Background: Understanding how individuals with autism spectrum disorder (ASD) learn is important for developing and implementing effective educational and behavioral interventions. Evidence suggests that individuals with ASD are relatively stronger in certain areas of perception (Simmons et al., 2009; Dakin and Frith, 2005); it therefore cannot be assumed that individuals with ASD learn using the same rules and strategies as neurotypicals (NT). Of particular interest, perceptual learning (PL) is a class of learning that is based upon changes induced by the repeated exposure and response to specific types of perceptual information. Such learning often includes feedback, indicating whether or not a response was correct during a trial within a PL task. The objectives of this study were to perform a pilot investigation of; (I) perceptual learning in adults with and without ASD using a low-level orientation discrimination task; and (II) the influence of feedback on accuracy in this task.
Methods: Eleven adults with ASD and fifteen NT adults, matched on Wechsler full-scale IQ and age (18–31 years), performed a low-level PL task. They were asked to indicate whether a grating was tilted to the left (i.e., counter-clockwise) or to the right (i.e., clockwise) relative to an oblique 45-degree reference orientation. Thresholds, defined by the minimal deviation in degrees needed to discriminate tilt orientation, were measured for each participant every 15 minutes, with each block consisting of 420 trials. To assess baseline performance, all participants completed a first block with no feedback. Participants were then randomly assigned to either feedback (NASD =6, NTD =8) or no feedback groups (NASD =5, NTD =7) and completed six subsequent testing blocks.
Results: PL was defined as the percent change in orientation discrimination threshold in each of the six testing blocks relative to baseline performance. No significant increase was found in performance as a function of testing block for any group; PL was therefore not evidenced under the conditions tested. ASD performance remained equal to that of baseline across testing blocks, whether or not trial-by-trial feedback was present. In contrast, NT performance was significantly increased when feedback was present.
Conclusions: NT individuals significantly benefited from feedback, while individuals with ASD did not. These results provide preliminary evidence for a divergent learning style in ASD and NT individuals. These pilot findings raise important questions regarding the impact of feedback during interventions, and at a more basic level, the atypical underlying perceptual and cognitive processes in individuals with ASD.
Background: Perceptual profiles, or the performance on visual-perceptual tasks that reflect early visual information processing, have been used to suggest condition-specific visuo-perceptual abilities across neurodevelopmental conditions (NDCs). The complexity-specific hypothesis (Bertone et al., 2010) was based on perceptual profiles defined by a selective decrease in sensitivity to more complex, texture-defined information in adults with autism and fragile-x syndrome, suggesting the atypical development of neural networks underlying early perception in NDCs. The aim of this study was to evaluate whether the complexity-specific hypothesis is applicable to children and adolescents with different NDCs by defining and comparing their perceptual profiles.
Methods: A single interval, two alternative forced-choice identification paradigm was used to measure the perceptual profiles of 64 participants with a NDC (MIQ =78) and 43 typically developing (TD) participants (MIQ =103), aged 5 to 17 years. Participants with a NDC were diagnosed with either: autism spectrum disorder (ASD, n=32), attention deficit/hyperactivity disorder (ADHD, n=9), or intellectual disability (ID, n=12). Perceptual profiles were defined by measuring participants’ sensitivity to static (orientation identification task) and dynamic (direction identification task) gratings (1 cpd) defined by either luminance (simple) or texture (complex) information. The Weschler Abbreviated Scale of Intelligence 2 (WASI-2) was used as a measure of cognitive ability.
Results: When performance was averaged across NDC and TD participants, no between-group difference in sensitivity was found for any of the conditions assessed. However, when assessed as a function of diagnosis, we found that the ID group was less sensitive to both the luminance (P=0.04) and texture-defined (P=0.01) dynamic information when compared to the TD group. Notably, although the perceptual profile of the ASD group was similar of that of the TD group, a significant positive relationship between mental age and sensitivity to both texture-defined static (r=?0.5) and dynamic (r=?0.4) information was found.
Conclusions: The ?ndings demonstrate that different conditions-specific perceptual profiles exist across children and adolescents with different types of NDCs, exemplified by differences found in this study for the ID group. In addition, the positive relationship between perceptual performance and mental age within the ASD group suggests that these perceptual abilities may still be undergoing maturation during the age-range assessed, and provides support for the complexity-specific hypothesis specific to the ASD profile during development. These results exemplify the importance of defining perceptual profiles at different periods of development across NDCs, since the tenets of most perceptually-relevant cognitive theories are based primarily on adult data.
