Les yeux grands fermés : littératie, phonologie et résonance adaptative

International audienceIn the present article, I question the claim that a literacy bias is responsible for the fact that major theoreticians underestimated or ignored the role of literacy in spoken language. Instead, I argue that the strongly modular, localist and symbolic information-processing approach to cognition that has dominated psychological science throughout the 20th century has prevented cross-fertilization and the emergence of a unified theory of written and spoken language processing. I show that the recognition of the fundamental role of phonology in reading had suffered from exactly the same “bias”, which had eventually been overcome not by breaking the “literacy glasses” but by shifting theoretical frameworks. I conclude by arguing that a marriage between cognitive science, evolutionary biology and neuroscience is needed more than ever to develop a unified, developmentally, biologically and evolutionary plausible theory of written and spoken language.Dans le présent article, je remets en question l’idée selon laquelle un « biais de littératie » est responsable du fait que les principaux théoriciens ont sous-estimé ou ignoré le rôle de la littératie dans l’étude du langage oral. Je développe l’hypothèse selon laquelle l’approche modulaire, localiste et symbolique du traitement de l’information qui a dominé les sciences psychologiques tout au long du xxe siècle a empêché l’émergence d’une théorie unifiée du traitement du langage écrit et parlé. Je montre que le même « biais » explique pourquoi il fallait des dizaines d’années pour reconnaître le rôle fondamental du traitement phonologique lors de la lecture. Je conclus en affirmant qu’un mariage entre les sciences cognitives, la biologie évolutive et les neurosciences est plus que jamais nécessaire pour développer une théorie unifiée du langage écrit et parlé plausible sur le plan développemental et biologique

A Dual-Route Approach to Orthographic Processing

In the present theoretical note we examine how different learning constraints, thought to be involved in optimizing the mapping of print to meaning during reading acquisition, might shape the nature of the orthographic code involved in skilled reading. On the one hand, optimization is hypothesized to involve selecting combinations of letters that are the most informative with respect to word identity (diagnosticity constraint), and on the other hand to involve the detection of letter combinations that correspond to pre-existing sublexical phonological and morphological representations (chunking constraint). These two constraints give rise to two different kinds of prelexical orthographic code, a coarse-grained and a fine-grained code, associated with the two routes of a dual-route architecture. Processing along the coarse-grained route optimizes fast access to semantics by using minimal subsets of letters that maximize information with respect to word identity, while coding for approximate within-word letter position independently of letter contiguity. Processing along the fined-grained route, on the other hand, is sensitive to the precise ordering of letters, as well as to position with respect to word beginnings and endings. This enables the chunking of frequently co-occurring contiguous letter combinations that form relevant units for morpho-orthographic processing (prefixes and suffixes) and for the sublexical translation of print to sound (multi-letter graphemes)

Understanding Dyslexia Through Personalized Large-Scale Computational Models

International audienceLearning to read is foundational for literacy development, yet many children in primary school fail to become efficient readers despite normal intelligence and schooling. This condition, referred to as developmental dyslexia, has been hypothesized to occur because of deficits in vision, attention, auditory and temporal processes, and phonology and language. Here, we used a developmentally plausible computational model of reading acquisition to investigate how the core deficits of dyslexia determined individual learning outcomes for 622 children (388 with dyslexia). We found that individual learning trajectories could be simulated on the basis of three component skills related to orthography, phonology, and vocabulary. In contrast, single-deficit models captured the means but not the distribution of reading scores, and a model with noise added to all representations could not even capture the means. These results show that heterogeneity and individual differences in dyslexia profiles can be simulated only with a personalized computational model that allows for multiple deficits

Literacy Affects Spoken Language in a Non-Linguistic Task: An ERP Study

It is now commonly accepted that orthographic information influences spoken word recognition in a variety of laboratory tasks (lexical decision, semantic categorization, gender decision). However, it remains a hotly debated issue whether or not orthography would influence normal word perception in passive listening. That is, the argument has been made that orthography might only be activated in laboratory tasks that require lexical or semantic access in some form or another. It is possible that these rather “unnatural” tasks invite participants to use orthographic information in a strategic way to improve task performance. To put the strategy account to rest, we conducted an event-related brain potential (ERP) study, in which participants were asked to detect a 500-ms-long noise burst that appeared on 25% of the trials (Go trials). In the NoGo trials, we presented spoken words that were orthographically consistent or inconsistent. Thus, lexical and/or semantic processing was not required in this task and there was no strategic benefit in computing orthography to perform this task. Nevertheless, despite the non-linguistic nature of the task, we replicated the consistency effect that has been previously reported in lexical decision and semantic tasks (i.e., inconsistent words produce more negative ERPs than consistent words as early as 300 ms after the onset of the spoken word). These results clearly suggest that orthography automatically influences word perception in normal listening even if there is no strategic benefit to do so. The results are explained in terms of orthographic restructuring of phonological representations

