A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in ....A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in sound-to-meaning correspondences as probabilistic cues to attain spoken language. The outcome will be a better neural account of language comprehension and production. The benefit of this new account will be a stronger basis for assessment and treatment of developmental and acquired language impairments.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
Learning and choosing in a complex world. How do people make choices in a complex world? Making good choices requires expertise, but people must often forego rewards in order to acquire this knowledge. This is the essence of an "explore-exploit dilemma": to maximise rewards across a long time frame, people must take the time to explore and learn now. Empirically, this project aims to unify much of the existing psychological literature and extend it to cover richer, more complex problems. Theoret ....Learning and choosing in a complex world. How do people make choices in a complex world? Making good choices requires expertise, but people must often forego rewards in order to acquire this knowledge. This is the essence of an "explore-exploit dilemma": to maximise rewards across a long time frame, people must take the time to explore and learn now. Empirically, this project aims to unify much of the existing psychological literature and extend it to cover richer, more complex problems. Theoretically, the project aims to use tools from machine learning to compare human decision making to optimal planning models.Read moreRead less
Investigation of the component distributions of pause duration in spontaneous speech: Constraints for models of language production. We have discovered that the distribution of pause durations in spontaneous speech of individual speakers can be decomposed into at least two log-normal distributions. Our project will investigate this finding and provide a foundation for new research relevant to language production models. This will be achieved by determining the semantic, lexical, psycholinguistic ....Investigation of the component distributions of pause duration in spontaneous speech: Constraints for models of language production. We have discovered that the distribution of pause durations in spontaneous speech of individual speakers can be decomposed into at least two log-normal distributions. Our project will investigate this finding and provide a foundation for new research relevant to language production models. This will be achieved by determining the semantic, lexical, psycholinguistic, physiological, and acoustic concomitants of each component distribution and by investigating the impact of selected variables on the shape and location of each. The project has important implications for models of language production and applied problems involving automatic speech recognition, forensic speaker identification, and human communication disorders.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
Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data t ....Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data that can extend and falsify current models of reading.
Benefits: These developments will significantly increase our understanding of how people read and what causes dyslexia. This work will also provide new ways to evaluate complex computational psychological models.Read moreRead less
Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropria ....Expecting the unexpected: how people prioritise predictability. This project aims to investigate how people represent and use information about unpredictability in their environment. Seeing too much predictability is problematic, but seeing too little can also be a problem, for example inappropriate "learned helplessness" can occur, whereby people feel disempowered because the world is seen as random. Recent findings demonstrated a bias in fundamental learning that may maintain these inappropriate beliefs about unpredictability. This bias is not anticipated by formal theories of learning. The project will investigate how this bias is brought about by first formalising a novel theory of fundamental learning and then systematically testing its assumptions.Read moreRead less
Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The ....Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The project is expected to explain the link between reading performance and underlying influences and why dyslexia manifests differently in different languages.Read moreRead less
Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the po ....Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the potential to make a major impact in understanding how information is understood and shared, especially when it is about topics that people lack firsthand knowledge about, like climate change. The computational models also have applications to the development of expert systems upon which our information economy relies.Read moreRead less
Uncovering the processes underlying human reasoning: A state-trace approach. This project aims to answer the most important unresolved question in the psychology of reasoning; how many distinct cognitive processes underlie human reasoning? To answer this question, this project aims to conduct an extensive experimental investigation of the factors that selectively impact inductive and deductive inferences and the application of high-dimensional state-trace analysis; a powerful new method for diag ....Uncovering the processes underlying human reasoning: A state-trace approach. This project aims to answer the most important unresolved question in the psychology of reasoning; how many distinct cognitive processes underlie human reasoning? To answer this question, this project aims to conduct an extensive experimental investigation of the factors that selectively impact inductive and deductive inferences and the application of high-dimensional state-trace analysis; a powerful new method for diagnosing underlying processes from behavioural data. The project is expected also to develop a new computational model that accounts for both inductive and deductive forms of reasoning.Read moreRead less