Publications

Abstract

Electroencephalography (EEG) provides high temporal resolution cognitive information from non-invasive recordings. However, one of the common practices-using a subset of sensors in ERP analysis is hard to provide a holistic and precise dynamic results. Selecting or grouping subsets of sensors may also be subject to selection bias, multiple comparison, and further complicated by individual differences in the group-level analysis. More importantly, changes in neural generators and variations in response magnitude from the same neural sources are difficult to separate, which limit the capacity of testing different aspects of cognitive hypotheses. We introduce EasyEEG, a toolbox that includes several multivariate analysis methods to directly test cognitive hypotheses based on topographic responses that include data from all sensors. These multivariate methods can investigate effects in the dimensions of response magnitude and topographic patterns separately using data in the sensor space, therefore enable assessing neural response dynamics. The concise workflow and the modular design provide user-friendly and programmer-friendly features. Users of all levels can benefit from the open-sourced, free EasyEEG to obtain a straightforward solution for efficient processing of EEG data and a complete pipeline from raw data to final results for publication.

Abstract

In a masked priming word-naming task, a facilitation due to the initial-segmental sound overlap for 2-character kanji prime-target pairs was affected by certain orthographic properties (Yoshihara, Nakayama, Verdonschot, & Hino, 2017). That is, the facilitation that was due to the initial mora overlap occurred only when the mora was the whole pronunciation of their initial kanji characters (i.e., match pairs; e.g., /ka-se.ki/-/ka-rjo.ku/). When the shared initial mora was only a part of the kanji characters' readings, however, there was no facilitation (i.e., mismatch pairs; e.g., /ha.tu-a.N/-/ha.ku-bu.tu/). In the present study, we used a masked priming picture-naming task to investigate whether the previous results were relevant only when the orthography of targets is visually presented. In Experiment 1. the main findings of our word-naming task were fully replicated in a picture-naming task. In Experiments 2 and 3. the absence of facilitation for the mismatch pairs were confirmed with a new set of stimuli. On the other hand, a significant facilitation was observed for the match pairs that shared the 2 initial morae (in Experiment 4), which was again consistent with the results of our word-naming study. These results suggest that the orthographic properties constrain the phonological expression of masked priming for kanji words across 2 tasks that are likely to differ in how phonology is retrieved. Specifically, we propose that orthography of a word is activated online and constrains the phonological encoding processes in these tasks.

Abstract

This article provides a first overview of some striking grammatical structures in Türk Idotscedilaret Dili (Turkish Sign Language, TID), the sign language used by the Deaf community in Turkey. The data are described with a typological perspective in mind, focusing on aspects of TID grammar that are typologically unusual across sign languages. After giving an overview of the historical, sociolinguistic and educational background of TID and the language community using this sign language, five domains of TID grammar are investigated in detail. These include a movement derivation signalling completive aspect, three types of nonmanual negation — headshake, backward head tilt, and puffed cheeks — and their distribution, cliticization of the negator NOT to a preceding predicate host sign, an honorific whole-entity classifier used to refer to humans, and a question particle, its history and current status in the language. A final evaluation points out the significance of these data for sign language research and looks at perspectives for a deeper understanding of the language and its history.

Abstract

Bilinguals usually select the right language to speak for the particular context they are in, but sometimes the nontarget language intrudes. Despite a large body of research into language selection and language control, it remains unclear where intrusion errors originate from. These errors may be due to incorrect selection of the nontarget language at the conceptual level, or be a consequence of erroneous word selection (despite correct language selection) at the lexical level. We examined the former possibility in two language switching experiments using a manipulation that supposedly affects language selection on the conceptual level, namely whether the conversational language context was associated with the target language (congruent) or with the alternative language (incongruent) on a trial. Both experiments showed that language intrusion errors occurred more often in incongruent than in congruent contexts, providing converging evidence that language selection during concept preparation is one driving force behind language intrusion.

Abstract

Bilingual speakers have to control their languages to avoid interference, which may be achieved by enhancing the target language and/or inhibiting the nontarget language. Previous research suggests that bilinguals use inhibition (e.g., Jackson et al., 2001), which should be reflected in the N2 component of the event-related potential (ERP) in the EEG. In the current study, we investigated the dynamics of inhibitory control by measuring the N2 during language switching and repetition in bilingual picture naming. Participants had to name pictures in Dutch or English depending on the cue. A run of same-language trials could be short (two or three trials) or long (five or six trials). We assessed whether RTs and N2 changed over the course of same-language runs, and at a switch between languages. Results showed that speakers named pictures more quickly late as compared to early in a run of same-language trials. Moreover, they made a language switch more quickly after a long run than after a short run. This run-length effect was only present in the first language (L1), not in the second language (L2). In ERPs, we observed a widely distributed switch effect in the N2, which was larger after a short run than after a long run. This effect was only present in the L2, not in the L1, although the difference was not significant between languages. In contrast, the N2 was not modulated during a same-language run. Our results suggest that the nontarget language is inhibited at a switch, but not during the repeated use of the target language.

