Publications

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.