Beyond the tried and true: How virtual reality, dialog setups, and a focus on multimodality can take bilingual language production research forward.

Bilinguals possess the ability of expressing themselves in more than one language, and typically do so in contextually rich and dynamic settings. Theories and models have indeed long considered context factors to affect bilingual language production in many ways. However, most experimental studies in this domain have failed to fully incorporate linguistic, social, or physical context aspects, let alone combine them in the same study. Indeed, most experimental psycholinguistic research has taken place in isolated and constrained lab settings with carefully selected words or sentences, rather than under rich and naturalistic conditions. We argue that the most influential experimental paradigms in the psycholinguistic study of bilingual language production fall short of capturing the effects of context on language processing and control presupposed by prominent models. This paper therefore aims to enrich the methodological basis for investigating context aspects in current experimental paradigms and thereby move the field of bilingual language production research forward theoretically. After considering extensions of existing paradigms proposed to address context effects, we present three far-ranging innovative proposals, focusing on virtual reality, dialog situations, and multimodality in the context of bilingual language production.

Emotions, fast and slow: processing of emotion words is affected by individual differences in need for affect and narrative absorption.

Emotional words have consistently been shown to be processed differently than neutral words. However, few studies have examined individual variability in emotion word processing with longer, ecologically valid stimuli (beyond isolated words, sentences, or paragraphs). In the current study, we re-analysed eye-tracking data collected during story reading to reveal how individual differences in need for affect and narrative absorption impact the speed of emotion word reading. Word emotionality was indexed by affective-aesthetic potentials (AAP) calculated by a sentiment analysis tool. We found that individuals with higher levels of need for affect and narrative absorption read positive words more slowly. On the other hand, these individual differences did not influence the reading time of more negative words, suggesting that high need for affect and narrative absorption are characterised by a positivity bias only. In general, unlike most previous studies using more isolated emotion word stimuli, we observed a quadratic (U-shaped) effect of word emotionality on reading speed, such that both positive and negative words were processed more slowly than neutral words. Taken together, this study emphasises the importance of taking into account individual differences and task context when studying emotion word processing.

Different kinds of simulation during literary reading: Insights from a combined fMRI and eye-tracking study.

Mental simulation is an important aspect of narrative reading. In a previous study, we found that gaze durations are differentially impacted by different kinds of mental simulation. Motor simulation, perceptual simulation, and mentalizing as elicited by literary short stories influenced eye movements in distinguishable ways (Mak & Willems, 2019). In the current study, we investigated the existence of a common neural locus for these different kinds of simulation. We additionally investigated whether individual differences during reading, as indexed by the eye movements, are reflected in domain-specific activations in the brain. We found a variety of brain areas activated by simulation-eliciting content, both modality-specific brain areas and a general simulation area. Individual variation in percent signal change in activated areas was related to measures of story appreciation as well as personal characteristics (i.e., transportability, perspective taking). Taken together, these findings suggest that mental simulation is supported by both domain-specific processes grounded in previous experiences, and by the neural mechanisms that underlie higher-order language processing (e.g., situation model building, event indexing, integration).

MA-EM: A neurocognitive model for understanding mixed and ambiguous emotions and morality.

Understanding emotions and moral intentions of other people is integral to being human. Humanities scholars have long recognized the complex and ambiguous nature of emotions and morality. People are rarely 'just' happy, or sad. Neither are they 'just' good or bad people. Despite this, most knowledge about the psychological and neural basis of emotions and moral understanding comes from experiments investigating unidimensional and non-ambiguous emotions and morality. The goal of this paper is twofold. First I want to point out why mixed and ambiguous emotions and morality are a promising research topic for cognitive neuroscientists. Observing or experiencing mixed or ambiguous emotions and morality tends to have a strong impact on humans. This impact is clearly visible in narratives and fiction, and I will argue that narratives make an excellent stimulus to study the effects of emotional and moral ambiguity. Second, I will sketch a model to help guide research in this promising corner of human cognition.

Different routes to liking: how readers arrive at narrative evaluations.

