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Domenico Tullo, Jocelyn Faubert, Armando Bertone; Learning and visual attention across neurodevel-opmental conditions: Using Multiple Object-Tracking as a descriptor of visual attention. Journal of Vision 2019;19(10):157a. doi: https://doi.org/10.1167/19.10.157a.
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While most studies in Multiple Object-Tracking (MOT) have focused on understanding the mechanisms of visual tracking, recent work has suggested that MOT can be used to characterize individual differences in attention resource capacity (Tullo, et al., 2018). In the current study, we investigated whether repeated practice on an adaptive MOT task could explain the interplay between attention resource capacity and learning in relation to individuals diagnosed with neurodevelopmental conditions. Specifically, we investigated whether MOT performance would differ across neurodevelopmental conditions that are either defined by deficits in attention (e.g., ADHD), or exhibit clinically significant difficulties in attention among other deficiencies (e.g., Autism). We asked whether intelligence, our proxy for cognitive capability, and/or diagnostic profile (i.e., autism, ADHD, Intellectual Disability [ID], and Learning Disability [LD]) predicted learning on daily MOT performance across 15 sessions. Children and adolescents (N=106; Mage=13.51) with a diagnosis of either autism (n=32), ADHD (n=35), or ID/LD (n=39) visually tracked 3 of 8 spheres for 8 seconds. Task difficulty adapted to the participant’s capability on a trial-by-trial basis. Performance was defined as the average speed in cm/s, where participants correctly tracked all target items. Results indicated that MOT performance mapped onto a logarithmic function, which resembled a typical learning curve at R2=0.87. Performance improved by 105% from the first to last day of testing. Moreover, day-one performance was predicted by intelligence: R2=0.28, and the rate of change in performance (i.e., learning) differed across diagnostic groups. Children and adolescents with autism (MsD1-1=1.11) demonstrated a greater standardized change than those with ADHD (MsD1-15=0.54) or ID/LD (MsD1-15=0.52). These differences highlight variability in learning capability and attention resource capacity, which vary by diagnosis and higher-level cognitive ability, such as fluid reasoning intelligence. Overall, these findings emphasize the promise and utility of MOT to define both attentional and learning capabilities across individuals.
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