#C, and V#V. Our results showed that the presence of vocalic sounds around a word boundary-especially before -impedes processing of Danish child-directed sentences.

Importance: Coagulopathy may deter physicians from performing a lumbar puncture., Objective: To determine the risk of spinal hematoma after lumbar puncture in patients with and without coagulopathy., Design, Setting, and Participants: Danish nationwide, population-based cohort study using medical registries to identify persons who underwent lumbar puncture and had cerebrospinal fluid analysis (January 1, 2008-December 31, 2018; followed up through October 30, 2019). Coagulopathy was defined as platelets lower than 150 × 109/L, international normalized ratio (INR) greater than 1.4, or activated partial thromboplastin time (APTT) longer than 39 seconds., Exposures: Coagulopathy at the time of lumbar puncture., Main Outcomes and Measures: Thirty-day risk of spinal hematoma. Risks were provided as numbers and percentages with 95% CIs. Secondary analyses included risks of traumatic lumbar puncture (>300 × 106 erythrocytes/L after excluding patients diagnosed with subarachnoid hemorrhage). Adjusted hazard rate ratios (HRs) were computed using Cox regression models., Results: A total of 83 711 individual lumbar punctures were identified among 64 730 persons (51% female; median age, 43 years [interquartile range, 22-62 years]) at the time of the procedure. Thrombocytopenia was present in 7875 patients (9%), high INR levels in 1393 (2%), and prolonged APTT in 2604 (3%). Follow-up was complete for more than 99% of the study participants. Overall, spinal hematoma occurred within 30 days for 99 of 49 526 patients (0.20%; 95% CI, 0.16%-0.24%) without coagulopathy vs 24 of 10 371 patients (0.23%; 95% CI, 0.15%-0.34%) with coagulopathy. Independent risk factors for spinal hematoma were male sex (adjusted hazard ratio [HR], 1.72; 95% CI, 1.15-2.56), those aged 41 through 60 years (adjusted HR, 1.96; 95% CI, 1.01-3.81) and those aged 61 through 80 years (adjusted HR, 2.20; 95% CI, 1.12-4.33). Risks did not increase significantly according to overall severity of coagulopathy, in subgroup analyses of severity of coagulopathy by pediatric specialty or medical indication (infection, neurological condition, and hematological malignancy), nor by cumulative number of procedures. Traumatic lumbar punctures occurred more frequently among patients with INR levels of 1.5 to 2.0 (36.8%; 95% CI, 33.3%-40.4%), 2.1 to 2.5 (43.7%; 95% CI, 35.8%-51.8%), and 2.6 to 3.0 (41.9% 95% CI 30.5-53.9) vs those with normal INR (28.2%; 95% CI, 27.7%-28.75%). Traumatic spinal tap occurred more often in patients with an APTT of 40 to 60 seconds (26.3%; 95% CI, 24.2%-28.5%) vs those with normal APTT (21.3%; 95% CI, 20.6%-21.9%) yielding a risk difference of 5.1% (95% CI, 2.9%-7.2%)., Conclusions and Relevance: In this Danish cohort study, risk of spinal hematoma following lumbar puncture was 0.20% among patients without coagulopathy and 0.23% among those with coagulopathy. Although these findings may inform decision-making about lumbar puncture by describing rates in this sample, the observed rates may reflect bias due to physicians selecting relatively low-risk patients for lumbar puncture.

Whereas a growing bulk of work has demonstrated that both adults and children are sensitive to frequently occurring word sequences, little is known about the potential role of meaning in the processing of such multiword chunks. Here, we take a first step toward assessing the contribution of meaningfulness in the processing of multiword sequences, using items that varied in chunk meaningfulness. In a phrasal-decision study, we compared reaction times for triads of three-word sequences, corresponding to idiomatic expressions, compositional phrases, and phrasal fragments, while controlling for phrase and substring frequencies. Chunk meaningfulness, as assessed by a separate subjective rating study, was found to speed up decision times for all three types of strings: The more meaningful a multiword sequence was judged to be, the faster it was processed, independently of whether it was idiomatic, compositional in nature, or a phrasal fragment. These results highlight the importance of taking meaning into account when considering the processing of multiword chunks, consistent with predictions of construction-based approaches to language., (© 2020 Cognitive Science Society, Inc.)

