Publications

Abstract

Previous studies, using the Continuous Flash Suppression (CFS) paradigm, observed that (Western) university students are better able to detect otherwise invisible pictures of objects when they are presented with the corresponding spoken word shortly before the picture appears. Here we attempted to replicate this effect with non-Western university students in Goa (India). A second aim was to explore the performance of (non-Western) meditators practicing Sudarshan Kriya Yoga in Goa in the same task. Some previous literature suggests that meditators may excel in some tasks that tap visual attention, for example by exercising better endogenous and exogenous control of visual awareness than non-meditators. The present study replicated the finding that congruent spoken cue words lead to significantly higher detection sensitivity than incongruent cue words in non-Western university students. Our exploratory meditator group also showed this detection effect but both frequentist and Bayesian analyses suggest that the practice of meditation did not modulate it. Overall, our results provide further support for the notion that spoken words can activate low-level category-specific visual features that boost the basic capacity to detect the presence of a visual stimulus that has those features. Further research is required to conclusively test whether meditation can modulate visual detection abilities in CFS and similar tasks.

Abstract

In the present paper we describe the Enhanced Literate Mind (ELM) hypothesis. As individuals learn to read and write, they are, from then on, exposed to extensive written-language input and become literate. We propose that acquisition and proficient processing of written language (‘literacy’) leads to, both, increased language knowledge as well as enhanced language and non-language (perceptual and cognitive) skills. We also suggest that all neurotypical native language users, including illiterate, low literate, and high literate individuals, share a Basic Language Cognition (BLC) in the domain of oral informal language. Finally, we discuss the possibility that the acquisition of ELM leads to some degree of ‘knowledge parallelism’ between BLC and ELM in literate language users, which has implications for empirical research on individual and situational differences in spoken language processing.

Abstract

Literacy is in decline in many parts of the world, accompanied by drops in associated cognitive skills (including IQ) and an increasing susceptibility to fake news. It is possible that the recent explosive growth and widespread deployment of Large Language Models (LLMs) might exacerbate this trend, but there is also a chance that LLMs can help turn things around. We argue that cognitive science is ideally suited to help steer future literacy development in the right direction by challenging and informing current educational practices and policy. Cognitive scientists have the right interdisciplinary skills to study, analyze, evaluate, and change LLMs to facilitate their critical use, to encourage turn-taking that promotes rather than hinders literacy, to support literacy acquisition in diverse and equitable ways, and to scaffold potential future changes in what it means to be literate. We urge cognitive scientists to take up this mantle—the future impact of LLMs on human literacy skills is too important to be left to the large, predominately US-based tech companies.

Abstract

We investigated prediction skills of adult heritage speakers and the role of written and spoken language experience on predictive processing. Using visual world eye-tracking, we focused on predictive use of case-marking cues in verb-medial and verb-final sentences in Turkish with adult Turkish heritage speakers (N = 25) and Turkish monolingual speakers (N = 24). Heritage speakers predicted in verb-medial sentences (when verb-semantic and case-marking cues were available), but not in verb-final sentences (when only case-marking cues were available) while monolinguals predicted in both. Prediction skills of heritage speakers were modulated by their spoken language experience in Turkish and written language experience in both languages. Overall, these results strongly suggest that verb-semantic information is needed to scaffold the use of morphosyntactic cues for prediction in heritage speakers. The findings also support the notion that both spoken and written language experience play an important role in predictive spoken language processing.

Abstract

Previous research suggests that literacy, specifically learning alphabetic letter-to-phoneme mappings, modifies online speech processing, and enhances brain responses, as indexed by the blood-oxygenation level dependent signal (BOLD), to speech in auditory areas associated with phonological processing (Dehaene et al., 2010). However, alphabets are not the only orthographic systems in use in the world, and hundreds of millions of individuals speak languages that are not written using alphabets. In order to make claims that literacy per se has broad and general consequences for brain responses to speech, one must seek confirmatory evidence from non-alphabetic literacy. To this end, we conducted a longitudinal fMRI study in India probing the effect of literacy in Devanagari, an abugida, on functional connectivity and cerebral responses to speech in 91 variously literate Hindi-speaking male and female human participants. Twenty-two completely illiterate participants underwent six months of reading and writing training. Devanagari literacy increases functional connectivity between acoustic-phonetic and graphomotor brain areas, but we find no evidence that literacy changes brain responses to speech, either in cross-sectional or longitudinal analyses. These findings shows that a dramatic reconfiguration of the neurofunctional substrates of online speech processing may not be a universal result of learning to read, and suggest that the influence of writing on speech processing should also be investigated.

