Publications

Abstract

Using language requires access to domain-specific linguistic representations, but also draws on domain-general cognitive skills. A key issue in current psycholinguistics is to situate linguistic processing in the network of human cognitive abilities. Here, we focused on spoken word recognition and used an individual differences approach to examine the links of scores in word recognition tasks with scores on tasks capturing effects of linguistic experience, general processing speed, working memory, and non-verbal reasoning. 281 young native speakers of Dutch completed an extensive test battery assessing these cognitive skills. We used psychometric network analysis to map out the direct links between the scores, that is, the unique variance between pairs of scores, controlling for variance shared with the other scores. The analysis revealed direct links between word recognition skills and processing speed. We discuss the implications of these results and the potential of psychometric network analysis for studying language processing and its embedding in the broader cognitive system.

Abstract

Individuals exhibit massive variability in general cognitive skills that affect language processing. This variability is partly developmental. Here, we recruited a large sample of participants (N = 487), ranging from 9 to 90 years of age, and examined the involvement of nonverbal processing speed (assessed using visual and auditory reaction time tasks) and working memory (assessed using forward and backward Digit Span tasks) in a visual world task. Participants saw two objects on the screen and heard a sentence that referred to one of them. In half of the sentences, the target object could be predicted based on verb-selectional restrictions. We observed evidence for anticipatory processing on predictable compared to non-predictable trials. Visual and auditory processing speed had main effects on sentence comprehension and facilitated predictive processing, as evidenced by an interaction. We observed only weak evidence for the involvement of working memory in predictive sentence comprehension. Age had a nonlinear main effect (younger adults responded faster than children and older adults), but it did not differentially modulate predictive and non-predictive processing, nor did it modulate the involvement of processing speed and working memory. Our results contribute to delineating the cognitive skills that are involved in language-vision interactions.

Abstract

We introduce the Individual Differences in Language Skills (IDLaS-NL) web platform, which enables users to run studies on individual differences in Dutch language skills via the internet. IDLaS-NL consists of 35 behavioral tests, previously validated in participants aged between 18 and 30 years. The platform provides an intuitive graphical interface for users to select the tests they wish to include in their research, to divide these tests into different sessions and to determine their order. Moreover, for standardized administration the platform
provides an application (an emulated browser) wherein the tests are run. Results can be retrieved by mouse click in the graphical interface and are provided as CSV-file output via email. Similarly, the graphical interface enables researchers to modify and delete their study configurations. IDLaS-NL is intended for researchers, clinicians, educators and in general anyone conducting fundaental research into language and general cognitive skills; it is not intended for diagnostic purposes. All platform services are free of charge. Here, we provide a
description of its workings as well as instructions for using the platform. The IDLaS-NL platform can be accessed at www.mpi.nl/idlas-nl.

Abstract

Humans differ greatly in their ability to use language. Contemporary psycholinguistic theories assume that individual differences in language skills arise from variability in linguistic experience and in general cognitive skills. While much previous research has tested the involvement of select verbal and non-verbal variables in select domains of linguistic processing, comprehensive characterizations of the relationships among the skills underlying language use are rare. We contribute to such a research program by re-analyzing a publicly available set of data from 112 young adults tested on 35 behavioral tests. The tests assessed nine key constructs reflecting linguistic processing skills, linguistic experience and general cognitive skills. Correlation and hierarchical clustering analyses of the test scores showed that most of the tests assumed to measure the same construct correlated moderately to strongly and largely clustered together. Furthermore, the results suggest important roles of processing speed in comprehension, and of linguistic experience in production.

Abstract

Oral communication often takes place in noisy environments, which challenge spoken-word recognition. Previous research has suggested that the presence of background noise extends the number of candidate words competing with the target word for recognition and that this extension affects the time course and accuracy of spoken-word recognition. In this study, we further investigated the temporal dynamics of competition processes in the presence of background noise, and how these vary in listeners with different language proficiency (i.e., native and non-native) using computational modeling. We developed ListenIN (Listen-In-Noise), a neural-network model based on an autoencoder architecture, which learns to map phonological forms onto meanings in two languages and simulates native and non-native spoken-word comprehension. Simulation A established that ListenIN captures the effects of noise on accuracy rates and the number of unique misperception errors of native and non-native listeners in an offline spoken-word identification task (Scharenborg et al., 2018). Simulation B showed that ListenIN captures the effects of noise in online task settings and accounts for looking preferences of native (Hintz & Scharenborg, 2016) and non-native (new data collected for this study) listeners in a visual-world paradigm. We also examined the model’s activation states during online spoken-word recognition. These analyses demonstrated that the presence of background noise increases the number of competitor words which are engaged in phonological competition and that this happens in similar ways intra- and interlinguistically and in native and non-native listening. Taken together, our results support accounts positing a ‘many-additional-competitors scenario’ for the effects of noise on spoken-word recognition.

