Publications

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

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. α oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while β oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and β oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language comprehension. Twenty-two (18 female) Dutch native speakers listened to stories in Dutch and French while MEG was recorded. We used dependency parsing to identify three dependency states at each word: the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed forward models to predict α and β power from the dependency features. Results showed that dependency features predict α and β power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in α, while frontal and parietal, higher-order language regions, and motor regions are involved in β. Critically, α- and β-band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Because of the temporal similarity of the α-β responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and β oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.

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

Research into the neural foundation of perception asserts a model where top-down predictions modulate the bottom-up processing of sensory input. Despite becoming increasingly influential in cognitive neuroscience, the precise account of this predictive coding framework remains debated. In this study, we aim to contribute to this debate by investigating how predictions about prosody facilitate speech perception, and to shed light especially on lexical access influenced by simultaneous predictions in different domains, inter alia, prosodic and semantic. Using a passive auditory oddball paradigm, we examined neural responses to prosodic changes, leading to a semantic change as in Dutch nouns canon [ˈkaːnɔn] ‘cannon’ vs kanon [kaːˈnɔn] ‘canon’, and used acoustically identical pseudowords as controls. Results from twenty-eight native speakers of Dutch (age range 18–32 years) indicated an enhanced P50/N100 complex to prosodic change in pseudowords as well as an MMN response to both words and pseudowords. The enhanced P50/N100 response to pseudowords is claimed to indicate that all relevant auditory information is still processed by the brain, whereas the reduced response to words might reflect the suppression of information that has already been encoded. The MMN response to pseudowords and words, on the other hand, is best justified by the unification of previously established prosodic representations with sensory and semantic input respectively. This pattern of results is in line with the predictive coding framework acting on multiple levels and is of crucial importance to indicate that predictions about linguistic prosodic information are utilized by the brain as early as 50 ms.

Abstract

Language is used in communicative contexts to identify and successfully transmit new information that should be later remembered. In three studies, we used question–answer pairs, a naturalistic device for focusing information, to examine how properties of conversations inform later item memory. In Experiment 1, participants viewed three pictures while listening to a recorded question–answer exchange between two people about the locations of two of the displayed pictures. In a memory recognition test conducted online a day later, participants recognized the names of pictures that served as answers more accurately than the names of pictures that appeared as questions. This suggests that this type of focus indeed boosts memory. In Experiment 2, participants listened to the same items embedded in declarative sentences. There was a reduced memory benefit for the second item, confirming the role of linguistic focus on later memory beyond a simple serial-position effect. In Experiment 3, two participants asked and answered the same questions about objects in a dialogue. Here, answers continued to receive a memory benefit, and this focus effect was accentuated by language production such that information-seekers remembered the answers to their questions better than information-givers remembered the questions they had been asked. Combined, these studies show how people’s memory for conversation is modulated by the referential status of the items mentioned and by the speaker’s roles of the conversation participants.

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.