Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/60251
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dc.contributor.authorLockhart, Amelia Kateen
dc.contributor.authorBitsika, Vickien
dc.contributor.authorShadli, Shabahen
dc.contributor.authorSharpley, Christopheren
dc.date.accessioned2024-05-30T04:07:45Z-
dc.date.available2024-05-30T04:07:45Z-
dc.date.created2023-
dc.date.issued2024-03-08-
dc.identifier.urihttps://hdl.handle.net/1959.11/60251-
dc.descriptionPlease contact rune@une.edu.au if you require access to this thesis for the purpose of research or studyen
dc.description.abstract<p>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.</p> <p>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.</p>en
dc.languageenen
dc.publisherUniversity of New England-
dc.titleMu Rhythms in Autism Spectrum Disorder: Electroencephalography for Determining the Viability of Mu as a Biomarker for Autistic Socialisation Deficitsen
dc.typeThesis Doctoralen
local.contributor.firstnameAmelia Kateen
local.contributor.firstnameVickien
local.contributor.firstnameShabahen
local.contributor.firstnameChristopheren
local.hos.emailst-sabl@une.edu.auen
local.thesis.passedPasseden
local.thesis.degreelevelDoctoralen
local.thesis.degreenameDoctor of Philosophy - PhDen
local.contributor.grantorUniversity of New England-
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science & Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailamelia.k.lockhart@gmail.comen
local.profile.emailvbitsik2@une.edu.auen
local.profile.emailsshadli@une.edu.auen
local.profile.emailcsharpl3@une.edu.auen
local.output.categoryT2en
local.access.restrictedto2026-09-09en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeArmidale, Australia-
local.title.subtitleElectroencephalography for Determining the Viability of Mu as a Biomarker for Autistic Socialisation Deficitsen
local.contributor.lastnameLockharten
local.contributor.lastnameBitsikaen
local.contributor.lastnameShadlien
local.contributor.lastnameSharpleyen
dc.identifier.staffune-id:vbitsik2en
dc.identifier.staffune-id:sshadlien
dc.identifier.staffune-id:csharpl3en
local.profile.orcid0000-0003-2518-6684en
local.profile.orcid0000-0002-3607-3469en
local.profile.orcid0000-0001-7922-4848en
local.profile.roleauthoren
local.profile.rolesupervisoren
local.profile.rolesupervisoren
local.profile.rolesupervisoren
local.identifier.unepublicationidune:1959.11/60251en
dc.identifier.academiclevelStudenten
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.thesis.bypublicationNoen
local.title.maintitleMu Rhythms in Autism Spectrum Disorderen
local.output.categorydescriptionT2 Thesis - Doctorate by Researchen
local.access.yearsrestricted2.5en
local.school.graduationSchool of Science & Technologyen
local.thesis.borndigitalYes-
local.search.authorLockhart, Amelia Kateen
local.search.supervisorBitsika, Vickien
local.search.supervisorShadli, Shabahen
local.search.supervisorSharpley, Christopheren
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.conferred2024en
local.subject.for2020320903 Central nervous systemen
local.subject.for2020320905 Neurology and neuromuscular diseasesen
local.subject.for2020320907 Sensory systemsen
local.subject.seo2020200101 Diagnosis of human diseases and conditionsen
local.subject.seo2020200105 Treatment of human diseases and conditionsen
local.subject.seo2020200599 Specific population health (excl. Indigenous health) not elsewhere classifieden
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
Appears in Collections:School of Science and Technology
Thesis Doctoral
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