Abstract

A recent trend in psycholinguistic research has been to posit prediction as an essential function of language processing. The present paper develops a linguistic perspective on viewing prediction in terms of pre-activation. We describe what predictions are and how they are produced. Our basic premises are that (a) no prediction can be made without knowledge to support it; and (b) it is therefore necessary to characterize the precise form of that knowledge, as revealed by a suitable theory of linguistic representations. We describe the Parallel Architecture (PA: Jackendoff, 2002; Jackendoff and Audring, 2020), which makes explicit our commitments about linguistic representations, and we develop an account of processing based on these representations. Crucial to our account is that what have been traditionally treated as derivational rules of grammar are formalized by the PA as lexical items, encoded in the same format as words. We then present a theory of prediction in these terms: linguistic input activates lexical items whose beginning (or incipit) corresponds to the input encountered so far; and prediction amounts to pre-activation of the as yet unheard parts of those lexical items (the remainder). Thus the generation of predictions is a natural byproduct of processing linguistic representations. We conclude that the PA perspective on pre-activation provides a plausible account of prediction in language processing that bridges linguistic and psycholinguistic theorizing.

Abstract

Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of real-world events to influence the moment-by-moment interpretation of a story by 7-year-old children and adults. Seven-year-olds were less effective at bypassing stored real-world knowledge during real-time interpretation than adults. Our results suggest that children privilege stored semantic knowledge over situation-specific information presented in a fictional story context. We suggest that 7-year-olds’ canonical semantic and conceptual relations are sufficiently strongly rooted in statistical patterns in language that have consolidated over time that they overwhelm new and unexpected information even when the latter is fantastical and highly salient.

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

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre- registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

Abstract

Prediction is one characteristic of the human mind. But what does it mean to say the mind is a ’prediction machine’ and inherently forward looking as is frequently claimed? In natural languages, many contexts are not easily predictable in a forward fashion. In English for example many frequent verbs do not carry unique meaning on their own, but instead rely on another word or words that follow them to become meaningful. Upon reading take a the processor often cannot easily predict walk as the next word. But the system can ‘look back’ and integrate walk more easily when it follows take a (e.g., as opposed to make|get|have a walk). In the present paper we provide further evidence for the importance of both forward and backward looking in language processing. In two self-paced reading tasks and an eye-tracking reading task, we found evidence that adult English native speakers’ sensitivity to word forward and backward conditional probability significantly explained variance in reading times over and above psycholinguistic predictors of reading latencies. We conclude that both forward and backward-looking (prediction and integration) appear to be important characteristics of language processing. Our results thus suggest that it makes just as much sense to call the mind an ’integration machine’ which is inherently backward looking.

Abstract

Three eye-tracking experiments investigated the impact of the complexity of the visual environment on the likelihood of word-object mapping taking place at phonological, semantic and visual levels of representation during language-mediated visual search. Dutch participants heard spoken target words while looking at four objects embedded in displays of different complexity and indicated the presence or absence of the target object. During filler trials the target objects were present, but during experimental trials they were absent and the display contained various competitor objects. For example, given the target word “beaker”, the display contained a phonological (a beaver, bever), a shape (a bobbin, klos), a semantic (a fork, vork) competitor, and an unrelated distractor (an umbrella, paraplu). When objects were presented in simple four-object displays (Experiment 2), there were clear attentional biases to all three types of competitors replicating earlier research (Huettig and McQueen, 2007). When the objects were embedded in complex scenes including four human-like characters or four meaningless visual shapes (Experiments 1, 3), there were biases in looks to visual and semantic but not to phonological competitors. In both experiments, however, we observed evidence for inhibition in looks to phonological competitors, which suggests that the phonological forms of the objects nevertheless had been retrieved. These findings suggest that phonological word-object mapping is contingent upon the nature of the visual environment and add to a growing body of evidence that the nature of our visual surroundings induces particular modes of processing during language-mediated visual search.