Abstract

Prediction is an important part of language processing. An open question is to what extent people predict language in challenging circumstances. Here we tested the limits of prediction by asking bilingual Dutch native speakers to interpret Dutch sentences into their English counterparts. In two visual world experiments, we recorded participants’ eye movements to co-present visual objects while they engaged in interpreting tasks (consecutive and simultaneous interpreting). Most participants showed anticipatory eye movements to semantically-related upcoming target words in their L1 source language during both consecutive and simultaneous interpretation. A quarter of participants during simultaneous interpretation however did not move their eyes, an extremely unusual participant behaviour in visual world studies. Overall, the findings suggest that most people predict in the source language under challenging interpreting situations. Further work is required to understand the causes of the absence of (anticipatory) eye movements during simultaneous interpretation in a substantial subset of individuals.

Abstract

Successful spoken-word recognition relies on an interplay between lexical and sublexical processing. Previous research demonstrated that listeners readily shift between more lexically-biased and more sublexically-biased modes of processing in response to the situational context in which language comprehension takes place. Recognizing words in the presence of background noise reduces the perceptual evidence for the speech signal and – compared to the clear – results in greater uncertainty. It has been proposed that, when dealing with greater uncertainty, listeners rely more strongly on sublexical processing. The present study tested this proposal using behavioral and electroencephalography (EEG) measures. We reasoned that such an adjustment would be reflected in changes in the effects of variables predicting recognition performance with loci at lexical and sublexical levels, respectively. We presented native speakers of Dutch with words featuring substantial variability in (1) word frequency (locus at lexical level), (2) phonological neighborhood density (loci at lexical and sublexical levels) and (3) phonotactic probability (locus at sublexical level). Each participant heard each word in noise (presented at one of three signal-to-noise ratios) and in the clear and performed a two-stage lexical decision and transcription task while EEG was recorded. Using linear mixed-effects analyses, we observed behavioral evidence that listeners relied more strongly on sublexical processing when speech quality decreased. Mixed-effects modelling of the EEG signal in the clear condition showed that sublexical effects were reflected in early modulations of ERP components (e.g., within the first 300 ms post word onset). In noise, EEG effects occurred later and involved multiple regions activated in parallel. Taken together, we found evidence – especially in the behavioral data – supporting previous accounts that the presence of background noise induces a stronger reliance on sublexical processing.

Abstract

Prediction of upcoming input is thought to be a main characteristic of language processing (e.g. Altmann & Mirkovic, 2009; Dell & Chang, 2014; Federmeier, 2007; Ferreira & Chantavarin, 2018; Pickering & Gambi, 2018; Hale, 2001; Hickok, 2012; Huettig 2015; Kuperberg & Jaeger, 2016; Levy, 2008; Norris, McQueen, & Cutler, 2016; Pickering & Garrod, 2013; Van Petten & Luka, 2012). One of the main pillars of experimental support for this notion comes from studies that have attempted to measure electrophysiological markers of prediction when participants read or listened to sentences ending in highly predictable words. The N400, a negative-going and centro-parietally distributed component of the ERP occurring approximately 400ms after (target) word onset, has been frequently interpreted as indexing prediction of the word (or the semantic representations and/or the phonological form of the predicted word, see Kutas & Federmeier, 2011; Nieuwland, 2019; Van Petten & Luka, 2012; for review). A major difficulty for interpreting N400 effects in language processing however is that it has been difficult to establish whether N400 target word modulations conclusively reflect prediction rather than (at least partly) ease of integration. In the present exploratory study, we attempted to distinguish lexical prediction (i.e. ‘top-down’ activation) from lexical integration (i.e. ‘bottom-up’ activation) accounts of ERP N400 modulations in language processing.