Getting back on track after the unexpected happens: decision making in predictable and unpredictable environments. This project intends to examine how the brain decides where to look next with our eyes, a decision made approximately three times every second. Understanding how the normal brain makes decisions will in turn help us to understand what happens when things go wrong in diseases like dementia and Parkinson's disease.
The Psychology of Misinformation—Towards A Theory-driven Understanding. The project aims to develop a psychological theory of misinformation effects. Misinformation influences people’s memory, reasoning and decision-making even after corrections – it thus poses a significant challenge for science and society. Through the combination of systematic experimentation with theory-driven computational modelling, the project will strive to concurrently consider individual-level cognition and the impact ....The Psychology of Misinformation—Towards A Theory-driven Understanding. The project aims to develop a psychological theory of misinformation effects. Misinformation influences people’s memory, reasoning and decision-making even after corrections – it thus poses a significant challenge for science and society. Through the combination of systematic experimentation with theory-driven computational modelling, the project will strive to concurrently consider individual-level cognition and the impact of sociocultural context. It is anticipated that this novel integrative approach will substantially expand our understanding of misinformation effects, and that this theoretical progress will result in the formulation of specific communication strategies to reduce the impact of misinformation on society.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
The desire for knowledge: Neural mechanisms of information-seeking. This project aims to determine the mechanisms that drive individuals to seek out information, and to characterise the neural processes that underlie how that information is valued. The project tests the idea that information is represented in the brain as a form of reward. The results are expected to contribute significant mechanistic insights at the level of brain and behaviour on the nature of information value. This is likely ....The desire for knowledge: Neural mechanisms of information-seeking. This project aims to determine the mechanisms that drive individuals to seek out information, and to characterise the neural processes that underlie how that information is valued. The project tests the idea that information is represented in the brain as a form of reward. The results are expected to contribute significant mechanistic insights at the level of brain and behaviour on the nature of information value. This is likely to have wide-ranging implications across multiple domains of human endeavour, including education, work-place efficiency, policy development, and consumer behaviour.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101508
Funder
Australian Research Council
Funding Amount
$447,000.00
Summary
A Brain-Behaviour Model of Decision-Making Under Distraction. People make thousands of decisions each day, such as judging whether it is safe to cross the street at a busy intersection. This project aims to investigate how decision-making is impacted when a person is temporarily distracted, for example when receiving a text message alert from one’s phone. By combining recordings of brain activity with cutting-edge mathematical modelling techniques, this project expects to develop a novel theoret ....A Brain-Behaviour Model of Decision-Making Under Distraction. People make thousands of decisions each day, such as judging whether it is safe to cross the street at a busy intersection. This project aims to investigate how decision-making is impacted when a person is temporarily distracted, for example when receiving a text message alert from one’s phone. By combining recordings of brain activity with cutting-edge mathematical modelling techniques, this project expects to develop a novel theoretical framework that captures the effects of distraction on brain networks that underpin human decision-making performance. This knowledge should be highly beneficial for developing informed policies that reduce effects of distraction and preserve decision-making capacity in safety critical situations.Read moreRead less
Cognitive models of decision making in clinical populations. This cognitive science project aims to develop new methods for mathematical modelling of decision making, and to apply these methods to study decision making in people with problem drug use. Precise measures of the thought processes underlying decision making in drug users will help to direct efforts to prevent and treat drug problems.
Discovery Early Career Researcher Award - Grant ID: DE150101301
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Cognitive Models of Human Decision-making in Cybersecurity Settings. This project aims to study human decision-making by attackers, defenders and users, in a cyber-security setting. Cognitive modelling of these decisions will play a central role in understanding and optimising the safety of cyberspace. This project will involve three components: new behavioural experiments focusing on cybersecurity situations of prevention and detection; cognitive models to understand and predict how people make ....Cognitive Models of Human Decision-making in Cybersecurity Settings. This project aims to study human decision-making by attackers, defenders and users, in a cyber-security setting. Cognitive modelling of these decisions will play a central role in understanding and optimising the safety of cyberspace. This project will involve three components: new behavioural experiments focusing on cybersecurity situations of prevention and detection; cognitive models to understand and predict how people make decisions in such settings; and the evaluation of these models against behavioural data using Bayesian statistical methods. This will then be applied to operational problems that will involve, determining optimal security policies, automated behaviour in adversarial situations, and individualised training.Read moreRead less
The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program ....The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program of experimental investigation and computational modelling. The anticipated benefits include an enhanced understanding of human inference, especially in domains such as the evaluation of forensic or financial evidence, where data censoring is common.Read moreRead less
Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits ....Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.Read moreRead less
Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time ....Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.Read moreRead less