When two people read the same story, they might both end up liking it very much. However, this does not necessarily mean that their reasons for liking it were identical. We therefore ask what factors contribute to "liking" a story, and-most importantly-how people vary in this respect. We found that readers like stories because they find them interesting, amusing, suspenseful and/or beautiful. However, the degree to which these components of appreciation were related to how much readers liked stories differed between individuals. Interestingly, the individual slopes of the relationships between many of the components and liking were (positively or negatively) correlated. This indicated, for instance, that individuals displaying a relatively strong relationship between interest and liking, generally display a relatively weak relationship between sadness and liking. The individual differences in the strengths of the relationships between the components and liking were not related to individual differences in expertize, a characteristic strongly associated with aesthetic appreciation of visual art. Our work illustrates that it is important to take into consideration the fact that individuals differ in how they arrive at their evaluation of literary stories, and that it is possible to quantify these differences in empirical experiments. Our work suggests that future research should be careful about "overfitting" theories of aesthetic appreciation to an "idealized reader," but rather take into consideration variations across individuals in the reason for liking a particular story.

Reading about minds: The social-cognitive potential of narratives.

It is often argued that narratives improve social cognition, either by appealing to social-cognitive abilities as we engage with the story world and its characters, or by conveying social knowledge. Empirical studies have found support for both a correlational and a causal link between exposure to (literary, fictional) narratives and social cognition. However, a series of failed replications has cast doubt on the robustness of these claims. Here, we review the existing empirical literature and identify open questions and challenges. An important conclusion of the review is that previous research has given too little consideration to the diversity of narratives, readers, and social-cognitive processes involved in the social-cognitive potential of narratives. We therefore establish a research agenda, proposing that future research should focus on (1) the specific text characteristics that drive the social-cognitive potential of narratives, (2) the individual differences between readers with respect to their sensitivity to this potential, and (3) the various aspects of social cognition that are potentially affected by reading narratives. Our recommendations can guide the design of future studies that will help us understand how, for whom, and in what respect exposure to narratives can advantage social cognition.

Reading Minds, Reading Stories: Social-Cognitive Abilities Affect the Linguistic Processing of Narrative Viewpoint.

Although various studies have shown that narrative reading draws on social-cognitive abilities, not much is known about the precise aspects of narrative processing that engage these abilities. We hypothesized that the linguistic processing of narrative viewpoint-expressed by elements that provide access to the inner world of characters-might play an important role in engaging social-cognitive abilities. Using eye tracking, we studied the effect of lexical markers of perceptual, cognitive, and emotional viewpoint on eye movements during reading of a 5,000-word narrative. Next, we investigated how this relationship was modulated by individual differences in social-cognitive abilities. Our results show diverging patterns of eye movements for perceptual viewpoint markers on the one hand, and cognitive and emotional viewpoint markers on the other. Whereas the former are processed relatively fast compared to non-viewpoint markers, the latter are processed relatively slow. Moreover, we found that social-cognitive abilities impacted the processing of words in general, and of perceptual and cognitive viewpoint markers in particular, such that both perspective-taking abilities and self-reported perspective-taking traits facilitated the processing of these markers. All in all, our study extends earlier findings that social cognition is of importance for story reading, showing that individual differences in social-cognitive abilities are related to the linguistic processing of narrative viewpoint.

How context changes the neural basis of perception and language.

Cognitive processes-from basic sensory analysis to language understanding-are typically contextualized. While the importance of considering context for understanding cognition has long been recognized in psychology and philosophy, it has not yet had much impact on cognitive neuroscience research, where cognition is often studied in decontextualized paradigms. Here, we present examples of recent studies showing that context changes the neural basis of diverse cognitive processes, including perception, attention, memory, and language. Within the domains of perception and language, we review neuroimaging results showing that context interacts with stimulus processing, changes activity in classical perception and language regions, and recruits additional brain regions that contribute crucially to naturalistic perception and language. We discuss how contextualized cognitive neuroscience will allow for discovering new principles of the mind and brain.

Distinguishing Syntactic Operations in the Brain: Dependency and Phrase-Structure Parsing.

Finding the structure of a sentence-the way its words hold together to convey meaning-is a fundamental step in language comprehension. Several brain regions, including the left inferior frontal gyrus, the left posterior superior temporal gyrus, and the left anterior temporal pole, are supposed to support this operation. The exact role of these areas is nonetheless still debated. In this paper we investigate the hypothesis that different brain regions could be sensitive to different kinds of syntactic computations. We compare the fit of phrase-structure and dependency structure descriptors to activity in brain areas using fMRI. Our results show a division between areas with regard to the type of structure computed, with the left anterior temporal pole and left inferior frontal gyrus favouring dependency structures and left posterior superior temporal gyrus favouring phrase structures.

Narratives for Neuroscience.

People organize and convey their thoughts according to narratives. However, neuroscientists are often reluctant to incorporate narrative stimuli into their experiments. We argue that narratives deserve wider adoption in human neuroscience because they tap into the brain's native machinery for representing the world and provide rich variability for testing hypotheses.

