Epigenetic mechanisms regulating sex differences in fear-related learning and memory. Anxiety disorders represent an enormous burden on society and are associated with premature aging and infertility in men and women. Evidence also indicates that parental anxiety affects child development. Given that fear-related learning has an important influence on emotional health which, in turn, affects lifestyle and the aging process, an understanding of the neural mechanisms mediating sex differences in ....Epigenetic mechanisms regulating sex differences in fear-related learning and memory. Anxiety disorders represent an enormous burden on society and are associated with premature aging and infertility in men and women. Evidence also indicates that parental anxiety affects child development. Given that fear-related learning has an important influence on emotional health which, in turn, affects lifestyle and the aging process, an understanding of the neural mechanisms mediating sex differences in fear learning will enhance our ability to develop better therapeutic approaches for treating anxiety and preventing relapse, potentially through a gender-specific approach. The studies outlined in this proposal will have implications for promoting and maintaining good health.Read moreRead less
Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demand ....Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demands when dealing with multiple stimuli or performing multiple tasks concurrently under time pressure. The project aims to provide the basic research that is needed to extend psychological models of choice to complex ‘real-world’ tasks, such air traffic control and maritime surveillance.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100772
Funder
Australian Research Council
Funding Amount
$393,414.00
Summary
Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of ....Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of the time course of decision-making. The new theory will provide a quantitative account of how incremental associative learning processes drive changes in cognitive representations that, in turn, account for known changes in the time course of decision-making.Read moreRead less
A process model of visual working memory. This project aims to develop a process model of encoding of items into memory. Working memory is central to almost all cognitive functions, but little is known about short-term memory for visual information. Progress in this area is slow because of a focus on models that do not specify the processes underlying memory, and no model explains the processes that would limit the number of items the memory can hold to four. A process model is expected to addre ....A process model of visual working memory. This project aims to develop a process model of encoding of items into memory. Working memory is central to almost all cognitive functions, but little is known about short-term memory for visual information. Progress in this area is slow because of a focus on models that do not specify the processes underlying memory, and no model explains the processes that would limit the number of items the memory can hold to four. A process model is expected to address fundamental issues in visual working memory.Read moreRead less
The role of relational information in the guidance of visual attention. The project aims to develop a new theory of attention that describes more accurately which items in the visual field can pop out and grab attention. The potential practical gains of the project are high, as it can lead to significant advancements in robotic vision, transport safety, and provide insights into clinical disorders such as ADHD.
Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures ....Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures from their sequences. The expected outcomes should provide significant benefits by computationally determining protein structures beyond homologous sequences, and enabling structure-based drug discovery to disease-causing protein targets previously inaccessible to biotech and pharmaceutical companies.Read moreRead less
The flipside of noise: Does it benefit listening and learning? People with low attention capacity can experience improvements in cognitive function (eg memory) in the presence of external white noise. This project aims to determine the brain mechanisms for this improvement and how it affects oral language comprehension and verbal learning. In doing so, the research would change the prevailing view that noise is always detrimental to mental processes, and provide a theoretical framework for predi ....The flipside of noise: Does it benefit listening and learning? People with low attention capacity can experience improvements in cognitive function (eg memory) in the presence of external white noise. This project aims to determine the brain mechanisms for this improvement and how it affects oral language comprehension and verbal learning. In doing so, the research would change the prevailing view that noise is always detrimental to mental processes, and provide a theoretical framework for predicting how an individual’s cognitive capacity is affected by the presence of noise. It may support the development of methods to improve educational participation and outcomes for children, particularly those with lower attention, and for older adults.Read moreRead less
A new training approach to address the novice driver problem. This project aims to develop a new approach to driver training. For the second consecutive year, road deaths in Australia have increased by 150 from 2014 to 2016. The increase in deaths was greatest for young drivers between the ages of 17-25 years, who remain over-represented in road deaths. The majority of these deaths occur in the first few months after licensing. This project expects to generate new knowledge, where the focus is o ....A new training approach to address the novice driver problem. This project aims to develop a new approach to driver training. For the second consecutive year, road deaths in Australia have increased by 150 from 2014 to 2016. The increase in deaths was greatest for young drivers between the ages of 17-25 years, who remain over-represented in road deaths. The majority of these deaths occur in the first few months after licensing. This project expects to generate new knowledge, where the focus is on developing young driver’s cognitive skills about speed choice through the provisions of a training program that focuses on feedback. The results will have the potential to be used by road authorities and driver training organisations to improve road safety.Read moreRead less
Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implement ....Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project will systematically develop a framework by combining modal-logics to adequately capture and reason about temporal, epistemic and social aspects of dynamic and multi-agent systems. The combined logics would be evaluated on practical applications.
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Forensic reasoning and uncertainty: identifying pattern and impression expertise. Maintaining high standards of evidence is vital for an effective justice system and ensuring that innocent people are not wrongly accused. This project aims to improve the reliability of forensic evidence and the value of expert testimony in the criminal justice system by examining forensic decision making.