Developing neuro-technologies for decoding and enhancing memory

The brain is a complex network that underlies our thoughts and actions. Uncovering how it operates is fundamental for improving performance, treating disorders and developing the next generation of artificial intelligence. Associate Professor Kai-Hsiang Chuang’s lab focuses on developing imaging, modelling and interventional techniques to define and modulate brain network essential for cognition. Their recent works published on Nature Communications and PNAS have demonstrated the potential of resting-state functional magnetic resonance imaging (fMRI) in locating network hubs that are causal for memory formation. Further development of these techniques in rodent models and humans will facilitate the diagnosis and treatment of cognitive impairment and dementia.

Neuromodulation techniques, such as TMS, have shown potential for changing neural activity and behavioural performance. However, current neuromodulation methods only target a specific brain area but not a network. They also stimulate the brain with a fixed protocol that is not optimal for each individual.

This project will pinpoint specific cell type (excitation vs inhibition), neuronal activity patterns, and connections that mediate memory formation using simultaneous calcium photometry, optogenetic neuromodulation and fMRI in rodents. New techniques will be developed to selectively modulation a specific network that is influential for memory formation. A computational model will be used to simulate and predict the effects of network modulation. The knowledge generated and technology developed will enable modulation of memory formation for treating dementia or other cognitive impairment.

This is an Earmarked scholarship project that aligns with a recently awarded Australian Government grant.

The scholarship includes:

• living stipend of $35,000 per annum tax free (2024 rate), indexed annually
• your tuition fees covered
• single overseas student health cover (OSHC).

Learn more about the Earmarked scholarship.

Your application will be assessed on a competitive basis.

We take into account your:

• previous academic record
• publication record
• honours and awards
• employment history

A working knowledge of functional MRI, artificial neural network, and programming language (eg, Matlab, C) would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of biomedical engineering, computer science, biological science, medicine and the potential for scholastic success.

A background or knowledge of functional MRI, and neurobiology is highly desirable.

This project requires candidates to commence no later than Research Quarter 1, 2025. To allow time for your application to be processed, we recommend applying no later than 30 September, 2024 30 June, 2024.

You can start in an earlier research quarter. See application dates.

Before you apply

1. Check your eligibility for the Doctor of Philosophy (PhD).
2. Prepare your documentation.
3. Contact Associate Professor Kai-Hsiang Chuang (k.chuang@uq.edu.au) to discuss your interest and suitability.

When you apply

You apply for this scholarship when you submit an application for a PhD. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

• My higher degree is not collaborative
• I am applying for, or have been awarded a scholarship or sponsorship
• UQ Earmarked Scholarship type.

Apply now