Prior investigations have demonstrated that people tend to link pseudowords such as bouba to rounded shapes and kiki to spiky shapes, but the cognitive processes underlying this matching bias have remained controversial. Here, we present three experiments underscoring the fundamental role of emotional mediation in this sound-shape mapping. Using stimuli from key previous studies, we found that kiki -like pseudowords and spiky shapes, compared with bouba -like pseudowords and rounded shapes, consistently elicit higher levels of affective arousal, which we assessed through both subjective ratings (Experiment 1, N = 52) and acoustic models implemented on the basis of pseudoword material (Experiment 2, N = 70). Crucially, the mediating effect of arousal generalizes to novel pseudowords (Experiment 3, N = 64, which was preregistered). These findings highlight the role that human emotion may play in language development and evolution by grounding associations between abstract concepts (e.g., shapes) and linguistic signs (e.g., words) in the affective system.

The computations involved in statistical learning have long been debated. Here, we build on work suggesting that a basic memory process, chunking, may account for the processing of statistical regularities into larger units. Drawing on methods from the memory literature, we developed a novel paradigm to test statistical learning by leveraging a robust phenomenon observed in serial recall tasks: that short-term memory is fundamentally shaped by long-term distributional learning. In the statistically induced chunking recall (SICR) task, participants are exposed to an artificial language, using a standard statistical learning exposure phase. Afterward, they recall strings of syllables that either follow the statistics of the artificial language or comprise the same syllables presented in a random order. We hypothesized that if individuals had chunked the artificial language into word-like units, then the statistically structured items would be more accurately recalled relative to the random controls. Our results demonstrate that SICR effectively captures learning in both the auditory and visual modalities, with participants displaying significantly improved recall of the statistically structured items, and even recall specific trigram chunks from the input. SICR also exhibits greater test-retest reliability in the auditory modality and sensitivity to individual differences in both modalities than the standard two-alternative forced-choice task. These results thereby provide key empirical support to the chunking account of statistical learning and contribute a valuable new tool to the literature., (© 2020 Cognitive Science Society, Inc.)

Artificial grammar learning (AGL) has become an important tool used to understand aspects of human language learning and whether the abilities underlying learning may be unique to humans or found in other species. Successful learning is typically assumed when human or animal participants are able to distinguish stimuli generated by the grammar from those that are not at a level better than chance. However, the question remains as to what subjects actually learn in these experiments. Previous studies of AGL have frequently introduced multiple potential contributors to performance in the training and testing stimuli, but meta-analysis techniques now enable us to consider these multiple information sources for their contribution to learning-enabling intended and unintended structures to be assessed simultaneously. We present a blueprint for meta-analysis approaches to appraise the effect of learning in human and other animal studies for a series of artificial grammar learning experiments, focusing on studies that examine auditory and visual modalities. We identify a series of variables that differ across these studies, focusing on both structural and surface properties of the grammar, and characteristics of training and test regimes, and provide a first step in assessing the relative contribution of these design features of artificial grammars as well as species-specific effects for learning., (© 2019 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.)

In the fields of linguistics and cognitive science, considerable attention has been devoted to the question of how linguistic structure emerged over evolutionary time. Here, we highlight the contribution of a fundamental constraint on processing, the Now-or-Never bottleneck. Language takes place in the here and now, with the transience of acoustic speech signals and our exceedingly limited memory for sound sequences requiring immediate processing. To overcome this bottleneck, the cognitive system employs basic chunking mechanisms to rapidly compress and recode incoming linguistic input into increasingly abstract levels of representation, thereby prolonging its retention in memory. Our suggestion is that these chunk-based memory processes influence linguistic structure across multiple time scales. Chunk-based memory constraints govern language acquisition and processing on the level of the individual. Through usage, linguistic structures that are more easily chunked will tend to proliferate, thus shaping the cultural evolution of language across generations of language users. This results in a selection of learnable structures, from individual words to multiword sequences that are optimally "chunkable," so as to better squeeze through the Now-or-Never bottleneck. From this perspective, language can be thought of as an adaptive system that culturally evolves to fit learners' cognitive capabilities, thereby resulting in the structure it bears today., (Copyright © 2018 Cognitive Science Society, Inc.)

