Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.

<h4>Background</h4>Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated...

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Main Authors: Katie L Richards, Povilas Karvelis, Stephen M Lawrie, Peggy Seriès
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0243100
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spelling doaj-6e3d1149e5244c5598f88ad70884e0622021-03-04T12:50:29ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011512e024310010.1371/journal.pone.0243100Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.Katie L RichardsPovilas KarvelisStephen M LawriePeggy Seriès<h4>Background</h4>Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated with flatter likelihoods (increased sensory processing noise), and/or difficulties in generating or using predictions. To our knowledge, such hypotheses have never been directly tested.<h4>Methods</h4>We here test these hypotheses by evaluating whether adults diagnosed with ADHD (n = 17) differed from a control group (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of a cloud of coherently moving dots. Unbeknown to the participants, two of the directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in other neurodevelopmental disorders, such as autistic spectrum disorder and schizophrenia.<h4>Results</h4>We found that both groups acquired the prior expectation for the most frequent directions and that these expectations substantially influenced task performance. Overall, there were no group differences in how much the priors influenced performance. However, subtle group differences were found in the influence of the prior over time.<h4>Conclusion</h4>Our findings suggest that the symptoms of inattention and hyperactivity in ADHD do not stem from broad difficulties in developing and/or using low-level perceptual priors.https://doi.org/10.1371/journal.pone.0243100
collection DOAJ
language English
format Article
sources DOAJ
author Katie L Richards
Povilas Karvelis
Stephen M Lawrie
Peggy Seriès
spellingShingle Katie L Richards
Povilas Karvelis
Stephen M Lawrie
Peggy Seriès
Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
PLoS ONE
author_facet Katie L Richards
Povilas Karvelis
Stephen M Lawrie
Peggy Seriès
author_sort Katie L Richards
title Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
title_short Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
title_full Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
title_fullStr Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
title_full_unstemmed Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
title_sort visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description <h4>Background</h4>Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated with flatter likelihoods (increased sensory processing noise), and/or difficulties in generating or using predictions. To our knowledge, such hypotheses have never been directly tested.<h4>Methods</h4>We here test these hypotheses by evaluating whether adults diagnosed with ADHD (n = 17) differed from a control group (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of a cloud of coherently moving dots. Unbeknown to the participants, two of the directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in other neurodevelopmental disorders, such as autistic spectrum disorder and schizophrenia.<h4>Results</h4>We found that both groups acquired the prior expectation for the most frequent directions and that these expectations substantially influenced task performance. Overall, there were no group differences in how much the priors influenced performance. However, subtle group differences were found in the influence of the prior over time.<h4>Conclusion</h4>Our findings suggest that the symptoms of inattention and hyperactivity in ADHD do not stem from broad difficulties in developing and/or using low-level perceptual priors.
url https://doi.org/10.1371/journal.pone.0243100
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