Features of eye movements during rapid automatized naming in Chinese children aged 7–11 years

Abstract

Rapid Automatized Naming (RAN) tests have been well-documented to predict reading abilities as well as a variety of neurobiological disorders (e.g., developmental dyslexia). Traditional measures of RAN tests only take into account the naming time and accuracy and cannot reflect temporal-spatial features during RAN tests. Although the eye tracking approach appears to be a promising tool for characterizing the essential temporal-spatial characteristics of RAN tests, no research has been conducted to investigate whether and how gender, age, and task-type alter those characteristics. Additionally, no study has examined eye movements during a Chinese adaptation of RAN in order to expand the applicability of RAN to developmental dyslexia in Chinese. To address the concerns stated above, this article recruited 408 children (206 males, aged 7–11 years) and adopted eight measures to quantify features of eye movements during a Chinese adaptation of RAN. Findings showed that: (1) eight eye-movement measures had the main effects of task-type and age, but only five of them had the main effect of gender (in particular, females outperformed males); (2) RAN abilities observed by eight eye-movement measures initially developed quickly before the age of 9, and then entered a relatively sluggish development phase; (3) non-alphanumeric RAN tasks generally required higher mental load (implying more fixation counts, saccade counts, and regression counts, smaller average saccade amplitude, fixation duration fluctuation and saccade amplitude fluctuation, and longer average fixation duration and total time of naming) than alphanumeric ones; (4) there were significant correlations between total time of naming (a widely-used behavioral parameter) and other eye-movement measures; and (5) there were significant correlation between eight eye-movement measures and three attention-related skills observed from a number cancellation task. The current study might offer some perspectives on the understanding of normative data of eye movements during RAN in Chinese school-aged children, as well as the applications (e.g., developmental dyslexia) associated with RAN.

Lévy Flight Model of Gaze Trajectories to Assist in ADHD Diagnoses

“…There, we obtained an accuracy of 93%, even when using shorter trajectories (less data). Other studies have analyzed reading tasks to investigate dyslexia [28,29], with similar standard metrics; the authors aimed to characterize the eye movements of children with dyslexia.…”

“…Besides the theoretical question of the best mathematical description of gaze trajectories, eye-tracking data has been gaining popularity due to its wide range of applications in health sciences. It can be used to determine an individual's age, gender, ethnicity [23], personality traits such as extroversion, curiosity, neuroticism, openness, agreeableness [24], Intelligence Quotient (IQ) [25], as well as helping detect conditions such as Alzheimer's [26], autism [27], or dyslexia [28,29].…”