Statistical learning (SL) is involved in a wide range of basic and higher-order cognitive functions and is taken to be an important building block of virtually all current theories of information processing. In the last 2 decades, a large and continuously growing research community has therefore focused on the ability to extract embedded patterns of regularity in time and space. This work has mostly focused on transitional probabilities, in vision, audition, by newborns, children, adults, in normal developing and clinical populations. Here we appraise this research approach and we critically assess what it has achieved, what it has not, and why it is so. We then center on present SL research to examine whether it has adopted novel perspectives. These discussions lead us to outline possible blueprints for a novel research agenda. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Statistical learning (SL), sensitivity to probabilistic regularities in sensory input, has been widely implicated in cognitive and perceptual development. Little is known, however, about the underlying mechanisms of SL and whether they undergo developmental change. One way to approach these questions is to compare SL across perceptual modalities. While a decade of research has compared auditory and visual SL in adults, we present the first direct comparison of visual and auditory SL in infants (8-10 months). Learning was evidenced in both perceptual modalities but with opposite directions of preference: Infants in the auditory condition displayed a novelty preference, while infants in the visual condition showed a familiarity preference. Interpreting these results within the Hunter and Ames model (1988), where familiarity preferences reflect a weaker stage of encoding than novelty preferences, we conclude that there is weaker learning in the visual modality than the auditory modality for this age. In addition, we found evidence of different developmental trajectories across modalities: Auditory SL increased while visual SL did not change for this age range. The results suggest that SL is not an abstract, amodal ability; for the types of stimuli and statistics tested, we find that auditory SL precedes the development of visual SL and is consistent with recent work comparing SL across modalities in older children., (© 2019 John Wiley & Sons Ltd.)

Statistical learning (SL) involving sensitivity to distributional regularities in the environment has been suggested to be an important factor in many aspects of cognition, including language. However, the degree to which statistically-learned information is retained over time is not well understood. To establish whether or not learners are able to preserve such regularities over time, we examined performance on an artificial second language learning task both immediately after training and also at a follow-up session 2 weeks later. Participants were exposed to an artificial language (Brocanto2), half of them receiving simplified training items in which only 20% of sequences contained complex structures, whereas the other half were exposed to a training set in which 80% of the items were composed of complex sequences. Overall, participants showed signs of learning at the first session and retention at the second, but the degree of learning was affected by the nature of the training they received. Participants exposed to the simplified input outperformed those in the more complex training condition. A GLMM was used to model the relationship between stimulus properties and participants' endorsement strategies across both sessions. The results indicate that participants in the complex training condition relied more on an item's chunk strength than those in the simple training condition. Taken together, this set of findings shows that statistically learned regularities are retained over the course of 2 weeks. The results also demonstrate that training on input featuring simple items leads to improved learning and retention of grammatical regularities., (Copyright © 2019 Jost, Brill-Schuetz, Morgan-Short and Christiansen.)

High frequency words have been suggested to benefit both speech segmentation and grammatical categorization of the words around them. Despite utilizing similar information, these tasks are usually investigated separately in studies examining learning. We determined whether including high frequency words in continuous speech could support categorization when words are being segmented for the first time. We familiarized learners with continuous artificial speech comprising repetitions of target words, which were preceded by high-frequency marker words. Crucially, marker words distinguished targets into 2 distributionally defined categories. We measured learning with segmentation and categorization tests and compared performance against a control group that heard the artificial speech without these marker words (i.e., just the targets, with no cues for categorization). Participants segmented the target words from speech in both conditions, but critically when the marker words were present, they influenced acquisition of word-referent mappings in a subsequent transfer task, with participants demonstrating better early learning for mappings that were consistent (rather than inconsistent) with the distributional categories. We propose that high-frequency words may assist early grammatical categorization, while speech segmentation is still being learned. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Implicit learning and statistical learning are two contemporary approaches to the long-standing question in psychology and cognitive science of how organisms pick up on patterned regularities in their environment. Although both approaches focus on the learner's ability to use distributional properties to discover patterns in the input, the relevant research has largely been published in separate literatures and with surprisingly little cross-pollination between them. This has resulted in apparently opposing perspectives on the computations involved in learning, pitting chunk-based learning against probabilistic learning. In this paper, I trace the nearly century-long historical pedigree of the two approaches to learning and argue for their integration under the heading of "implicit statistical learning." Building on basic insights from the memory literature, I sketch a framework for statistically based chunking that aims to provide a unified basis for understanding implicit statistical learning., (Copyright © 2018 Cognitive Science Society, Inc.)

