Gaze avoidance is a hallmark behavioral feature of fragile X syndrome (FXS), but little is known about whether abnormalities in the visual processing of faces, including disrupted autonomic reactivity, may underlie this behavior. Eye tracking was used to record fixations and pupil diameter while adolescents and young adults with FXS and sex- and age-matched typically developing controls passively viewed photographs of faces containing either a calm, happy, or fearful expression, preceded by a scrambled face matched on luminance. Results provide quantitative evidence for significant differences in gaze patterns and increased pupillary reactivity when individuals with FXS passively view static faces. Such abnormalities have significant implications in terms of understanding causes of gaze avoidance observed in individuals with FXS.

Recent insight into the underlying molecular and cellular mechanisms of fragile X syndrome (FXS) has led to the proposal and development of new pharmaceutical treatment strategies, and the initiation of clinical trials aimed at correcting core symptoms of the developmental disorder. Consequently, there is an urgent and critical need for outcome measures that are valid for quantifying specific symptoms of FXS and that are consistent across time. We used eye tracking to evaluate test-retest reliability of gaze and pupillometry measures in individuals with FXS and we demonstrate that these measures are viable options for assessing treatment-specific outcomes related to a core behavioral feature of the disorder.

Introduction

Lumosity's Memory Match (LMM) is an online game requiring visual working memory. Change in LMM scores may be associated with individual differences in age-related changes in working memory.

Methods

Effects of age and time on LMM learning and forgetting rates were estimated using data from 1890 game sessions for users aged 40 to 79 years.

Results

There were significant effects of age on baseline LMM scores (β = -.31, standard error or SE = .02, P < .0001) and lower learning rates (β = -.0066, SE = .0008, P < .0001). A sample size of 202 subjects/arm was estimated for a 1-year study for subjects in the lower quartile of game performance.

Discussion

Online memory games have the potential to identify age-related decline in cognition and to identify subjects at risk for cognitive decline with smaller sample sizes and lower cost than traditional recruitment methods.