Ascending Control Of Behavioural State And Cognition - Role Of Nucleus Incertus And Relaxin-3 Transmission
Funder
National Health and Medical Research Council
Funding Amount
$540,356.00
Summary
Mental illness and dementia are significant social and economic burdens worldwide and knowledge of their underlying causes and more effective therapies are required. Our research aims to use pre-clinical models to characterize a little studied neuronal network implicated in control of brain theta rhythm activity, which could lead to improved treatment of neuropsychiatric diseases such as anxiety and depression, and degenerative cognitive decline.
Thalamocortical Neural Circuits In Higher Order Cognitive And Sensory Processing
Funder
National Health and Medical Research Council
Funding Amount
$370,860.00
Summary
Schizophrenia, depression and dementia are devastating disorders with problems in thinking and sensory perception, but the neural circuits causing these symptoms are not known. I will use new optical and genetic tools in mice to identify the cortical and subcortical circuits required for complex touchscreen tasks, the same tasks to assess patients. Identification of neural circuits that underlie clinical symptoms will increase our understanding of these disorders and improve treatments.
Interactive Attention Training Technology To Enhance Cognitive Skills In Early Life
Funder
National Health and Medical Research Council
Funding Amount
$759,680.00
Summary
Over 30,000 Australian children enter school with attention difficulties each year. We have established a suite of tasks to train attention based on over 20 years of research into neurodevelopmental disorders and attention. These are delivered on tablets in the form of a game known as TALI Train. We now aim to show TALI can improve attention in children with acquired brain injuries and typically developing children for commercialisation to a broad market.
Attention deficit hyperactivity disorde(ADHD) is the most prevalent mental disorder of childhood affecting around 7.5% of Australian school age children. The disorder is strongly genetic and causes significant impairments in academic functioning, family and peer relations with sufferers at increased risk for drug abuse. Identification and characterisation of rare mutations will enhance our knowledge of the neurobiology and advance the search for next generation drug treatments for the disorder.
Discovery Early Career Researcher Award - Grant ID: DE240101089
Funder
Australian Research Council
Funding Amount
$436,847.00
Summary
Trustworthy Hypothesis Transfer Learning. It is urgent to develop a new hypothesis transfer learning scheme that can overcome potential risks when finetuning unreliable large-scale pre-trained models. This project aims to develop an advanced and reliable scheme of hypothesis transfer learning, called Trustworthy Hypothesis Transfer Learning (TrustHTL). A new theoretically guaranteed heterogeneous hypothesis transfer learning framework will be developed to handle heterogeneous situations; a metho ....Trustworthy Hypothesis Transfer Learning. It is urgent to develop a new hypothesis transfer learning scheme that can overcome potential risks when finetuning unreliable large-scale pre-trained models. This project aims to develop an advanced and reliable scheme of hypothesis transfer learning, called Trustworthy Hypothesis Transfer Learning (TrustHTL). A new theoretically guaranteed heterogeneous hypothesis transfer learning framework will be developed to handle heterogeneous situations; a methodology to disinherit risks of pre-trained models and a new fuzzy relation based distributional discrepancy in heterogeneous transfer learning scenarios. The outcomes should significantly improve the reliability of machine learning with benefits for safety learning in data analytics.Read moreRead less
A Study Addressing Motor, Cognitive And Attentional Deficits In Presymptomatic Gene Carriers For Huntington's Disease
Funder
National Health and Medical Research Council
Funding Amount
$180,330.00
Summary
Since the discovery of the Huntington's disease (HD) gene mutation there has been much controversy in the literature relating to whether there are any preclinical deficits in individuals who are gene positive for HD but who have not yet been clinically diagnosed with the disease. Our aim is to examine, over a three year period, the cognitive, attentional and motor performance of presymptomatic gene-positive, and negative, individuals on a wide variety of computerized experimental procedures, whi ....Since the discovery of the Huntington's disease (HD) gene mutation there has been much controversy in the literature relating to whether there are any preclinical deficits in individuals who are gene positive for HD but who have not yet been clinically diagnosed with the disease. Our aim is to examine, over a three year period, the cognitive, attentional and motor performance of presymptomatic gene-positive, and negative, individuals on a wide variety of computerized experimental procedures, which we have previously shown to be sensitive to deficits in individuals who have already been diagnosed with HD. If progressive behavioural changes in gene-positive individuals can be reliably documented to occur before the clinical symptoms of HD are evident, this would be of profound significance as it would allow a set of criteria to be established to assist in early detection of clinical onset of symptoms, and possibly permit use of newly-emerging therapies.Read moreRead less
Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100751
Funder
Australian Research Council
Funding Amount
$379,506.00
Summary
How health shapes young children’s academic outcomes, and opportunities to intervene. Every year, about 280,000 Australian children make the crucial transition from preschool to formal education. Within this population, there is a wide range of learning capabilities and levels of preparedness. Children who have difficulties during the early years have greater risk of poorer academic and social outcomes. This project aims to determine how children's academic outcomes are shaped by common physical ....How health shapes young children’s academic outcomes, and opportunities to intervene. Every year, about 280,000 Australian children make the crucial transition from preschool to formal education. Within this population, there is a wide range of learning capabilities and levels of preparedness. Children who have difficulties during the early years have greater risk of poorer academic and social outcomes. This project aims to determine how children's academic outcomes are shaped by common physical health problems during the early years of school and how best to address these problems within the traditional school setting. This will inform future research as to the opportunities to help all children have the best opportunity to learn so they can reach their academic potential.Read moreRead less
Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capabili ....Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.Read moreRead less
The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project ....The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project are new understandings of how problem-answer associations can be strengthened in memory and the development of tools to promote retrieval-based strategies. Potential benefits include children who are better prepared to take on higher-level mathematics in secondary school and, subsequently, more numerate citizens. Read moreRead less