The neutrophil-lymphocyte ratio (NLR) is a novel biomarker, showing promising both diagnostic and prognostic capabilities. The aim of this study was to present NLR distributions in a Danish population from general practice (GP) and compare levels between patients from intensive care units (ICU) and GP. A register-based study was conducted using results from 31,966 blood samples from GP and ICU located in the admission area of Aarhus University Hospital, Denmark. Exclusion of samples with lymphocytes >40 × 10 9 /L, resulted in 28,582 samples from GP and 3,373 from ICU. Distributions for patients from GP with CRP <8 mg/L were age-dependent and were established for the following three age groups; 0-17 years [0.30:3.76], 18-75 years: [0.74:4.94], above 76 years: [0.89:8.80]. Patients from ICU had a significantly higher median NLR than patients from GP when stratified for CRP, [8.48 and 1.99 respectively]. This study describes for the first time the distributions of NLR in a large European population of GP patients.

While usage-based approaches to language development enjoy considerable support from computational studies, there have been few attempts to answer a key computational challenge posed by usage-based theory: the successful modeling of language learning as language use. We present a usage-based computational model of language acquisition which learns in a purely incremental fashion, through online processing based on chunking, and which offers broad, cross-linguistic coverage while uniting key aspects of comprehension and production within a single framework. The model's design reflects memory constraints imposed by the real-time nature of language processing, and is inspired by psycholinguistic evidence for children's sensitivity to the distributional properties of multiword sequences and for shallow language comprehension based on local information. It learns from corpora of child-directed speech, chunking incoming words together to incrementally build an item-based "shallow parse." When the model encounters an utterance made by the target child, it attempts to generate an identical utterance using the same chunks and statistics involved during comprehension. High performance is achieved on both comprehension- and production-related tasks: the model's shallow parsing is evaluated across 79 single-child corpora spanning English, French, and German, while its production performance is evaluated across over 200 single-child corpora representing 29 languages from the CHILDES database. The model also succeeds in capturing findings from children's production of complex sentence types. Together, our modeling results suggest that much of children's early linguistic behavior may be supported by item-based learning through online processing of simple distributional cues, consistent with the notion that acquisition can be understood as learning to process language. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of starting small and less is more (Elman, ; Newport, ). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains this facilitation. We report four artificial grammar learning experiments with human participants. In Experiments 1a and 1b we found a beneficial effect of starting small using two types of simple recursive grammars: right-branching and center-embedding, with recursive embedded clauses in fixed positions and fixed length. This effect was replicated in Experiment 2 (N = 100). In Experiment 3 and 4, we used a more complex center-embedded grammar with recursive loops in variable positions, producing strings of variable length. When participants were presented an incremental ordering of training stimuli, as in natural language, they were better able to generalize their knowledge of simple units to more complex units when the training input "grew" according to structural complexity, compared to when it "grew" according to string length. Overall, the results suggest that starting small confers an advantage for learning complex center-embedded structures when the input is organized according to structural complexity., (© 2018 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.)

