Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist ....Discrimination learning in humans: Associative and attentional mechanisms. This project offers three major benefits: (1) Australian researchers excel in cognitive neuroscience, learning and psychopharmacology, areas based largely on animal models of human cognition. This project contributes to these areas by specifying the relationship between animal learning and human cognition; (2) the project enhances Australia's international reputation in these areas via its collaboration with a scientist of Geoff Hall's stature; it also offers students outstanding research training and international exposure; (3) given Chris Mitchell's industry experience and the relevance of this work to advertising/marketing, this project will generate knowledge relevant to, and possible future collaborations with, Australian industries.Read moreRead less
Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different lear ....Evaluating models of category learning that use general feature-based representations. Three competing models of human category learning will be evaluated by comparing their behaviour to human performance on an experimental task where each model makes qualitatively different predictions. A series of theoretical and algorithmic advances will be undertaken to ensure each of the category learning models uses the same feature-based representation. Because the three models propose very different learning processes, their comparison will give insight into the basic cognitive process of categorisation. The algorithms for generating feature representations and modelling human category learning will also have potential for application in data visualisation and information handling systems.Read moreRead less
Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure present ....Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.Read moreRead less
Using shape change for object perception: human and artificial vision. This project aims to examine the steps taken by the visual system to code the shape of objects, including those that change shape over time. The project seeks to employ experiments assessing human vision and machine learning techniques to examine these codes and, in particular, focus on the advantages of a system that exaggerates shape change over time. Expected outcomes include an improved shape code based on superior human ....Using shape change for object perception: human and artificial vision. This project aims to examine the steps taken by the visual system to code the shape of objects, including those that change shape over time. The project seeks to employ experiments assessing human vision and machine learning techniques to examine these codes and, in particular, focus on the advantages of a system that exaggerates shape change over time. Expected outcomes include an improved shape code based on superior human performance that can have many applications in automated visual systems. This project can directly benefit the animation industries where the creation of realistic movement of humans and animals remains a computationally intensive challenge.Read moreRead less
The role of memory and reasoning processes in associative learning. The project will investigate how people learn to detect cues that predict or cause significant events in their environment (associative learning). The research builds on recent empirical and theoretical work by the investigators supporting the role of deductive reasoning processes in associative learning. Novel experimental strategies will be used to identify the separate and interacting roles of lower-level memory processes a ....The role of memory and reasoning processes in associative learning. The project will investigate how people learn to detect cues that predict or cause significant events in their environment (associative learning). The research builds on recent empirical and theoretical work by the investigators supporting the role of deductive reasoning processes in associative learning. Novel experimental strategies will be used to identify the separate and interacting roles of lower-level memory processes and higher-level reasoning processes. Existing competing models and novel cooperative models will be tested. The research will lead to a better understanding of associative learning in humans, and will also inform the construction of intelligent artificial systems.Read moreRead less
Making sense of ambiguity: brain system interactions and visual uncertainty. This project aims to identify and characterise the interactions between brain regions underlying a fundamental process in visual perception: interpreting sensory input that is unclear or ambiguous. It will use two complementary neuroimaging techniques and cutting-edge analysis methods. The intended outcomes include new insights into a fundamental but poorly characterised aspect of brain function: how brain regions inter ....Making sense of ambiguity: brain system interactions and visual uncertainty. This project aims to identify and characterise the interactions between brain regions underlying a fundamental process in visual perception: interpreting sensory input that is unclear or ambiguous. It will use two complementary neuroimaging techniques and cutting-edge analysis methods. The intended outcomes include new insights into a fundamental but poorly characterised aspect of brain function: how brain regions interact, and advanced analysis methods with wide application. Expected benefits include important advances in knowledge that lay foundations for future study of neural disorders, international collaboration, and new methods placing Australia at the forefront of the international effort to understand the human brain. Read moreRead less
Making sense of the world: how does the brain process task-relevant information? Contributing to a global effort to understand the human brain, this project will develop and use innovative brain imaging techniques to ask how our brains make sense of the world. This project establishes collaboration with a world renowned research centre in Cambridge, UK, and will be fundamental for advancing basic science in Australia.
How people learn inhibitory associations. This project aims to combine insights from associative and cognitive theories to investigate how people acquire, represent and generalise knowledge about inhibitory, or preventative, relationships. The project intends to use novel methods to assess the inhibitory causal structures inferred by individual participants, expected to include direct outcome prevention, modulation of a causal relationship, and configural learning. This project should expand our ....How people learn inhibitory associations. This project aims to combine insights from associative and cognitive theories to investigate how people acquire, represent and generalise knowledge about inhibitory, or preventative, relationships. The project intends to use novel methods to assess the inhibitory causal structures inferred by individual participants, expected to include direct outcome prevention, modulation of a causal relationship, and configural learning. This project should expand our understanding of the mechanisms of human associative learning. The project should benefit and inform clinical interventions based on identifying and normalising maladaptive learned associations.Read moreRead less
Testing a relational account for visual working memory. This project aims to test whether Becker's relational theory of attention can explain visual working memory performance, the ability to remember visual items over brief time periods. According to the relational account, elementary features such as colours are encoded relative to other features in the context (e.g. as redder, larger, darker). Our ability to detect a change in a feature would depend on the features in the context, and on whet ....Testing a relational account for visual working memory. This project aims to test whether Becker's relational theory of attention can explain visual working memory performance, the ability to remember visual items over brief time periods. According to the relational account, elementary features such as colours are encoded relative to other features in the context (e.g. as redder, larger, darker). Our ability to detect a change in a feature would depend on the features in the context, and on whether the context remains constant. This project expects to provide insights into how features are represented in memory, and to predict which items will be remembered. This could help to develop interactions and therapies for the ageing population and in clinical disorders.Read moreRead less
Development of a validated tool to help manage the risk of human fatigue in the workplace. Our world has embraced many benefits of the 24-hour society. However, these benefits can not be delivered without the costs: one significant cost is human fatigue. A recent federal parliamentary inquiry recommended that a fatigue risk management approach be applied to the regulation of working hours within industry. A key requirement of such an approach, and the aim of the proposed project, is to develo ....Development of a validated tool to help manage the risk of human fatigue in the workplace. Our world has embraced many benefits of the 24-hour society. However, these benefits can not be delivered without the costs: one significant cost is human fatigue. A recent federal parliamentary inquiry recommended that a fatigue risk management approach be applied to the regulation of working hours within industry. A key requirement of such an approach, and the aim of the proposed project, is to develop a scientifically validated tool to help manage the work-related fatigue associated with hours-of-work. Ultimately, this will reduce the costs of our 24-hour society on employees, their families, organisations and the wider community.Read moreRead less