Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/60251
Title: Mu Rhythms in Autism Spectrum Disorder: Electroencephalography for Determining the Viability of Mu as a Biomarker for Autistic Socialisation Deficits
Contributor(s): Lockhart, Amelia Kate (author); Bitsika, Vicki  (supervisor)orcid ; Shadli, Shabah  (supervisor)orcid ; Sharpley, Christopher  (supervisor)orcid 
Conferred Date: 2024-03-08
Copyright Date: 2023
Thesis Restriction Date until: 2026-09-09
Handle Link: https://hdl.handle.net/1959.11/60251
Abstract: 

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by deficits in social communication and social interaction, and the presence of repetitive and restricted behaviours (American Psychiatric Association, 2022). Neurobiological approaches to studying ASD are a promising methodology for identifying autistic-related neuromarkers. Mu rhythms (Mu), detectable via an electroencephalogram (EEG), can potentially shed light on the socialisation deficits characterising ASD. However, Mu-related ASD studies have yielded inconsistent results and shared common theoretical and methodological limitations. These limitations include the use of Mu as a proxy for the mirror neuron system (hence, socialisation) based on limited evidence, inadequate sample sizes, socially irrelevant stimuli (i.e., not accounting for social interaction intensity [SII], familiarity or overall social competence), and limited measurement of other factors shown to influence Mu power (MP) variation (i.e., cognitive capacity, age and anxiety). The present study aimed to determine the validity of Mu as a neuromarker for autistic-related socialisation deficits. A sample of 42 autistic boys (aged 6–18 years) was recruited, and their social competence and level of anxiety were evaluated. The autistic boys completed an EEG experiment exposing them to socially relevant stimuli that increased in SII (i.e., starting with a smiling face on screen and progressing to a controlled real-time social encounter), alternating between familiar and novel persons. Their MP was analysed to determine if desynchronisation (i.e., the proposed neuromarker for social competence) occurred in these autistic boys, and to explore whether general variations in their MP could be utilised in classifying them into high and low MP groups.

The autistic boys’ group means of social competence, anxiety, age and cognitive capacities were compared according to their subtypes of MP classification. Results showed that these autistic boys failed to desynchronise Mu even as the social stimuli increased in SII (i.e., very low SII, low SII, moderate SII, and high SII). However, their Mu variation was influenced only by their social awareness, not their pre-rated social competence. MP variation, instead of socialisation, was more influenced by anxiety subtype (depending on the condition of Mu measurement) and age (i.e., more Mu desynchronisation occurred in older autistic boys). Whilst these findings suggest that Mu is dysfunctional in autistic boys, it should not be used as a proxy for socialisation in the mirror neuron system because anxiety and age influenced Mu variation more than social competence.

Publication Type: Thesis Doctoral
Fields of Research (FoR) 2020: 320903 Central nervous system
320905 Neurology and neuromuscular diseases
320907 Sensory systems
Socio-Economic Objective (SEO) 2020: 200101 Diagnosis of human diseases and conditions
200105 Treatment of human diseases and conditions
200599 Specific population health (excl. Indigenous health) not elsewhere classified
HERDC Category Description: T2 Thesis - Doctorate by Research
Description: Please contact rune@une.edu.au if you require access to this thesis for the purpose of research or study
Appears in Collections:School of Science and Technology
Thesis Doctoral

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