Previous research has shown that Danish-learning children lag behind in early lexical acquisition compared with children learning a number of other languages. This delay has been ascribed to the opaque phonetic structure of Danish, which appears to have fewer reliable segmentation cues than other closely related languages. In support of this hypothesis, recent work has shown that the phonetic properties of Danish negatively affect online language processing in young Danish children. In this study, we used eye-tracking to investigate whether the challenges associated with processing Danish also affect how Danish-learning children between 24 and 35 months of age establish and learn novel label-object mappings. The children were presented with a series of novel mappings, either ostensively (one novel object presented alone on the screen) or ambiguously (one novel object presented together with a familiar one), through carrier phrases with different phonetic structures (more vs less opaque). Our results showed two main trends. First, Danish-learning children performed poorly on the task of mapping novel labels onto novel objects. Second, when learning did occur, accuracy was affected by the phonetic opacity of the speech stimuli. We suggest that this finding results from the interplay of a perceptually challenging speech input and a slower onset of early vocabulary experience, which in turn may delay the onset of word learning skills in Danish-learning children., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Humans and nonhuman primates can learn about the organization of stimuli in the environment using implicit sequential pattern learning capabilities. However, most previous artificial grammar learning studies with nonhuman primates have involved relatively simple grammars and short input sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an artificial grammar-learning task that was more complex than most others previously used with nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial reaction time task in which two monkeys were exposed to grammar-generated sequences at sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the monkeys came to respond faster to the sequences generated from the artificial grammar compared to random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel sequences, responding significantly faster to novel instances of sequences produced using the familiar grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as complex as some used with humans, for sequences up to eight items long. These findings are discussed in relation to whether or not rhesus macaques and other primate species possess implicit sequence learning abilities that are similar to those that humans draw upon to learn natural language grammar.

Humans differ in innumerable ways, with considerable variation observable at every level of description, from the molecular to the social. Traditionally, linguistic and psycholinguistic theory has downplayed the possibility of meaningful differences in language across individuals. However, it is becoming increasingly evident that there is significant variation among speakers at any age as well as across the lifespan. Here, we review recent research in psycholinguistics, and argue that a focus on individual differences (IDs) provides a crucial source of evidence that bears strongly upon core issues in theories of the acquisition and processing of language; specifically, the role of experience in language acquisition, processing, and attainment, and the architecture of the language system., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Languages with many speakers tend to be structurally simple while small communities sometimes develop languages with great structural complexity. Paradoxically, the opposite pattern appears to be observed for non-structural properties of language such as vocabulary size. These apparently opposite patterns pose a challenge for theories of language change and evolution. We use computational simulations to show that this inverse pattern can depend on a single factor: ease of diffusion through the population. A population of interacting agents was arranged on a network, passing linguistic conventions to one another along network links. Agents can invent new conventions, or replicate conventions that they have previously generated themselves or learned from other agents. Linguistic conventions are either Easy or Hard to diffuse, depending on how many times an agent needs to encounter a convention to learn it. In large groups, only linguistic conventions that are easy to learn, such as words, tend to proliferate, whereas small groups where everyone talks to everyone else allow for more complex conventions, like grammatical regularities, to be maintained. Our simulations thus suggest that language, and possibly other aspects of culture, may become simpler at the structural level as our world becomes increasingly interconnected., (© 2018 The Author(s).)

The ability to convey our thoughts using an infinite number of linguistic expressions is one of the hallmarks of human language. Understanding the nature of the psychological mechanisms and representations that give rise to this unique productivity is a fundamental goal for the cognitive sciences. A long-standing hypothesis is that single words and rules form the basic building blocks of linguistic productivity, with multiword sequences being treated as units only in peripheral cases such as idioms. The new millennium, however, has seen a shift toward construing multiword linguistic units not as linguistic rarities, but as important building blocks for language acquisition and processing. This shift-which originated within theoretical approaches that emphasize language learning and use-has far-reaching implications for theories of language representation, processing, and acquisition. Incorporating multiword units as integral building blocks blurs the distinction between grammar and lexicon; calls for models of production and comprehension that can accommodate and give rise to the effect of multiword information on processing; and highlights the importance of such units to learning. In this special topic, we bring together cutting-edge work on multiword sequences in theoretical linguistics, first-language acquisition, psycholinguistics, computational modeling, and second-language learning to present a comprehensive overview of the prominence and importance of such units in language, their possible role in explaining differences between first- and second-language learning, and the challenges the combined findings pose for theories of language., (Copyright © 2017 Cognitive Science Society, Inc.)