Rate My Professor Amelia Lockhart

Amelia Lockhart is pursuing a Doctor of Philosophy in the Brain & Behaviour Research Group, School of Science and Technology, Faculty of Science, Agriculture, Business and Law at the University of New England, Armidale, Australia. Her thesis, titled "Mu Variation and Socialisation in Autism Spectrum Disorder," is supervised by Professors Vicki Bitsika, Christopher Sharpley, and Phillip Fourie. The research focuses on mu rhythms—phasic electrophysiological signals identified at 8-13 Hz by the C3, Cz, C4 electrodes located above the sensorimotor region of the brain. These rhythms desynchronise in response to the observation, imagination, and execution of movement and share similarities with the mirror neuron system, which is considered dysfunctional in individuals with autism spectrum disorder, leading to poorer socialisation. Lockhart's work investigates the efficacy of mu dysfunction as a marker in ASD by exposing participants to actual social situations, potentially enabling more targeted neurofeedback training to enhance social outcomes.

As Unit Coordinator for NEUR334/NEUR534 Neurobiology of Developmental, Cognitive and Affective Disorders in 2023 and 2024 trimesters, Lockhart contributes to teaching in neuroscience at undergraduate and postgraduate levels. She is the corresponding author of the review paper "Mu Desynchronisation in Autistic Individuals: What We Know and Where We Need to Go," published online in February 2023 in the Review Journal of Autism and Developmental Disorders (issue September 2024), co-authored with Christopher F. Sharpley and Vicki Bitsika, all from the BBRG at UNE. The paper synthesizes 14 studies from 2005–2022 on mu desynchronisation (MD) in ASD, highlighting inconsistent results—eight studies found differences primarily in observation conditions, while four did not. Variability stems from small sample sizes, lack of demographic controls (e.g., age, sex, handedness), use of screen-based rather than live social stimuli, and theoretical assumptions linking mu directly to mirror neurons. It recommends future studies with larger, diverse samples, real-world social interactions, consideration of genetic factors, and exploration of neurofeedback for social deficit remediation.