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Title: EEG connectivity in infants at risk for autism spectrum disorder
Author: Haartsen, Rianne
ISNI:       0000 0004 7961 4725
Awarding Body: Birkbeck, University of London
Current Institution: Birkbeck (University of London)
Date of Award: 2019
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Autism Spectrum Disorder (ASD) is characterized by social and communication difficulties, and restricted and repetitive behaviours, and is typically diagnosed during toddlerhood. Electroencephalographic (EEG) connectivity during infancy may predict later diagnostic outcome, and dimensional traits, although results vary with differences in methods. The aim of this thesis is to examine how infant EEG connectivity relates to familial risk, and later categorical and dimensional outcomes of ASD. A previous study found alpha band hyperconnectivity in 14-month-old infants who developed ASD compared to infants who did not develop ASD at 36 months. Chapter 3 shows that methods used in this previous study indeed provide reliable results. Chapter 4 describes the replication study using identical methods to the previous study. Although the difference between groups was not replicated, the association between alpha connectivity and restricted and repetitive behaviours during toddlerhood was replicated. Chapter 5 tested the hypothesis that social and communication difficulties relate to theta connectivity in response to social and non-social stimuli. Theta connectivity was increased during social compared to non-social stimuli. Network topologies differed between groups with high and low familial risk, but not between categorical outcome groups. Theta connectivity was not associated with dimensional traits at toddlerhood. Chapter 6 showed that graph organisation was not related to familial risk, or diagnostic or dimensional outcomes at toddlerhood. Finally, Chapter 7 combined measures from previous chapters and examined how these relate to dimensional outcomes at childhood. Graph organisation at infancy showed a stronger association with dimensional outcomes at childhood than other connectivity measures. Overall, the results in this thesis illustrate the variability in developmental trajectories in ASD, while emphasizing the complexity of the disorder and use of a dimensional approach to ASD. Chapter 8 further discusses contributions and implications for research of EEG connectivity as early predictive marker for ASD.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available