Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encodi ....Developing a Unified Theory of Episodic Memory. This project aims to develop a model of episodic memory and to apply the model to both adult and child development data. Unlike current approaches, the model is expected to address multiple memory tasks including item recognition, associative recognition, source recognition and cued recall, and also aims to address reaction time data, allowing different sources of interference causing forgetting in adults to be identified. By addressing both encoding and retrieval processes, the model can assess how changes in different sources of interference modulate performance through the trajectory of early development. Hierarchical Bayesian estimation aims to enable a simultaneous account of multiple tasks and support future deployment in applied contexts.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
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
Special Research Initiatives - Grant ID: SR0354513
Funder
Australian Research Council
Funding Amount
$20,000.00
Summary
The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, ex ....The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, explore new ways in which computational models inform our understanding of human languages, and exploit new opportunities for applying theories of language in the development of human language technologies.Read moreRead less
Using written language to probe speech recognition models. Speech recognition models fall into two principal classes, with fundamentally different processing architectures. Feedback models (e.g. TRACE, McClelland & Elman, 1986) allow lexical knowledge to exert top-down control over phonemic analysis. Feedforward models (e.g. Merge, Norris, McQueen & Cutler, 2000) assume that information flow is entirely bottom-up. Our project adopts an innovative approach to testing between these model classe ....Using written language to probe speech recognition models. Speech recognition models fall into two principal classes, with fundamentally different processing architectures. Feedback models (e.g. TRACE, McClelland & Elman, 1986) allow lexical knowledge to exert top-down control over phonemic analysis. Feedforward models (e.g. Merge, Norris, McQueen & Cutler, 2000) assume that information flow is entirely bottom-up. Our project adopts an innovative approach to testing between these model classes, by examining the influence of written-word knowledge on speech perception. To distinguish the models, contrasts must test different processing levels and examine strategy effects. TRACE favors broad effects with limited strategic influence; Merge favors lexical effects that are necessarily sensitive to strategic factorsRead moreRead less
Modifying The Trajectory Of Insidious Late Life Cognitive Decline Using Computerised Cognitive Training
Funder
National Health and Medical Research Council
Funding Amount
$743,152.00
Summary
Supervised, group-based computerised cognitive training (CCT) is a safe and effective intervention to maintain cognition in healthy older adults. This project will examine the extent to which CCT can attenuate or even reverse the rate of decline in older people with previously documented cognitive decline, as well as strategies to maintain CCT effects in the long term.
The early communicative environment prior to and following cochlear implants: impact on children's early communicative and cognitive development. This research with children with cochlear implants will examine the effect on language development of being in an oral environment or one that also includes sign language. The outcomes will provide information for parents and professionals enabling informed decision about the management of the children to promote the best possible outcomes.
Local Sleep In The Awake Brain: An Underlying Cause Of Neurobehavioural Deficits In Sleep Apnea?
Funder
National Health and Medical Research Council
Funding Amount
$582,330.00
Summary
Obstructive sleep apnea (OSA) is a common sleep disorder which significantly impacts daytime functioning leading to excessive sleepiness, and problems with attention and thinking. Currently, the causes for cognitive impairment in OSA (including attentional lapses and performance deficits) are poorly understood. In the awake state, groups of neurons can briefly go “offline” as they do in sleep. These periods of “local sleep” may explain impaired task performance in OSA.