scholarly journals Atypical predictive processing during visual statistical learning in children with developmental dyslexia: an event-related potential study

2018 ◽  
Vol 68 (2) ◽  
pp. 165-179 ◽  
Author(s):  
Sonia Singh ◽  
Anne M. Walk ◽  
Christopher M. Conway
PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243100
Author(s):  
Katie L. Richards ◽  
Povilas Karvelis ◽  
Stephen M. Lawrie ◽  
Peggy Seriès

Background 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. Methods 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. Results 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. Conclusion 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.


2013 ◽  
Author(s):  
Jerome Daltrozzo ◽  
Joanne A. Deocampo ◽  
Julie Trapani ◽  
Sam Sims ◽  
Christopher M. Conway

2020 ◽  
Author(s):  
Katie Richards ◽  
Povilas Karvelis ◽  
Stephen Lawrie ◽  
Peggy Series

Deficits in statistical learning and predictive processing could in principle explain inattention and distractibility in attention deficit hyperactivity disorder (ADHD). To test this, we evaluated whether adults diagnosed with ADHD (n = 17) differed from controls (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 coherently moving dots. Unbeknown to the participants, two directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in autistic spectrum disorder and schizophrenia. Both groups acquired the prior expectations for the most frequent directions and, except for some subtle differences over time, there were no group difference in how much the priors influenced performance. This suggests that ADHD symptoms do not stem from difficulties in developing and/or using perceptual priors.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Heida Maria Sigurdardottir ◽  
Hilda Bjork Danielsdottir ◽  
Margret Gudmundsdottir ◽  
Kristjan Helgi Hjartarson ◽  
Elin Astros Thorarinsdottir ◽  
...  

2011 ◽  
Author(s):  
M. Sobanska ◽  
I. Szumska ◽  
D. Warakomski ◽  
P. Jaskowski

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