Discovery Early Career Researcher Award - Grant ID: DE170100106
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Measuring interference from prior memories using experience sampling. The project aims to better understand the causes of forgetting in recognition memory. This project will measure participants' experiences using smartphone technology for four weeks before a recognition memory experiment. Similarities between the images in the experiment and images in prior experience can be used to fully specify all interference components within a computational model of recognition memory, leading to a comple ....Measuring interference from prior memories using experience sampling. The project aims to better understand the causes of forgetting in recognition memory. This project will measure participants' experiences using smartphone technology for four weeks before a recognition memory experiment. Similarities between the images in the experiment and images in prior experience can be used to fully specify all interference components within a computational model of recognition memory, leading to a complete model of recognition memory. Better understanding the causes of forgetting in recognition memory could show how interference contributes to memory impairments in ageing, and ultimately Alzheimer’s and other clinical disorders.Read moreRead less
Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outc ....Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outcome. This new knowledge will enhance the world-class status of Australian cognitive psychology. Moreover, it should provide significant benefits through improving our ability to predict and shape behaviour, and shedding light on the role of biases in healthy cognition and in the context of compulsive behaviours.Read moreRead less
A statistical decision theory of cognitive capacity. This project aims to investigate the limited capacity of the human cognitive system to form representations of the things in the world around us and to make decisions about them in real time. Its goal is to provide an integrated theory of cognitive capacity based on the statistical properties of cognitive representations and the decision processes that act on them. Its expected outcome will be a unified metric for cognitive capacity that will ....A statistical decision theory of cognitive capacity. This project aims to investigate the limited capacity of the human cognitive system to form representations of the things in the world around us and to make decisions about them in real time. Its goal is to provide an integrated theory of cognitive capacity based on the statistical properties of cognitive representations and the decision processes that act on them. Its expected outcome will be a unified metric for cognitive capacity that will allow us to quantify how cognitive load affects the speed and accuracy of decision making. It will benefit the design and evaluation of high workload real-time decision systems and will contribute to the selection and training of users of such systems.
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Discovery Early Career Researcher Award - Grant ID: DE240101348
Funder
Australian Research Council
Funding Amount
$470,999.00
Summary
Synergies between physical exercise, brain stimulation, and neuroplasticity. The brain is a highly dynamic organ. This capacity, known as neuroplasticity, governs our ability to learn new skills, acquire new knowledge, and fine-tune cognition. This project aims to investigate synergies between exercise, brain stimulation, and neuroplasticity, via application of a highly innovative interdisciplinary approach combining exercise physiology and cognitive neuroscience techniques. This project will pi ....Synergies between physical exercise, brain stimulation, and neuroplasticity. The brain is a highly dynamic organ. This capacity, known as neuroplasticity, governs our ability to learn new skills, acquire new knowledge, and fine-tune cognition. This project aims to investigate synergies between exercise, brain stimulation, and neuroplasticity, via application of a highly innovative interdisciplinary approach combining exercise physiology and cognitive neuroscience techniques. This project will pioneer novel, non-invasive methods of harnessing neuroplasticity to improve brain function, and generate fundamental insights into the mechanisms mediating learning and memory. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100433
Funder
Australian Research Council
Funding Amount
$365,058.00
Summary
Cortical layer specific functional imaging of the human brain. This project aims to record layer specific cortical activity in humans by leveraging ultra-high field magnetic resonance imaging. It expects to yield robust techniques for the general analysis of neuroimaging-based, layer-specific measurements. This project will progress the fields of cognitive neuroscience and neuroimaging as well as bring the field of neuroimaging closer to that of neurophysiology and thus facilitate collaboration ....Cortical layer specific functional imaging of the human brain. This project aims to record layer specific cortical activity in humans by leveraging ultra-high field magnetic resonance imaging. It expects to yield robust techniques for the general analysis of neuroimaging-based, layer-specific measurements. This project will progress the fields of cognitive neuroscience and neuroimaging as well as bring the field of neuroimaging closer to that of neurophysiology and thus facilitate collaboration among researchers.Read moreRead less
Determining principles for successful episode retrieval of repeated events. This project aims to develop the first-ever set of explanatory principles for how people successfully retain and retrieve individual episode memories from repeated experiences (e.g., one occurrence of a routine social encounter or job-related activity). By deepening our understanding of how memory works, this new knowledge is expected to lay the foundation for interview guidance and ongoing research aimed at enhancing th ....Determining principles for successful episode retrieval of repeated events. This project aims to develop the first-ever set of explanatory principles for how people successfully retain and retrieve individual episode memories from repeated experiences (e.g., one occurrence of a routine social encounter or job-related activity). By deepening our understanding of how memory works, this new knowledge is expected to lay the foundation for interview guidance and ongoing research aimed at enhancing the proficiency of investigations into matters that rely on detailed and accurate accounts of specific episodes. This includes workplace or traffic accident investigations, infectious disease contact tracing, as well as prosecution of repeated sexual offences.Read moreRead less
Using cognitive models to understand memorability of real world images. This proposal aims to understand and make predictions about which real world images -- specifically living things, objects, and human faces -- that people will remember remember via an integration of cognitive models of memory and machine learning techniques. Computer vision models and similarity scaling techniques will be used to produce psychological representations of the images. These representations will then be integra ....Using cognitive models to understand memorability of real world images. This proposal aims to understand and make predictions about which real world images -- specifically living things, objects, and human faces -- that people will remember remember via an integration of cognitive models of memory and machine learning techniques. Computer vision models and similarity scaling techniques will be used to produce psychological representations of the images. These representations will then be integrated with cognitive models of memory, which predict that images are more likely to be recognized if they are similar to each of the representations in memory. Large scale memory and similarity rating datasets will be used to develop and test the model.Read moreRead less
The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synt ....The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synthetic (AI-generated) misinformation. The expected outcome is new knowledge on the processing and impacts of emerging types of misinformation and translation into practical interventions. These promise to benefit consumers, educators and policymakers, contributing to a healthier information environment.Read moreRead less
Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes incl ....Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes include benchmark data from a novel paradigm for studying perceptual decisions and behavior and a model which can explain and predict human scheduling. This project aims to benefit industry by allowing for the simulation of information prioritisation by human agents in complex environments.Read moreRead less
Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to p ....Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to provide these languages with improved memory-management algorithms, and provides researchers and industry with a framework for innovation. This project will enable safe software that is more efficient on today's hardware and able to exploit emerging hardware. This project should lead to better performance and energy savings for server applications, phones, watches, and smart appliances, while ensuring memory safety.Read moreRead less