2015
DOI: 10.1038/nn.4129
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Perceptual learning in autism: over-specificity and possible remedies

Abstract: Inflexible behavior is a core characteristic of autism spectrum disorder (ASD), but its underlying cause is unknown. Using a perceptual learning protocol, we observed initially efficient learning in ASD that was followed by anomalously poor learning when the location of the target was changed (over-specificity). Reducing stimulus repetition eliminated over-specificity. Our results indicate that inflexible behavior may be evident ubiquitously in ASD, even in sensory learning, but can be circumvented by specific… Show more

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Cited by 61 publications
(72 citation statements)
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“…Typical observers improve their performance (show reduced thresholds) with training across 3–4 days, but need to relearn the task when the target is moved to a different location in the visual field, showing specificity. We (Harris et al, 2015) reported similar results with observers with ASD, but unlike the typical observers who showed faster learning at the second location (Sagi, 2011), ASD observers showed difficulty in relearning the task at the second location, suggesting that the training with the target at the first location might have interfered with the training at the new, second location. We termed this anomalous poor learning “over-specificity” (OS) to reflect the narrowness of the learning and the failure to generalize, and quantified OS as the average threshold difference between the second and the first learning curves (for generalization OS < 0; specificity, OS = 0; over-specificity, OS > 0).…”
supporting
confidence: 54%
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“…Typical observers improve their performance (show reduced thresholds) with training across 3–4 days, but need to relearn the task when the target is moved to a different location in the visual field, showing specificity. We (Harris et al, 2015) reported similar results with observers with ASD, but unlike the typical observers who showed faster learning at the second location (Sagi, 2011), ASD observers showed difficulty in relearning the task at the second location, suggesting that the training with the target at the first location might have interfered with the training at the new, second location. We termed this anomalous poor learning “over-specificity” (OS) to reflect the narrowness of the learning and the failure to generalize, and quantified OS as the average threshold difference between the second and the first learning curves (for generalization OS < 0; specificity, OS = 0; over-specificity, OS > 0).…”
supporting
confidence: 54%
“…Mercado and coauthors (Mercado et al, 2016) have claimed that our results showing OS of learning in individuals with ASD, when using the standard training method (Harris et al, 2015), is explained by the higher initial thresholds of the ASD group relative to the other groups (standard typically developing controls (labeled TD); dummy ASD and dummy TD; Figure 2 in Harris et al (2015). To evaluate the validity of this claim, here, we analyzed the dependence of OS on the initial threshold (measured on day 1), using measurements derived from each participant individually.…”
mentioning
confidence: 76%
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“…Finally, it was considered that a different learning style, namely one resembling overfitting in machine learning, and differences in adaptation can also be explained by this hypothesis [cf. [64]].…”
Section: Bayesian Approachesmentioning
confidence: 99%