Reinforcement Learning in Autism Spectrum Disorder

Schuetze, Manuela; Rohr, Christiane S.; Dewey, Deborah; McCrimmon, Adam W.; Bray, Signe

doi:10.3389/fpsyg.2017.02035

Cited by 35 publications

(45 citation statements)

References 124 publications

(217 reference statements)

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“…Reduced reward learning could also have implications for behavioral interventions. If autistic adolescents do not learn from typical rewards in the same way that TD adolescents do, the type(s) of rewards used in behavioral interventions would require adapting [ 76 ]. For example, there is evidence to suggest autistic individuals assign specific reward value to their circumscribed interests such that they may be of value in intervention design [ 77 – 79 ].…”

Section: Discussionmentioning

confidence: 99%

Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group

et al. 2020

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Flexible behavior is critical for everyday decision-making and has been implicated in restricted, repetitive behaviors (RRB) in autism spectrum disorder (ASD). However, how flexible behavior changes developmentally in ASD remains largely unknown. Here, we used a developmental approach and examined flexible behavior on a probabilistic reversal learning task in 572 children, adolescents, and adults (ASD N = 321; typical development [TD] N = 251). Using computational modeling, we quantified latent variables that index mechanisms underlying perseveration and feedback sensitivity. We then assessed these variables in relation to diagnosis, developmental stage, core autism symptomatology, and associated psychiatric symptoms. Autistic individuals showed on average more perseveration and less feedback sensitivity than TD individuals, and, across cases and controls, older age groups showed more feedback sensitivity than younger age groups. Computational modeling revealed that dominant learning mechanisms underpinning flexible behavior differed across developmental stages and reduced flexible behavior in ASD was driven by less optimal learning on average within each age group. In autistic children, perseverative errors were positively related to anxiety symptoms, and in autistic adults, perseveration (indexed by both task errors and model parameter estimates) was positively related to RRB. These findings provide novel insights into reduced flexible behavior in relation to clinical symptoms in ASD.

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Section: Discussionmentioning

confidence: 99%

Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group

et al. 2020

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“…Reduced reward learning could also have implications for behavioral interventions. If autistic adolescents do not learn from typical rewards in the same way that TD adolescents do, the type(s) of rewards used in behavioral interventions would require adapting [76]. For example, there is evidence to suggest autistic individuals assign specific reward value to their circumscribed interests such that they may be of value in intervention design [77][78][79].…”

Section: Discussionmentioning

confidence: 99%

Modeling flexible behaviour in autism spectrum disorder and typical development

Crawley¹,

Zhang²,

Jones³

et al. 2019

Preprint

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Flexible behavior is critical for everyday decision-making and has been implicated in restricted, repetitive behaviors (RRB) in autism spectrum disorder (ASD). However, how flexible behavior changes developmentally in ASD remains largely unknown. Here, we used a developmental approach and examined flexible behavior on a probabilistic reversal learning task in 572 children, adolescents and adults (ASD N=321; typical development, TD; N=251). Using computational modeling, we quantified latent variables that index mechanisms underlying perseveration and feedback sensitivity. We then assessed these variables in relation to diagnosis, developmental stage, core autism symptomatology and associated psychiatric symptoms. Autistic individuals showed on average more perseveration and less feedback sensitivity than TD individuals and, across cases and controls, older age groups showed more feedback sensitivity than younger age groups. Computational modeling revealed that dominant learning mechanisms underpinning flexible behavior differed across developmental stages and reduced flexible behavior in ASD was driven by less optimal learning on average within each age group. In autistic children, perseverative errors were positively related to anxiety symptoms, and in autistic adults, perseveration (indexed by both task errors and model parameters) was positively related to RRB. These findings provide novel insights into reduced flexible behavior in relation to clinical symptoms in ASD.

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“…FC between nucleus accumbens (NAcc) and visual areas, which was linked to all three BR subdomains, has been observed during reward processing (53) and NAcc and visual areas have been jointly activated in reward-directed action and inhibition of action (54) and response to incentives (55). NAcc is known to play an important role in processing rewarding and reinforcing stimuli (e.g., food and water) (56) as well as in reward anticipation (57) and outcome prediction (58, 59); it receives projections from dopamine-releasing neurons (60) and interacts with the PFC (61). Reward and BR are arguably linked (62), especially in children (63).…”

Section: Discussionmentioning

confidence: 99%

Functional Connectivity based Brain Signatures of Behavioral Regulation in Children with ADHD, DCD and ADHD-DCD

Rohr

Bray

Dewey

2020

Preprint

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1Background: Children with neurodevelopmental disorders such as Attention Deficit Hyperactivity 2 Disorder (ADHD) often struggle with behavioral self-regulation (BR), which is associated with daily-3 life challenges. ADHD sometimes presents with Developmental Coordination Disorder (DCD), but 4 little is known about BR in DCD. BR is thought to involve limbic, prefrontal, parietal and temporal 5 brain areas. Given the risk for negative outcomes, gaining a better understanding of the brain 6 mechanisms underlying BR in children with ADHD and/or DCD is imperative. 7Methods: Resting-state fMRI data collected from 115 children (31 typically developing (TD), 35 8 ADHD, 21 DCD, 28 ADHD-DCD) aged 7-17 years were preprocessed and motion was mitigated 9 using ICA-AROMA. Emotion control, inhibition, and shifting were assessed as subdomains of BR. 10Functional connectivity (FC) maps were computed for ten limbic, prefrontal, parietal and temporal 11 regions of interest and were investigated for associations with BR subdomains across all participants 12 as well as for significant group differences. 13 Results:Multiple FC patterns were associated with BR across all participants. Some FC patterns 14 were associated with multiple BR subdomains, while others were associated with only one. 15Differences in BR were found only between children with ADHD (i.e. ADHD and ADHD-DCD) and 16 those without ADHD (i.e. TD and DCD). FC differences were also found between children with and 17 without ADHD. 18 Conclusions:Our results show dimensional associations between BR subdomain scores and whole-19 brain FC and highlight the potential of these associative patterns as brain-based signatures of BR in 20 children with and without ADHD. 21

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Reinforcement Learning in Autism Spectrum Disorder

Cited by 35 publications

References 124 publications

Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group

Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group

Modeling flexible behaviour in autism spectrum disorder and typical development

Functional Connectivity based Brain Signatures of Behavioral Regulation in Children with ADHD, DCD and ADHD-DCD

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