Differences in Attentional Disengagement in Preschoolers at Risk for ASD and with FXS
Early visual attention is critical to shaping learning opportunities. Although attentional problems are not core features of neurodevelopmental disorders such as fragile X syndrome (FXS) and autism spectrum disorder (ASD), much work has highlighted atypical attention patterns in young children in these populations (Tonnsen, Grefer, Hatton, & Roberts, 2014). Many studies utilize eye-tracking to measure low-level differences in attention at young ages in children with ASD and FXS. One example is attentional disengagement, indexed by the gap-overlap paradigm. Longer latencies to attentional disengagement may suggest attention difficulties, and increased latency of disengagement has been shown to discriminate infant siblings who go on to develop ASD from those who do not (Elsabbagh et al., 2013). Little work has examined performance on the gap-overlap task in very young children with FXS although some studies suggest attentional disengagement is impaired in older individuals (Shelton et al., 2014). Given the high rate of comorbidity of ASD with FXS and the mounting interest in neurodevelopmental pathways to common and divergent phenotypes in childhood disorders, the examination of early visual attention in these populations offers an important avenue for current research.
To evaluate differences in attentional disengagement between typically developing (TD) preschoolers and those at risk for developing ASD due to 1) FXS or 2) heritable factors due to an older sibling with ASD.
Data were taken from a longitudinal study of neurodevelopment in children with disabilities. Assignment to risk groups was made at recruitment. The sample included 21 ASIB preschoolers (nmales=15; Mage=5.09 years), 19 with FXS (nmales=14; Mage=5.11 years), and 21 TD (nmales=15; Mage=4.46 years). Groups did not differ by age (p=.274). Participants viewed the gap-overlap eye-tracking task using the SR Eyelink system, and saccadic reaction times (RT) for gap, overlap, and baseline conditions were recorded. Disengagement was calculated as the difference in RT between the overlap and baseline conditions. Given the small within-group sample and heterogeneity characteristic of at-risk populations, nonparametric methods were utilized to test differences in median disengagement time.
Median disengagement times for each group were: qASIB=88.8 ms, qFXS= 119.5 ms, and qTD=74.3 ms. Results of the Independent-Samples Kruskal-Wallis test suggest that the groups differ (H(2) = 6.0, p=.050) with pairwise comparisons showing a difference between TD-ASIB (p=.049) and TD-FXS (p=.025), but not for ASIB-FXS (p=.748).
Consistent with previous findings, the present study found longer disengagement latencies in the ASIB and FXS groups relative to TD but no differences between ASIB and FXS preschoolers. Results suggest that atypical visual attention patterns observed in both of these risk groups are similar and present in early childhood. These findings provide important information regarding ASD risk and the convergent developmental pathways that lead to an ASD diagnosis. Impaired attentional control could be related to ASD features in both groups, particularly as it relates to executive functioning deficits, anxiety, or atypical social learning. Continuing longitudinal research will examine earlier attentional vulnerabilities among these etiological risk groups earlier in life and their relation to ASD diagnostic outcomes as those data become available.