Word skipping as an indicator of individual reading style during literary reading.

Decades of research have established that the content of language (e.g. lexical characteristics of words) predicts eye movements during reading. Here we investigate whether there exist individual differences in 'stable' eye movement patterns during narrative reading. We computed Euclidean distances from correlations between gaze durations time courses (word level) across 102 participants who each read three literary narratives in Dutch. The resulting distance matrices were compared between narratives using a Mantel test. The results show that correlations between the scaling matrices of different narratives are relatively weak (r ≤ .11) when missing data points are ignored. However, when including these data points as zero durations (i.e. skipped words), we found significant correlations between stories (r > .51). Word skipping was significantly positively associated with print exposure but not with self-rated attention and story-world absorption, suggesting that more experienced readers are more likely to skip words, and do so in a comparable fashion. We interpret this finding as suggesting that word skipping might be a stable individual eye movement pattern.

Is less readable liked better? The case of font readability in poetry appreciation.

Previous research shows conflicting findings for the effect of font readability on comprehension and memory for language. It has been found that-perhaps counterintuitively-a hard to read font can be beneficial for language comprehension, especially for difficult language. Here we test how font readability influences the subjective experience of poetry reading. In three experiments we tested the influence of poem difficulty and font readability on the subjective experience of poems. We specifically predicted that font readability would have opposite effects on the subjective experience of easy versus difficult poems. Participants read poems which could be more or less difficult in terms of conceptual or structural aspects, and which were presented in a font that was either easy or more difficult to read. Participants read existing poems and subsequently rated their subjective experience (measured through four dependent variables: overall liking, perceived flow of the poem, perceived topic clarity, and perceived structure). In line with previous literature we observed a Poem Difficulty x Font Readability interaction effect for subjective measures of poetry reading. We found that participants rated easy poems as nicer when presented in an easy to read font, as compared to when presented in a hard to read font. Despite the presence of the interaction effect, we did not observe the predicted opposite effect for more difficult poems. We conclude that font readability can influence reading of easy and more difficult poems differentially, with strongest effects for easy poems.

The Storytelling Brain: How Neuroscience Stories Help Bridge the Gap between Research and Society.

Active communication between researchers and society is necessary for the scientific community's involvement in developing science-based policies. This need is recognized by governmental and funding agencies that compel scientists to increase their public engagement and disseminate research findings in an accessible fashion. Storytelling techniques can help convey science by engaging people's imagination and emotions. Yet, many researchers are uncertain about how to approach scientific storytelling, or feel they lack the tools to undertake it. Here we explore some of the techniques intrinsic to crafting scientific narratives, as well as the reasons why scientific storytelling may be an optimal way of communicating research to nonspecialists. We also point out current communication gaps between science and society, particularly in the context of neurodiverse audiences and those that include neurological and psychiatric patients. Present shortcomings may turn into areas of synergy with the potential to link neuroscience education, research, and advocacy.

Frequency-specific brain dynamics related to prediction during language comprehension.

The brain's remarkable capacity to process spoken language virtually in real time requires fast and efficient information processing machinery. In this study, we investigated how frequency-specific brain dynamics relate to models of probabilistic language prediction during auditory narrative comprehension. We recorded MEG activity while participants were listening to auditory stories in Dutch. Using trigram statistical language models, we estimated for every word in a story its conditional probability of occurrence. On the basis of word probabilities, we computed how unexpected the current word is given its context (word perplexity) and how (un)predictable the current linguistic context is (word entropy). We then evaluated whether source-reconstructed MEG oscillations at different frequency bands are modulated as a function of these language processing metrics. We show that theta-band source dynamics are increased in high relative to low entropy states, likely reflecting lexical computations. Beta-band dynamics are increased in situations of low word entropy and perplexity possibly reflecting maintenance of ongoing cognitive context. These findings lend support to the idea that the brain engages in the active generation and evaluation of predicted language based on the statistical properties of the input signal.

Taking common ground into account: Specifying the role of the mentalizing network in communicative language production.

Several studies have shown that communicative language production as compared to non-communicative language production recruits parts of the mentalizing or theory of mind network, yet the exact role of this network in communication remains underspecified. In this study, we therefore aimed to test under what conditions the mentalizing network contributes to communicative language production. We were especially interested in distinguishing between situations in which speakers have to consider which information they do or do not share with their addressee (common vs. privileged ground information). We therefore manipulated whether speakers had to distinguish between common and privileged ground in order to communicate efficiently with the listener, in addition to comparing language production in a communicative and a non-communicative context. Participants performed a referential communicative game in the MRI-scanner as well as a similar, non-communicative task. We found that the medial prefrontal cortex, a core region of the mentalizing network, is especially sensitive to communicative contexts in which speakers have to take their addressee's needs into account in order to communicate efficiently. In addition, we found neural differences between the communicative and the non-communicative settings before speakers started to plan their utterances, suggesting that they continuously update common ground in a communicative context.

Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension.

Recent decades have ushered in tremendous progress in understanding the neural basis of language. Most of our current knowledge on language and the brain, however, is derived from lab-based experiments that are far removed from everyday language use, and that are inspired by questions originating in linguistic and psycholinguistic contexts. In this paper we argue that in order to make progress, the field needs to shift its focus to understanding the neurobiology of naturalistic language comprehension. We present here a new conceptual framework for understanding the neurobiological organization of language comprehension. This framework is non-language-centered in the computational/neurobiological constructs it identifies, and focuses strongly on context. Our core arguments address three general issues: (i) the difficulty in extending language-centric explanations to discourse; (ii) the necessity of taking context as a serious topic of study, modeling it formally and acknowledging the limitations on external validity when studying language comprehension outside context; and (iii) the tenuous status of the language network as an explanatory construct. We argue that adopting this framework means that neurobiological studies of language will be less focused on identifying correlations between brain activity patterns and mechanisms postulated by psycholinguistic theories. Instead, they will be less self-referential and increasingly more inclined towards integration of language with other cognitive systems, ultimately doing more justice to the neurobiological organization of language and how it supports language as it is used in everyday life.

Distinguishable memory retrieval networks for collaboratively and non-collaboratively learned information.

Learning often occurs in communicative and collaborative settings, yet almost all research into the neural basis of memory relies on participants encoding and retrieving information on their own. We investigated whether learning linguistic labels in a collaborative context at least partly relies on cognitively and neurally distinct representations, as compared to learning in an individual context. Healthy human participants learned labels for sets of abstract shapes in three different tasks. They came up with labels with another person in a collaborative communication task (collaborative condition), by themselves (individual condition), or were given pre-determined unrelated labels to learn by themselves (arbitrary condition). Immediately after learning, participants retrieved and produced the labels aloud during a communicative task in the MRI scanner. The fMRI results show that the retrieval of collaboratively generated labels as compared to individually learned labels engages brain regions involved in understanding others (mentalizing or theory of mind) and autobiographical memory, including the medial prefrontal cortex, the right temporoparietal junction and the precuneus. This study is the first to show that collaboration during encoding affects the neural networks involved in retrieval.

When Fiction Is Just as Real as Fact: No Differences in Reading Behavior between Stories Believed to be Based on True or Fictional Events.

Experiments have shown that compared to fictional texts, readers read factual texts faster and have better memory for described situations. Reading fictional texts on the other hand seems to improve memory for exact wordings and expressions. Most of these studies used a "newspaper" vs. "literature" comparison. In the present study, we investigated the effect of reader's expectation to whether information is true or fictional with a subtler manipulation by labeling short stories as either based on true or fictional events. In addition, we tested whether narrative perspective or individual preference in perspective taking affects reading true or fictional stories differently. In an online experiment, participants (final N = 1,742) read one story which was introduced as based on true events or as fictional (factor fictionality). The story could be narrated in either 1st or 3rd person perspective (factor perspective). We measured immersion in and appreciation of the story, perspective taking, as well as memory for events. We found no evidence that knowing a story is fictional or based on true events influences reading behavior or experiential aspects of reading. We suggest that it is not whether a story is true or fictional, but rather expectations toward certain reading situations (e.g., reading newspaper or literature) which affect behavior by activating appropriate reading goals. Results further confirm that narrative perspective partially influences perspective taking and experiential aspects of reading.

Probabilistic language models in cognitive neuroscience: Promises and pitfalls.

Cognitive neuroscientists of language comprehension study how neural computations relate to cognitive computations during comprehension. On the cognitive part of the equation, it is important that the computations and processing complexity are explicitly defined. Probabilistic language models can be used to give a computationally explicit account of language complexity during comprehension. Whereas such models have so far predominantly been evaluated against behavioral data, only recently have the models been used to explain neurobiological signals. Measures obtained from these models emphasize the probabilistic, information-processing view of language understanding and provide a set of tools that can be used for testing neural hypotheses about language comprehension. Here, we provide a cursory review of the theoretical foundations and example neuroimaging studies employing probabilistic language models. We highlight the advantages and potential pitfalls of this approach and indicate avenues for future research.

Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.