Reading proficiency predicts the extent of the right, but not left, perceptual span in older readers

Veldre, Aaron; Wong, Roslyn; Andrews, Sally

doi:10.3758/s13414-020-02185-x

Cited by 10 publications

(5 citation statements)

References 24 publications

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“…In contrast, Rayner et al (2009) observed that older adults showed no additional benefit from window sizes larger than one word to the right of fixation, and were more disrupted than younger readers by being deprived of one word to the left. Veldre et al (2021) recently confirmed the increased leftward extent of the perceptual span among older readers and showed that the size of the rightward span depended on written language proficiency. These findings suggest that older readers have a smaller and less asymmetric perceptual span than younger readers.…”

Section: Parafoveal Processing In Readingmentioning

confidence: 72%

Predictability effects and parafoveal processing in older readers.

Veldre¹,

Wong²,

Andrews³

2022

Psychology and Aging

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Normative aging is accompanied by visual and cognitive changes that impact the systems that are critical for fluent reading. The patterns of eye movements during reading displayed by older adults have been characterized as demonstrating a trade-off between longer forward saccades and more word skipping versus higher rates of regressions back to previously read text. This pattern is assumed to reflect older readers' reliance on top-down contextual information to compensate for reduced uptake of parafoveal information from yet-to-be fixated words. However, the empirical evidence for these assumptions is equivocal. This study investigated the depth of older readers' parafoveal processing as indexed by sensitivity to the contextual plausibility of parafoveal words in both neutral and highly constraining sentence contexts. The eye movements of 65 cognitively intact older adults (61-87 years) were compared with data previously collected from young adults in two sentence reading experiments in which critical target words were replaced by valid, plausible, related, or implausible previews until the reader fixated on the target word location. Older and younger adults showed equivalent plausibility preview benefits on first-pass reading measures of both predictable and unpredictable words. However, older readers did not show the benefit of preview orthographic relatedness that was observed in young adults, and showed significantly attenuated preview validity effects. Taken together, the data suggest that older readers are specifically impaired in the integration of parafoveal and foveal information but do not show deficits in the depth of parafoveal processing. The implications for understanding the effects of aging on reading are discussed.

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Section: Parafoveal Processing In Readingmentioning

confidence: 72%

Predictability effects and parafoveal processing in older readers.

Veldre¹,

Wong²,

Andrews³

2022

Psychology and Aging

Self Cite

View full text Add to dashboard Cite

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“…The major eye-movement signatures claimed to index this strategy were slower reading times owing to longer fixations and more regressions (attributed to slower lexical processing), and increased skipping, longer forward saccades, and enhanced word frequency and predictability effects (which were attributed to a compensatory increased reliance on prediction to "guess" upcoming words; Rayner et al, 2006). Although the risky reading hypothesis has motivated further research (e.g., Paterson et al, 2020) and computational modeling (McGowan & Reichle, 2018; see also Laubrock et al, 2006), questions have been raised about the strength and consistency of the evidence underpinning it (Payne & Silcox, 2019;Veldre et al, 2021Veldre et al, , 2022.…”

Section: Cognitive Aging and Predictabilitymentioning

confidence: 99%

How do task demands and aging affect lexical prediction during online reading of natural texts?

Andrews¹,

Veldre²,

Wong³

et al. 2023

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Facilitated identification of predictable words during online reading has been attributed to the generation of predictions about upcoming words. But highly predictable words are relatively infrequent in natural texts, raising questions about the utility and ubiquity of anticipatory prediction strategies. This study investigated the contribution of task demands and aging to predictability effects for short natural texts from the Provo corpus. The eye movements of 49 undergraduate students (mean age 21.2) and 46 healthy older adults (mean age 70.8) were recorded while they read these passages in two conditions: (a) reading for meaning to answer occasional comprehension questions; (b) proofreading to detect “transposed letter” lexical errors (e.g., clam instead of calm) in intermixed filler passages. The results suggested that the young adults, but not the older adults, engaged anticipatory prediction strategies to detect semantic errors in the proofreading condition, but neither age group showed any evidence of costs of prediction failures. Rather, both groups showed facilitated reading times for unexpected words that appeared in a high constraint within-sentence position. These findings suggest that predictability effects for natural texts reflect partial, probabilistic expectancies rather than anticipatory prediction of specific words.

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“…The participants were seated 55 cm from the camera while their heads were fixed using a chin rest. Only the right eye movements were tracked [35]. Natural reading performance was measured: the participants silently read 30 different sentences from the child's version of the Russian sentence corpus [36,37].…”

Section: Apparatus and Stimulimentioning

confidence: 99%

Identifying dyslexia in school pupils from eye movement and demographic data using artificial intelligence

Shalileh,

Ignatov,

Lopukhina

et al. 2023

PLoS ONE

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This paper represents our research results in the pursuit of the following objectives: (i) to introduce a novel multi-sources data set to tackle the shortcomings of the previous data sets, (ii) to propose a robust artificial intelligence-based solution to identify dyslexia in primary school pupils, (iii) to investigate our psycholinguistic knowledge by studying the importance of the features in identifying dyslexia by our best AI model. In order to achieve the first objective, we collected and annotated a new set of eye-movement-during-reading data. Furthermore, we collected demographic data, including the measure of non-verbal intelligence, to form our three data sources. Our data set is the largest eye-movement data set globally. Unlike the previously introduced binary-class data sets, it contains (A) three class labels and (B) reading speed. Concerning the second objective, we formulated the task of dyslexia prediction as regression and classification problems and scrutinized the performance of 12 classifications and eight regressions approaches. We exploited the Bayesian optimization method to fine-tune the hyperparameters of the models: and reported the average and the standard deviation of our evaluation metrics in a stratified ten-fold cross-validation. Our studies showed that multi-layer perceptron, random forest, gradient boosting, and k-nearest neighbor form the group having the most acceptable results. Moreover, we showed that although separately using each data source did not lead to accurate results, their combination led to a reliable solution. We also determined the importance of the features of our best classifier: our findings showed that the IQ, gender, and age are the top three important features; we also showed that fixation along the y-axis is more important than other fixation data. Dyslexia detection, eye fixation, eye movement, demographic, classification, regression, artificial intelligence.

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Reading proficiency predicts the extent of the right, but not left, perceptual span in older readers

Cited by 10 publications

References 24 publications

Predictability effects and parafoveal processing in older readers.

Predictability effects and parafoveal processing in older readers.

How do task demands and aging affect lexical prediction during online reading of natural texts?

Identifying dyslexia in school pupils from eye movement and demographic data using artificial intelligence

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