Unravelling The Behavioural And Brain Mechanisms Of Compulsive Disorders, And New Ways To Treat Them
Funder
National Health and Medical Research Council
Funding Amount
$635,076.00
Summary
Disorders of compulsion, such as obsessive-compulsive disorder and substance use disorder, are chronic, debilitating, and present a significant cost to the individual and to society. Together, these disorders affect more than 10% of the population. Moreover, 40-60% of these individuals are resistant to current treatment. The current project is aimed at improving the preclinical research underlying our understanding the behavioural and brain mechanisms of such disorders and how to treat them.
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
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
Behaviour Bootstrapping for Ad Hoc, Heterogeneous Robot Swarms. This project aims to develop algorithms to permit groups of robots to evolve coordinated, collective, swarm behaviours. Groups of robots will be conceptualised as developmental swarm organisms with an initially limited set of behaviours, but equipped with structures and processes to permit them to evolve new behaviours. This project expects to deliver the next generation of computational intelligence technologies to enable humans to ....Behaviour Bootstrapping for Ad Hoc, Heterogeneous Robot Swarms. This project aims to develop algorithms to permit groups of robots to evolve coordinated, collective, swarm behaviours. Groups of robots will be conceptualised as developmental swarm organisms with an initially limited set of behaviours, but equipped with structures and processes to permit them to evolve new behaviours. This project expects to deliver the next generation of computational intelligence technologies to enable humans to harness large groups of robots for new kinds of transport and inspection tasks in smart cities, smart farming and defence. The expected outcomes of the project include new software frameworks for distributed developmental learning, extending developmental robotics to evolutionary robot swarms. 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
Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis f ....Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis for the development of platform technology capable of monitoring and detection of neural health status. Success is expected to yield a new generation of smart dynamic non-invasive systems that will be critical for developing effective solutions to counter life threating conditions for a large cross section of the Australian population.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.
Meshless, numerical modelling for polymer processing. The new modelling technology will significantly improve Australian polymer producers' competitiveness and their ability to respond to international market forces. The technology will lead to new opportunities for Australian companies that develop simulation software. Our consumers will benefit from improvements in the design of polymer products. Our researchers in rheology and computational mechanics will gain further opportunities to extend ....Meshless, numerical modelling for polymer processing. The new modelling technology will significantly improve Australian polymer producers' competitiveness and their ability to respond to international market forces. The technology will lead to new opportunities for Australian companies that develop simulation software. Our consumers will benefit from improvements in the design of polymer products. Our researchers in rheology and computational mechanics will gain further opportunities to extend the advances this project will make.Read moreRead less