Online activation of L1 Danish orthography enhances spoken word recognition of Swedish

It has been reported that speakers of Danish understand more Swedish than vice versa. One reason for this asymmetry might be that spoken Swedish is closer to written Danish than vice versa. We hypothesise that literate speakers of Danish use their orthographic knowledge of Danish to decode spoken Swedish. To test this hypothesis, first-language (L1) Danish speakers were confronted with spoken Swedish in a translation task. Event-related brain potentials (ERPs) were elicited to study the online brain responses during decoding operations. Results showed that ERPs to words whose Swedish pronunciation was inconsistent with the Danish spelling were significantly more negative-going than ERPs to words whose Swedish pronunciation was consistent with the Danish spelling between 750 ms and 900 ms after stimulus onset. Together with higher word-recognition scores for consistent items, our data provide strong evidence that online activation of L1 orthography enhances word recognition of spoken Swedish in literate speakers of Danish

Orthographic Contamination of Broca’s Area

Strong evidence has accumulated over the past years suggesting that orthography plays a role in spoken language processing. It is still unclear, however, whether the influence of orthography on spoken language results from a co-activation of posterior brain areas dedicated to low-level orthographic processing or whether it results from orthographic restructuring of phonological representations located in the anterior perisylvian speech network itself. To test these hypotheses, we ran a fMRI study that tapped orthographic processing in the visual and auditory modalities. As a marker for orthographic processing, we used the orthographic decision task in the visual modality and the orthographic consistency effect in the auditory modality. Results showed no specific orthographic activation neither for the visual nor the auditory modality in left posterior occipito-temporal brain areas that are thought to host the visual word form system. In contrast, specific orthographic activation was found both for the visual and auditory modalities at anterior sites belonging to the perisylvian region: the left dorsal–anterior insula and the left inferior frontal gyrus. These results are in favor of the restructuring hypothesis according to which learning to read acts like a “virus” that permanently contaminates the spoken language system

A Hierarchical Diffusion Model Analysis of Age Effects on Visual Word Recognition

Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423) performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modeling approach, which provides more information than standard response time/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modeling allowed us to differentiate between age- related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing, whereas a general age- disadvantage was observed at the sublexical and phonological levels. Low- performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose age-related disadvantages for older readers to be caused by inefficiencies in temporal sampling and activation and/or inhibition processes

Orthographic consistency influences morphological processing in reading aloud: Evidence from a cross‐linguistic study

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Structural gray matter features and behavioral preliterate skills predict future literacy – A machine learning approach

When children learn to read, their neural system undergoes major changes to become responsive to print. There seem to be nuanced interindividual differences in the neurostructural anatomy of regions that later become integral parts of the reading network. These differences might affect literacy acquisition and, in some cases, might result in developmental disorders like dyslexia. Consequently, the main objective of this longitudinal study was to investigate those interindividual differences in gray matter morphology that might facilitate or hamper future reading acquisition. We used a machine learning approach to examine to what extent gray matter macrostructural features and cognitive-linguistic skills measured before formal literacy teaching could predict literacy 2 years later. Forty-two native German-speaking children underwent T1-weighted magnetic resonance imaging and psychometric testing at the end of kindergarten. They were tested again 2 years later to assess their literacy skills. A leave-one-out cross-validated machine-learning regression approach was applied to identify the best predictors of future literacy based on cognitive-linguistic preliterate behavioral skills and cortical measures in a priori selected areas of the future reading network. With surprisingly high accuracy, future literacy was predicted, predominantly based on gray matter volume in the left occipito-temporal cortex and local gyrification in the left insular, inferior frontal, and supramarginal gyri. Furthermore, phonological awareness significantly predicted future literacy. In sum, the results indicate that the brain morphology of the large-scale reading network at a preliterate age can predict how well children learn to read

Using Virtual Reality to Assess Reading Fluency in Children

Here we provide a proof-of-concept for the use of virtual reality (VR) goggles to assess reading behavior in beginning readers. Children performed a VR version of a lexical decision task that allowed us to record eye-movements. External validity was assessed by comparing the VR measures (lexical decision RT and accuracy, gaze durations and refixation probabilities) to a gold standard reading fluency test—the One-Minute Reading test. We found that the VR measures correlated strongly with the classic fluency measure. We argue that VR-based techniques provide a valid and child-friendly way to study reading behavior in a school environment. Importantly, they enable not only the collection of a richer dataset than standard behavioral assessments but also the possibility to tightly control the environment