Modifiable Risks And Interventions For Cognitive Decline, Depression And Dementia In Older People
Funder
National Health and Medical Research Council
Funding Amount
$430,055.00
Summary
This research proposal will explore the modifiable risk factors for cognitive decline (ie. changes in memory and thinking functions) in older people. It will examine the pertinence of critical contributors to glial-neuronal networks including depression, cardiovascular disease, sleep-wake systems, mental and physical exercise, inflammatory processes and diet, as well as test interventions that target these risk factors. It will use sophisticated brain scanning methods to examine which factors pr ....This research proposal will explore the modifiable risk factors for cognitive decline (ie. changes in memory and thinking functions) in older people. It will examine the pertinence of critical contributors to glial-neuronal networks including depression, cardiovascular disease, sleep-wake systems, mental and physical exercise, inflammatory processes and diet, as well as test interventions that target these risk factors. It will use sophisticated brain scanning methods to examine which factors promote neuroplasticity.Read moreRead less
Studies Of The Effects Of Asymmetric Hearing Loss On The Brain
Funder
National Health and Medical Research Council
Funding Amount
$920,076.00
Summary
Hearing loss impairs the normal development and maintenance of auditory pathways. Irreversible pathologies persist when hearing is not restored in a timely manner. While cochlear implantation is the accepted treatment for profound sensorineural hearing loss, there is significant variability in outcomes. Some of this variability is linked to the degree of hearing asymmetry. Thus, we propose to study brain changes in the auditory system that accompany asymmetric hearing impairment.
Mechanisms of Recovery after Extinction of Conditioned Behaviour. Old habits die hard and may never die at all. My previous ARC-funded research has revealed that extinguished learning can be recovered rapidly and in unsuspected ways. This project is aimed at building a neural network to explain how old learning can recovered. In practical terms, rapid recovery has both benefits, e.g., our ability to regain old skills with brief refresher training, and costs, e.g., relapse after therapies for anx ....Mechanisms of Recovery after Extinction of Conditioned Behaviour. Old habits die hard and may never die at all. My previous ARC-funded research has revealed that extinguished learning can be recovered rapidly and in unsuspected ways. This project is aimed at building a neural network to explain how old learning can recovered. In practical terms, rapid recovery has both benefits, e.g., our ability to regain old skills with brief refresher training, and costs, e.g., relapse after therapies for anxiety disorders and substance abuse. In theoretical terms, understanding recovery in biological systems will inform research concerning both the neural basis of memory and the design of robots.Read moreRead less
Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results ....Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results will test the generality of principles that have been developed in studies of female mate choice and extend these ideas to address intra-sexual selection operating through opponent assessment.Read moreRead less
Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, commun ....Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, community the ability to contribute to growing our knowledge-based society in a safe, transparent and trustworthy manner. Outcomes will include innovative instruments to teach machines, novel knowledge creation, trusted and transparent AI systems, and a new generation of human teachers specialised in educating AI systems.Read moreRead less
Memetic algorithms for multiobjective optimisation problems in bioinformatics. Many questions of paramount importance in life sciences can be formulated as optimisation problems but using just a single criterion can be misleading. This project will address this problem using multiobjective optimisation and leveraging Australia's investment in supercomputing with algorithms that mimic evolutionary processes in silico.
Memetic algorithms and adaptive memory metaheuristics for large scale combinatorial optimisation problems arising in biomarker discovery. Despite modern supercomputers, the world depends on combinatorial optimisation, the branch of mathematics and computer science that involves finding optimal solutions when it is impossible to enumerate all solutions. We bring complementary skills to address the core set of the five most challenging problems arising from novel biotechnologies.
Unleashing the power of a supernetwork-driven approach for bioinformatics. Supernetworks are built “above and beyond” existing networks. In bioinformatics they arise from the integration of a set of networks with different types of nodes and edges. While large companies and governments have already understood the importance of decision problems in supernetworks, the power of this perspective has not yet been exploited in the life sciences. Using supercomputer-based approaches together with memet ....Unleashing the power of a supernetwork-driven approach for bioinformatics. Supernetworks are built “above and beyond” existing networks. In bioinformatics they arise from the integration of a set of networks with different types of nodes and edges. While large companies and governments have already understood the importance of decision problems in supernetworks, the power of this perspective has not yet been exploited in the life sciences. Using supercomputer-based approaches together with memetic algorithms, this project will address the first key areas that will lead to smart information use of existing networks in distributed databases. This project will deliver the next generation of algorithms for network alignment, identification of connected-cohesive subnetworks and embedding large graphs in multi-planar structures.Read moreRead less
Challenging systems to discover vulnerabilities using computational red teaming. Computational red teaming concerns the design of computational models to role play intelligent adversaries. These adversaries who are determined to exploit a system rely on creative thinking to discover system-level vulnerabilities by challenging system design, implementation or operations. This project closes a gap in the risk assessment literature by designing automated computational red teaming methods to discove ....Challenging systems to discover vulnerabilities using computational red teaming. Computational red teaming concerns the design of computational models to role play intelligent adversaries. These adversaries who are determined to exploit a system rely on creative thinking to discover system-level vulnerabilities by challenging system design, implementation or operations. This project closes a gap in the risk assessment literature by designing automated computational red teaming methods to discover vulnerabilities associated with intentional risks. Scientific outcomes include novel automated skill assessment algorithms and new search techniques to exploit assumptions that could have been overlooked otherwise. Practical outcomes include robust risk assessment tools, strong research training, and high impact publications.Read moreRead less