If priming is graded rather than all-or-none, can reactivating abstract structures be the underlying mechanism?

In our commentary on Branigan & Pickering (B&P), we start by arguing that the authors implicitly adopt several assumptions, the consequence of which is to make further claims necessary and/or sufficient. Crucially, the authors assume the existence of discrete units at various levels of linguistic granularity that then must be operated upon by combinatorial mechanisms and rules (i.e., decomposition/recomposition). They further argue that structural priming provides a powerful tool to study abstract, structural representations. We provide evidence that priming effects in production are characterized better as graded than as all-or-none and that priming need not arise from a mechanism that (re)activates a shared but abstract internal structure

The relationship between thematic, lexical, and syntactic features of written texts and personality traits

The relationship between linguistic features of written texts and personality traits was investigated. Linguistic features used in this study were thematic (co-occurrence of the most frequent content words across participants), lexical (the maximum of new words) and syntactic (average sentence length). Personality traits were measured by VP+2 questionnaire standardized for Serbian population. Research was conducted on text materials collected from 114 Serbian participants (age 15–65), in their native tongue. Results showed that participants who gained low scores on Conscientiousness and high scores on Neuroticism and Negative Valence wrote about repeated daily activities and everyday life, but not about job-related matters or life perspective. Higher scores on Aggressiveness and Negative Valence coincided with writing about job-related matters and with the lower lexical richness. By showing that thematic content of text materials is affected by personality traits, these results support and expand previous findings regarding the relationship between personality and linguistic behaviour

A learning perspective on individual differences in skilled reading: Exploring and exploiting orthographic and semantic discrimination cues

The goal of the present study is to understand the role orthographic and semantic information play in the behaviour of skilled readers. Reading latencies from a self-paced sentence reading experiment in which Russian near-synonymous verbs were manipulated appear well-predicted by a combination of bottom-up sub-lexical letter triplets (trigraphs) and top-down semantic generalizations, modelled using the Naive Discrimination Learner. The results reveal a complex interplay of bottom-up and top-down support from orthography and semantics to the target verbs, whereby activations from orthography only are modulated by individual differences. Using performance on a serial reaction time task for a novel operationalization of the mental speed hypothesis, we explain the observed individual differences in reading behaviour in terms of the exploration/exploitation hypothesis from Reinforcement Learning, where initially slower and more variable behaviour leads to better performance overall

Language comprehension as a multi-label classification problem

The initial stage of language comprehension is a multi-label classification problem. Listeners or readers, presented with an utterance, need to discriminate between the intended words and the tens of thousands of other words they know. We propose to address this problem by pairing a network trained with the learning rule of Rescorla andWagner (1972) with a second network trained independently with the learning rule of Widrow and Hoff (1960). The first network has to recover from sublexical input features the meanings encoded in the language signal, resulting in a vector of activations over the lexicon. The second network takes this vector as input and further reduces uncertainty about the intended message. Classification performance for a lexicon with 52,000 entries is good. The model also correctly predicts several aspects of human language comprehension. By rejecting the traditional linguistic assumption that language is a (de)compositional system, and by instead espousing a discriminative approach (Ramscar, 2013), a more parsimonious yet highly effective functional characterization of the initial stage of language comprehension is obtained

The informativeness of linguistic unit boundaries

Contemporary models of structural analysis tend to operate with discrete units at different linguistic levels. There is, however, considerable debate regarding the choice of units and the validity of the cues that guide their demarcation. At the level of grammatical analysis, this debate focuses largely on the status of words vs sub-word units and on the generality of the linguistic properties that mark each type of unit. This paper suggests that the status of a unit type can be evaluated in terms of its informativity A measure of informativity is obtained by assessing the influence that different unit boundary types have on text compressibility. The results obtained from this initial study support a pair of general conclusions. The first is that unit boundaries primarily reflect a statistical structure, and that the typological variability of linguistic cues reflects the fact that they serve a secondary reinforcing function. The second is that word boundaries are the most informative boundary type, and that the demarcation of words provides the most informative description of the regular patterns in a language

Psycholinguistic studies of word morphology and their implications for models of the mental lexicon and lexical processing

We sample from behavioral studies of visually presented inflected and derived words in the lexical decision task to describe how we understand morphologically complex word forms. We discuss how these results inform theories of the mental lexicon and lexical processing and offer some implications for how these findings might inform teaching practices for beginning readers about morphology. We focus on experimental findings pertaining to morphological regularity, whole word and morpheme frequency (including family size, entropy measures, affix frequency, and position), along with semantic transparency and morpho-orthographic parsing of words composed of several morphemes. Models of how we understand and produce morphologically complex words epitomize issues about how to capture knowledge about word patterns and the extent to which that knowledge is better characterized as general statistical patterning based on graded similarity of form and meaning as contrasted with rules that apply to linguistically defined morphemic units

Information and learning in processing adjective inflection

​We investigated the processing of inflected Serbian adjective forms to bring together quantitative linguistic measures from two frameworks – information theory and discrimination learning. From each framework we derived several quantitative descriptions of an inflectional morphological system and fitted two separate regression models to the processing latencies that were elicited by inflected adjectival forms presented in a visual lexical decision task. The model, which was based on lexical distributional and information theory revealed a dynamic interplay of information. The information was sensitive to syntagmatic and paradigmatic dimensions of variation; the paradigmatic information (formalized as respective relative entropies) was also modulated by lemma frequency. The discrimination learning based model revealed an equally complex pattern, involving several learning-based variables. The two models revealed strikingly similar patterns of results, as confirmed by the very high proportion of shared variance in model predictions (85.83%). Our findings add to the body of research demonstrating that complex morphological phenomena can arise as a consequence of the basic principles of discrimination learning. Learning discriminatively about inflectional paradigms and classes, and about their contextual or syntagmatic embedding, sheds light on human language-processing efficiency and on the fascinating complexity of naturally emerged language systems

Effects of nitrogen supply on must quality and anthocyanin accumulation in berries of cv. Merlot

Nitrogen supply to Merlot vines (Vitis vinifera L.), grown under controlled conditions, affected must quality and the anthocyanin content in berry skins irrespective of vegetative growth. High N supply delayed fruit maturation; berries had a higher arginine and a lower anthocyanin content with relatively more abundant acylated anthocyanins compared to berries of vines supplied with low N. During maturation the anthocyanin content in the skin of berries decreased; this was more significant in high-N vines. It is concluded that high nitrogen supply affects the metabolic pathway of anthocyanins in different ways, e.g. it delays the quantitative and qualitative biosynthesis and enhances their degradation during the final steps of berry maturation.

Silicon/Disordered Carbon Nanocomposites for Lithium-Ion Battery Anodes

Silicon/disordered carbon Si-DC nanocomposites have been synthesized by high-energy ballmilling of Si-sucrose and silicon-polyvinyl alcohol followed by pyrolysis under argon flow. The exact disordered carbon content in the as-prepared Si-DC nanocomposites was determined by thermogravimetric analysis for the first time. Based on the thermogravimetric analysis, X-ray diffraction, Raman, and cyclic voltammetric results, we believe that carbon distribution on the Si particles in Si-DC nanocomposite using PVA as the carbon source is more uniform and has higher efficiency than that using sucrose as the carbon source, under the same preparation conditions. The carbon content and the starting polymers significantly affect the electrochemical performance of the Si-DC nanocomposites. The optimized Si-DC nanocomposite anode demonstrated a reversible capacity of 754 mAh/g within 20 cycles