Decoding change of mind decisions and errors from brain activity in humans. This project intends to provide new insights into how the brain changes a decision to achieve better outcomes. Decision-making is rarely optimal, and in a dynamic world people must often change their initial decisions in order to avoid consequential errors. This project aims to investigate the neural mechanisms underlying such change-of-mind decisions and decision errors in humans. To this end, it plans to use novel deco ....Decoding change of mind decisions and errors from brain activity in humans. This project intends to provide new insights into how the brain changes a decision to achieve better outcomes. Decision-making is rarely optimal, and in a dynamic world people must often change their initial decisions in order to avoid consequential errors. This project aims to investigate the neural mechanisms underlying such change-of-mind decisions and decision errors in humans. To this end, it plans to use novel decoding techniques to predict the evolution of change-of-mind decisions from brain activity while decisions unfold. This approach would clarify how quality of information, effort, and reward are integrated at a neural level to bias people towards changing their decisions. The expected results would provide an improved understanding of the neural dynamics of errors and how the brain corrects decisions online to achieve better outcomes.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
The brain in real time: a neural model of rhythmic action and perception. This project aims to study a fundamental function of the human brain: its temporal architecture. It will provide an innovative perspective on the neural mechanisms underlying and relating perception, intention, and voluntary action in real time, though a combination of eye-tracking, behaviour, and neural recordings. By providing a common language with which to relate perception, cognition, volition and action, this will ....The brain in real time: a neural model of rhythmic action and perception. This project aims to study a fundamental function of the human brain: its temporal architecture. It will provide an innovative perspective on the neural mechanisms underlying and relating perception, intention, and voluntary action in real time, though a combination of eye-tracking, behaviour, and neural recordings. By providing a common language with which to relate perception, cognition, volition and action, this will provide significant benefits that will transform the way we think about brain function.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.
Improving human reasoning with causal Bayes networks: a multimodal approach. This project aims to improve human causal and probabilistic reasoning about complex systems by taking a user-centric, multimodal, interactive approach. The project will explore new integrated visual and verbal ways of explaining a causal probabilistic model and its reasoning, to reduce known human reasoning difficulties, and investigate how to reduce cognitive load by prioritising the most useful user- and context-speci ....Improving human reasoning with causal Bayes networks: a multimodal approach. This project aims to improve human causal and probabilistic reasoning about complex systems by taking a user-centric, multimodal, interactive approach. The project will explore new integrated visual and verbal ways of explaining a causal probabilistic model and its reasoning, to reduce known human reasoning difficulties, and investigate how to reduce cognitive load by prioritising the most useful user- and context-specific information. Expected outcomes include novel AI methods that empower users to drive the reasoning process and strengthen trust in the system’s reasoning. Performance will be assessed in medical and legal domains, with significant potential benefits to end users from better, more transparent reasoning and decision making.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
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
Modelling trajectories of cognitive control in adolescents and young adults. This project aims to develop an innovative framework that models behaviour, brain function and brain structure to characterise developmental trajectories of cognitive control in typically-developing young people, and to test the model’s ability to predict psychosocial outcomes. Cognitive control processes are supported by complex frontal brain networks that develop well into adulthood. Poor cognitive control is linked t ....Modelling trajectories of cognitive control in adolescents and young adults. This project aims to develop an innovative framework that models behaviour, brain function and brain structure to characterise developmental trajectories of cognitive control in typically-developing young people, and to test the model’s ability to predict psychosocial outcomes. Cognitive control processes are supported by complex frontal brain networks that develop well into adulthood. Poor cognitive control is linked to negative psychosocial outcomes (e.g. substance use, high-risk behaviours). This work is expected to inform evidence-based programmes that identify young people at risk and develop targeted training strategies to improve psychosocial outcomes.Read moreRead less
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 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