Abstract

Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. To investigate how bilinguals monitor their speech errors and control their languages in use, we recorded event-related potentials (ERPs) in unbalanced Dutch-English bilingual speakers in a cued language-switching task. We tested the conflict-based monitoring model of Nozari and colleagues by investigating the error-related negativity (ERN) and comparing the effects of the two switching directions (i.e., to the first language, L1 vs. to the second language, L2). Results show that the speakers made more language selection errors when switching from their L2 to the L1 than vice versa. In the EEG, we observed a robust ERN effect following language selection errors compared to correct responses, reflecting monitoring of speech errors. Most interestingly, the ERN effect was enlarged when the speakers were switching to their L2 (less conflict) compared to switching to the L1 (more conflict). Our findings do not support the conflict-based monitoring model. We discuss an alternative account in terms of error prediction and reinforcement learning.

Abstract

Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. We examined the relative contribution of top-down cognitive control and bottom-up language priming to these errors. Unbalanced Dutch-English bilinguals named pictures and were cued to switch between languages under time pressure. We also manipulated the number of same-language trials before a switch (long vs. short runs). Results show that speakers made more language selection errors when switching from their second language (L2) to the first language (L1) than vice versa. Furthermore, they made more errors when switching to the L1 after a short compared to a long run of L2 trials. In the reverse switching direction (L1 to L2), run length had no effect. These findings are most compatible with an account of language selection errors that assigns a strong role to top-down processes of cognitive control.

Abstract

Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.

Abstract

In informal interaction, speakers rarely thank a person who has complied with a request. Examining data from British English, German, Italian, Polish, and Telugu, we ask when speakers do thank after compliance. The results show that thanking treats the other’s assistance as going beyond what could be taken for granted in the circumstances. Coupled with the rareness of thanking after requests, this suggests that cooperation is to a great extent governed by expectations of helpfulness, which can be long-standing, or built over the course of a particular interaction. The higher frequency of thanking in some languages (such as English or Italian) suggests that cultures differ in the importance they place on recognizing the other’s agency in doing as requested.

Abstract

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature.

Abstract

Change in linguistic prosody generates a mismatch negativity response (MMN), indicating neural representation of linguistic prosody, while change in affective prosody generates a positive response (P3a), reflecting its motivational salience. However, the neural response to concurrent affective and linguistic prosody is unknown. The present paper investigates the integration of these two prosodic features in the brain by examining the neural response to separate and concurrent processing by electroencephalography (EEG). A spoken pair of Swedish words—[ˈfɑ́ːsɛn] phase and [ˈfɑ̀ːsɛn] damn—that differed in emotional semantics due to linguistic prosody was presented to 16 subjects in an angry and neutral affective prosody using a passive auditory oddball paradigm. Acoustically matched pseudowords—[ˈvɑ́ːsɛm] and [ˈvɑ̀ːsɛm]—were used as controls. Following the constructionist concept of emotions, accentuating the conceptualization of emotions based on language, it was hypothesized that concurrent affective and linguistic prosody with the same valence—angry [ˈfɑ̀ːsɛn] damn—would elicit a unique late EEG signature, reflecting the temporal integration of affective voice with emotional semantics of prosodic origin. In accordance, linguistic prosody elicited an MMN at 300–350 ms, and affective prosody evoked a P3a at 350–400 ms, irrespective of semantics. Beyond these responses, concurrent affective and linguistic prosody evoked a late positive component (LPC) at 820–870 ms in frontal areas, indicating the conceptualization of affective prosody based on linguistic prosody. This study provides evidence that the brain does not only distinguish between these two functions of prosody but also integrates them based on language and experience.

Abstract

There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques—even simple ones that are straightforward to use—can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space.

Abstract

The Corpus NGT

Abstract

Although in many respects sign languages have a similar structure to that of spoken languages, the different modalities in which both types of languages are expressed cause differences in structure as well. One of the most striking differences between spoken and sign languages is the influence of the interface between grammar and PF on the surface form of utterances. Spoken language words and phrases are in general characterized by sequential strings of sounds, morphemes and words, while in sign languages we find that many phonemes, morphemes, and even words are expressed simultaneously. A linguistic model should be able to account for the structures that occur in both spoken and sign languages. In this paper, I will discuss the morphological/ morphosyntactic structure of signs in Nederlandse Gebarentaal (Sign Language of the Netherlands, henceforth NGT), with special focus on the components ‘place of articulation’ and ‘handshape’. I will focus on their multiple functions in the grammar of NGT and argue that the framework of Distributed Morphology (DM), which accounts for word formation in spoken languages, is also suited to account for the formation of structures in sign languages. First I will introduce the phonological and morphological structure of NGT signs. Then, I will briefly outline the major characteristics of the DM framework. Finally, I will account for signs that have the same surface form but have a different morphological structure by means of that framework.