How does abstract linguistic negation develop in early child language? Previous research has suggested that abstract negation develops in stages and from more concrete communicative functions such as rejection, prohibition, or non-existence. The evidence for the emergence of these functions in stages is mixed, however, leaving the possibility that negation is an abstract concept from the beginning that can serve multiple specific functions depending on early communicative environment. Leveraging automatic annotations of large-scale child speech corpora in English, we examine the production trajectories of seven negative constructions that tend to convey communicative functions previously discussed in the literature. The results demonstrate the emergence and gradual increase of these constructions in child speech within the age range of 18-36 months. Production mostly remains stable, regular, and close to parents’ levels after this age range. These findings are consistent with two hypotheses: first, that negation starts as an abstract concept that can serve multiple functions from the beginning; and second, that negation develops in stages from specific communicative functions but this development is early and quick, leaving our corpus methods incapable of detecting them from the available corpus data.

We examine how idiosyncrasies of specific verbs in syntac-tic constructions affect constituent ordering preferences. Pre-vious work on binomial expressions in English has demon-strated that the polarization of ordering preferences for a givenbinomial type depends on its overall frequency. The higherthe frequency of a binomial type, the stronger and more ex-treme preference/regularization language users will have forone alternative over the other (e.g. “facts and techniques” >“techniques and facts”; “bread and butter” >>> “butter andbread”). Here using the dative constructions in English as thetest case, we show that the same frequency-dependent regular-ization exists in syntactic structures above the word level. Themore frequent a dative construction type is, governed by thehead verb, the stronger preference there is for one alternationover the other. Further, we present evidence that the regulariza-tion patterns can be accounted for via iterated learning model-ing of language change, suggesting that frequency-dependentregularization emerges via the interactions between languageproduction, language learning and cultural transmission.

Gonering & Corina (2023) argued that abstractions over visual scenes (i.e. schemas or situation models) provide a semantic scaffold for acquiring verb argument structures. We provide a systematic meta-analysis of 158 fMRI studies of verb processing (from NeuroSynth) and 208 fMRI studies of visual event processing (from NeuroQuery) suggestive of their hypothesis. Functional maps produced using Activation Likelihood Estimation via the Neuroimaging Meta-Analysis Research Environment package (Salo et al., 2022) (cluster-level family-wise error corrected using Monte Carlo method) showed overlapping regions of activation in the left inferior parietal lobule and Brodmann's area 47 bilaterally, suggesting shared neural resources for processing verbs and visual scenes. Meta-analyses on additional visual scene and verb processing studies from NeuroSynth and NeuroQuery, respectively, are also underway. We further intend to show that a hierarchical Bayesian model can learn verb argument structures from input statistics, even when they deviate from strong prior event semantic knowledge.

Computational models of morphology acquisition have played a central role in debates over the nature of morphological representations. The apparent success of recent artificial neural network architectures for morphological inflection in natural language processing has renewed this debate. However, the actual suitability of these advanced neural models as models of human morphology acquisition remains uncertain. We argue that much of this confusion stems from inconsistent methods of training and evaluation. In this work, we demonstrate that more careful data set creation and an evaluation combining quantitative analysis and comparison with human development will put the evaluation of neural models on firmer ground.

What determines children's production of syntactic alternations? This study takes up this question with the double PP construction in English as the test case (e.g., write [PP1 on the paper] [PP2 with this new pen]). Leveraging data of spontaneous child-parent interactions, we investigate the roles of dependency length and parent input frequency, with the latter being operationalized as lexical frequency and contextual predictability. We found that when child and parent data was combined, all three factors turned out to have significant predictive power, with dependency length having the most pronounced role. Results from the developmental trajectory of DLM as well as logistic regression analysis suggest that child production of constituent ordering preferences starts becoming more parent-like after the age of 30 months.

Second-language (L2) learning is characterized by both positive and negative transfer from the first language (L1). However, psycholinguistic studies focus on a few syntactic phenomena and L1-L2 pairs at a time, resulting in an incomplete picture. We apply machine learning to seven learner corpora in English and Spanish with 39 language pairs, showing that statistical models combined with simple $n$-grams of part-of-speech tags and syntactic dependency relations achieve good performance in recovering the L1, indicating structural transfer from L1 to L2. Further machine learning using a rich hand-curated linguistic feature set allowed us to identify aspects of L2 linguistic structure particularly influenced by L1 (verbal morphology, average dependency tree parse depth, and headedness of clausal structures) as well as those with minimal influence (distributions of dependency relations, basic word orders, or non-projective dependencies).

Previous studies have claimed that language structures tend to minimize the linear distance between syntactic heads and their dependents, a principle known as Dependency Length Minimization (DLM). These studies, however, have largely focused on written modality. In this study we examine the role of dependency length in acceptability ratings of English and Hindi, two typologically distinct languages, using audio stimuli. With double PP constructions as a test case, our results demonstrate no effect of DLM, suggesting the preference for shorter dependencies is different in acceptability and written texts. These findings are further supported with corpus analysis of a total of 10 treebanks for the two languages, which shows additional language-specific differences in the extent of DLM. We discuss the implications of our work and call for more careful consideration of linguistic and modality-specific diversity when it comes to processing-based claims about language typology.

In English binomial expressions, “bread and butter” is preferred over “butter and bread”. Morgan & Levy (2015) show that for these types of expressions, frequently used phrases tend to have stronger, more extreme preferences. In contrast, there is roughly an equal preference for “bishops and rooks” versus “rooks and bishops”, a much less common pairing. This paper extends this research to the concept of Mandarin elastic word length, a phenomenon in which most Mandarin words have long and short forms. We find evidence for frequency-dependent regularization in the elastic length of Noun-Noun compounds in Chinese, demonstrating that frequency-dependent regularization extends to structures with more than two alternations and to languages other than English.

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck cancer characterized by Epstein-Barr virus (EBV) infection and dense lymphocyte infiltration. The scarcity of NPC genomic data hinders the understanding of NPC biology, disease progression and rational therapy design. Here we performed whole-exome sequencing (WES) on 111 micro-dissected EBV-positive NPCs, with 15 cases subjected to further whole-genome sequencing (WGS), to determine its mutational landscape. We identified enrichment for genomic aberrations of multiple negative regulators of the NF-κB pathway, including CYLD, TRAF3, NFKBIA and NLRC5, in a total of 41% of cases. Functional analysis confirmed inactivating CYLD mutations as drivers for NPC cell growth. The EBV oncoprotein latent membrane protein 1 (LMP1) functions to constitutively activate NF-κB signalling, and we observed mutual exclusivity among tumours with somatic NF-κB pathway aberrations and LMP1-overexpression, suggesting that NF-κB activation is selected for by both somatic and viral events during NPC pathogenesis.