Abstract

It is now well-established that anticipation of up-coming input is a key characteristic of spoken language comprehension. It has also frequently been observed that literacy influences spoken language processing. Here we investigated whether anticipatory spoken language processing is related to individuals’ word reading abilities. Dutch adults with dyslexia and a control group participated in two eye-tracking experiments. Experiment 1 was conducted to assess whether adults with dyslexia show the typical language-mediated eye gaze patterns. Eye movements of both adults with and without dyslexia closely replicated earlier research: spoken language is used to direct attention to relevant objects in the environment in a closely time-locked manner. In Experiment 2, participants received instructions (e.g., "Kijk naar deCOM afgebeelde pianoCOM", look at the displayed piano) while viewing four objects. Articles (Dutch “het” or “de”) were gender-marked such that the article agreed in gender only with the target and thus participants could use gender information from the article to predict the target object. The adults with dyslexia anticipated the target objects but much later than the controls. Moreover, participants' word reading scores correlated positively with their anticipatory eye movements. We conclude by discussing the mechanisms by which reading abilities may influence predictive language processing.

Abstract

The notion that prediction is a fundamental principle of human information processing has been en vogue over recent years. The investigation of language processing may be particularly illuminating for testing this claim. Linguists traditionally have argued prediction plays only a minor role during language understanding because of the vast possibilities available to the language user as each word is encountered. In the present review I consider four central questions of anticipatory language processing: Why (i.e. what is the function of prediction in language processing)? What (i.e. what are the cues used to predict up-coming linguistic information and what type of representations are predicted)? How (what mechanisms are involved in predictive language processing and what is the role of possible mediating factors such as working memory)? When (i.e. do individuals always predict up-coming input during language processing)? I propose that prediction occurs via a set of diverse PACS (production-, association-, combinatorial-, and simulation-based prediction) mechanisms which are minimally required for a comprehensive account of predictive language processing. Models of anticipatory language processing must be revised to take multiple mechanisms, mediating factors, and situational context into account. Finally, I conjecture that the evidence considered here is consistent with the notion that prediction is an important aspect but not a fundamental principle of language processing.

Abstract

Recent experimental evidence from cognitive psychology and cognitive neuroscience shows that reading acquisition has non-trivial consequences for cognitive processes other than reading per se. In the present chapter I present evidence from three areas of cognition: phonological processing, prediction in language processing, and visual search. These findings suggest that literacy on cognition influences are far-reaching. This implies that a good understanding of the dramatic impact of literacy acquisition on the human mind is an important prerequisite for successful education policy development and guidance of educational support.

Abstract

During language comprehension, listeners often anticipate upcoming information. This can draw listeners’ overt attention to visually presented objects before the objects are referred to. We investigated to what extent the anticipatory mechanisms involved in such language-mediated attention rely on specific verbal factors and on processes shared with other domains of cognition. Participants listened to sentences ending in a highly predictable word (e.g., “In 1969 Neil Armstrong was the first man to set foot on the moon”) while viewing displays containing three unrelated distractor objects and a critical object, which was either the target object (e.g., a moon), or an object with a similar shape (e.g., a tomato), or an unrelated control object (e.g., rice). Language-mediated anticipatory eye movements to targets and shape competitors were observed. Importantly, looks to the shape competitor were systematically related to individual differences in anticipatory attention, as indexed by a spatial cueing task: Participants whose responses were most strongly facilitated by predictive arrow cues also showed the strongest effects of predictive language input on their eye movements. By contrast, looks to the target were related to individual differences in vocabulary size and verbal fluency. The results suggest that verbal and nonverbal factors contribute to different types of language-mediated eye movement. The findings are consistent with multiple-mechanism accounts of predictive language processing.