Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.787817
Title: Investigating sensory prediction in autism spectrum conditions
Author: Finnemann, Johanna J. S.
ISNI:       0000 0004 7972 9274
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2019
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Abstract:
Autism is the umbrella term for a family of neurodevelopmental disorders characterised by heterogeneous clinical presentations affecting social interaction, communication, sensory atypicalities and restricted and repetitive behaviours (DSM 5). The idea of a unifying explanation that can account for the range of cognitive, behavioural and neurological features associated with autism is attractive, but as of yet no such cognitive or physiological underpinnings have been identified. However, the last years have seen a growing interest in using approaches within the nascent field of the predictive processing framework to explore the potential causal role of aberrant prediction for the autistic phenotype. While hypothesised differences in predictive abilities have demonstrated some explanatory power for symptoms of psychotic spectrum disorders, empirical investigations into autism are still sparse. In this thesis I follow up on the theoretical work about difficulties with expectation generation in autism with three empirical studies on prediction in perception and sensory processing (Chapters 2-4). My results did not support the idea of autism as a generalised disorder of prediction; however better phenotyping in future work might help to tease apart some of the variability observed in the autism group. Furthermore I also examined the psychometric properties of two widely-used self-report questionnaires assessing autistic traits and schizotypy (Chapter 5). If latent traits are not measured equivalently across clinical and non-clinical populations, this could have implications for studies using high self-reported traits in healthy participants as proxies for the clinical condition as well as for correlational studies.
Supervisor: Fletcher, Paul Sponsor: Christ's College ; Cambridge
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.787817  DOI:
Keywords: autism ; ASD ; Asperger's ; sensory ; motor ; prediction ; predictive coding ; predictive processing ; Bayesian Brain
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