Motor Functioning In Young People With Attention Deficit Hyperactivity Disorder – Combined Type: A Three-dimensional Motion Analysis Study.
Funder
National Health and Medical Research Council
Funding Amount
$477,065.00
Summary
Attention deficit hyperactivity disorder –combined type (ADHD-CT) is a complex neuropsychiatric disorder with a progressively devastating impact on psychosocial development. The first objective of this study is to use 3D-motion analysis to ‘probe’ the underlying brain dysfunction which characterises ADHD-CT. The second objective of this study is to improve our understanding of the link between movement problems, and (a) injury proneness, and (b) social-communicative problems, in children with AD ....Attention deficit hyperactivity disorder –combined type (ADHD-CT) is a complex neuropsychiatric disorder with a progressively devastating impact on psychosocial development. The first objective of this study is to use 3D-motion analysis to ‘probe’ the underlying brain dysfunction which characterises ADHD-CT. The second objective of this study is to improve our understanding of the link between movement problems, and (a) injury proneness, and (b) social-communicative problems, in children with ADHD-CT.Read moreRead less
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
Ocular Motility In Autism And Asperger S Disorder: Dissociation Of Motor Deficits.
Funder
National Health and Medical Research Council
Funding Amount
$131,235.00
Summary
We will use ocular motor technology to investigate motor dysfunction in autism and Asperger's disorder, to advance our understanding of the neurobiological bases of these disorders. This will help clarify whether neural networks are differentially disrupted in these disorders, as our previous clinical research suggests. This dissociation and the subsequent development of an ocular motor clincal screen may improve diagnosis, and potentially treatment, of these devastating conditions.
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
Optimising Speech Assessment And Treatment In Frontotemporal Dementia
Funder
National Health and Medical Research Council
Funding Amount
$722,210.00
Summary
Frontotemporal dementia has a devastating impact on our ability to speak and understand others. This proposal aims to improve our understanding of how to best assess, diagnose and treat these debilitating impairments. By bringing together an international consortium of clinics, these findings will lead to significant advances in our understanding of disease progression and patient care.
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
Musculoskeletal injuries sustained as a consequence of road traffic crashes are common and costly to the Australian community. Many people do not recover well after the injury but suffer ongoing pain and disability. The Centre for Research Excellence in Recovery Following Road Traffic Injury will target a clear need to improve health outcomes for injured individuals through research, capacity building and end-user engagement with a focus in primary care.
Motor problems, ranging from clumsiness to cerebral palsy, are one of the most common adverse outcomes in children born early. This study will investigate the motor development of children born <30 weeks’ gestation compared with peers born at term from birth to 5 years. We will determine whether early clinical evaluations or neuroimaging in the newborn period can predict later motor impairment at 5 years to be able to identify those who will benefit most from early intervention.
A Longitudinal Neuroimaging Study Investigating Reorganisation Of Cerebellar-cerebral Networks In Friedreich Ataxia
Funder
National Health and Medical Research Council
Funding Amount
$816,908.00
Summary
Friedreich ataxia (FRDA) causes debilitating motor and cognitive deficits. We propose a longitudinal multi-modal magnetic resonance (MR) imaging study to measure different types of tissue in the brain in this disease. We seek to understand how the brain reorganises itself due to cell loss in the spinal cord, cerebellum and cerebral cortex. This study will establish sensitivity of a range of MR imaging measures as potential biomarkers for use in large multi-centre drug trials in this disease.
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