In our day-to-day interactions with the world we have to learn from salient feedback, adapt when it changes and also learn when to ignore ‘noise’ or erroneous feedback. In autism, change can often be experienced as particularly difficult and can cause distress.Co-lead author Daisy Crawley, Institute of Psychiatry, Psychology & Neuroscience, King's College London
17 November 2020
Reduced flexible behaviour in autistic individuals is driven by less optimal learning
Researchers from King’s College London have used computational modelling to reveal different dominant learning mechanisms across developmental stages, and less optimal learning in autistic individuals resulting in reduced flexible behaviour.
Flexible behaviour is critical for everyday decision-making and has been implicated in a range of neurodevelopmental and neuropsychiatric conditions, including autism. In particular, reduced flexible behaviour is suggested to underpin core features of restricted, repetitive behaviours in autism, such as insistence on sameness.
However, the current evidence base has been mixed and it hasn’t been clear what the role of development is in learning flexible behaviour, and how it relates to differences or difficulties experienced by autistic people.
New research, co-led by researchers at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s and the University of Vienna, was part of the EU-AIMS consortium (European Autism Interventions - A Multicentre Study for Developing New Medications), which is a wide-ranging research programme aiming to understand more about autism and reveal insights to improve the lives of autistic people. The study has been published in the journal PLOS Biology.
The researchers used a probabilistic reversal learning task – where participants learn using feedback and then must adjust their responses when the rules of the task change – to explore flexible learning in 572 children, adolescents, and adults. Of the participants, 321 were autistic and 251 were ‘neurotypical’.
During the tasks, autistic individuals showed on average more perseveration and less feedback sensitivity than neurotypical individuals, resulting in poorer task performance. Computational modelling revealed that dominant learning mechanisms underpinning flexible behaviour differed across developmental stages, and reduced flexible behaviour in autism was driven by less optimal learning. In autistic children, perseverative errors were positively related to anxiety symptoms, and in autistic adults, perseveration was positively related to restricted, repetitive behaviours. According to the authors, this study is the first to illustrate a potential learning mechanism by which behavioural rigidity manifests in autistic adults.
She continued, ‘Understanding the dominant learning strategies of different age groups and in individuals both with and without autism may improve our understanding of flexible behaviour and allow us to identify ways to support difficulties with change.’
She added ‘Our findings emphasise the need for a developmental framework when investigating mechanistic accounts of flexible behaviour. Furthermore, the results suggest that altered learning rates in autism have different effects on behaviour depending on the learning environment. The computational models therefore demonstrate differences between autistic and neurotypical individuals rather than solely difficulties in autism.
‘In this context, individuals with autism are less effective in learning flexible behaviour when learning to ignore misleading feedback is as important as tracking salient change. These difficulties may underpin the marked difficulties with minor deviations in routine that are often reported by autistic individuals or their caregivers. However, in different environments, faster learning may manifest in strengths.
‘We believe this is an important message for future research and intervention development.’ The study also demonstrates the value of computational psychiatry – a newly emerging field with potential to improve our understanding of ‘online’ cognitive processes such as probabilistic learning. This approach could help answer questions that are otherwise hard to answer using traditional research methods.
EU-AIMS (and its follow-up project, AIMS-2-Trials) was an Innovative Medicines Initiative-funded project and the first Europe-wide collaboration between organisations representing autistic people and their families, academia and industry. The consortium aimed to identify treatment targets for autism and reveal why some therapies are effective in subgroups of autistic people.
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