A5060075383- Tactile and Sensory Interactions
- Neural dynamics and brain function
- COVID-19 epidemiological studies
- SARS-CoV-2 and COVID-19 Research
- EEG and Brain-Computer Interfaces
- Time Series Analysis and Forecasting
- Functional Brain Connectivity Studies
- Neuroscience and Neuropharmacology Research
- Orbital Angular Momentum in Optics
- Neuroscience and Neural Engineering
- Vaccine Coverage and Hesitancy
QIMR Berghofer Medical Research Institute
2022-2024
The University of Queensland
2020
Bionics Institute
2017-2020
Long-term control of SARS-CoV-2 outbreaks depends on the widespread coverage effective vaccines. In Australia, two-dose vaccination above 90% adult population was achieved. However, between August 2020 and 2021, hesitancy fluctuated dramatically. This raised question whether settings with low naturally derived immunity, such as Queensland where less than <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mn>0.005</mml:mn> <mml:mi mathvariant="normal">%</mml:mi> </mml:math> is...
Abstract Melancholia has been proposed as a qualitatively distinct depressive subtype associated with characteristic symptom profile (psychomotor retardation, profound anhedonia) and better response to biological therapies. Existing work suggested that individuals melancholia are blunted in their display of positive emotions differ neural emotionally evocative stimuli. Here, we unify these brain behavioural findings amongst carefully phenotyped group seventy depressed participants, drawn...
Objective. Retinal prosthesis recipients require rehabilitative training to learn the non-intuitive nature of prosthetic 'phosphene vision'. This study investigated whether addition auditory cues, using The vOICe sensory substitution device (SSD), could improve functional performance with simulated phosphene vision. Approach. Forty normally sighted subjects completed two visual tasks under three conditions. condition converted image phosphenes displayed on a virtual reality headset. SSD...
Identifying a particle in an optical trap can be difficult task, especially for biological samples with low contrast. The relationship of radius and refractive index to the stiffness traps is non-intuitive, motivating machine learning approach. We demonstrate methods real-time estimates particles trapped by tweezers. This achieved analysing particle’s position force artificial neural networks. Our network binary classification experimental sampling only milliseconds values. demonstrates that...