Social buffering of fear inhibition in adolescent rats. Adolescence is an important time when individuals learn to manage stress-related emotions like fear. Peers can help, or hinder, individuals to regulate fear. This project aims to understand how, when, and for whom social buffering of fear regulation occurs during adolescence. It uses a behavioural, pharmacological, and neural approach to explore these issues. The project aims to close the gap in understanding of how social companions affect ....Social buffering of fear inhibition in adolescent rats. Adolescence is an important time when individuals learn to manage stress-related emotions like fear. Peers can help, or hinder, individuals to regulate fear. This project aims to understand how, when, and for whom social buffering of fear regulation occurs during adolescence. It uses a behavioural, pharmacological, and neural approach to explore these issues. The project aims to close the gap in understanding of how social companions affect basic learning and memory processes in an understudied population of adolescents. The expected outcomes of this project include a richer knowledge of how peers shape emotional regulation during development, which will ultimately inform social-based approaches for improving emotion regulation in youth.
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Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory develo ....Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory development about human and robot intergroup acceptance, enhanced institutional and international collaborations, and much needed psychological knowledge for robot designers. Benefits include a detailed understanding of how to increase the acceptance of robots in a wide variety of fields.Read moreRead less
Teaching An Old Brain New Tricks: Optimising Cognitive Training Through Neuroplasticity
Funder
National Health and Medical Research Council
Funding Amount
$1,562,250.00
Summary
People with early dementia have the most to gain from brain training programs aimed at delaying deterioration. Yet, its power is under-realised, with improvements not generalising to everyday living. This research program will harness the power of neuroplasticity to optimise brain training so that the effects transfer to everyday life. The knowledge gained will transform the way that we design and deliver brain training programs and revolutionise our understanding of why and how people respond.
Evaluating the Network Neuroscience of Human Cognition to Improve AI. This project will translate the brain’s inherent complexity into a set of explorable networks that will test the network theory of intelligence, and also be used to drive advances in next generation artificial neural networks. Our approach will catalyse new knowledge regarding how the complexity of the brain gives rise to cognition using innovative analyses inspired by physics and engineering. This fresh perspective on cogniti ....Evaluating the Network Neuroscience of Human Cognition to Improve AI. This project will translate the brain’s inherent complexity into a set of explorable networks that will test the network theory of intelligence, and also be used to drive advances in next generation artificial neural networks. Our approach will catalyse new knowledge regarding how the complexity of the brain gives rise to cognition using innovative analyses inspired by physics and engineering. This fresh perspective on cognition will accelerate understanding of normal cognitive function and also advance the development of advances in artificial neural network performance. Expected outcomes include methods to describe the computational signature of how cognition emerges from dynamic brain network activity and novel AI algorithms. Read moreRead less
Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include ....Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include a new and accurate deep neural network framework for learning, analysing and detecting human states from speech automatically using articulatory timing markers. This should provide significant benefits, such as individually-tailored, frequent and low-cost automatic detection, monitoring and analytics for adverse states.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100608
Funder
Australian Research Council
Funding Amount
$457,810.00
Summary
Characterising brain networks of intelligence through information tracking. For intelligent behaviour, the human brain needs to engage several processes including sensory, memory and motor processes. How it does this is one of the most significant questions in cognitive neuroscience. This project characterises the neural networks of human intelligence by advancing and building on the most recent advances in neuroimaging analyses. It will determine the interaction of different brain processes by ....Characterising brain networks of intelligence through information tracking. For intelligent behaviour, the human brain needs to engage several processes including sensory, memory and motor processes. How it does this is one of the most significant questions in cognitive neuroscience. This project characterises the neural networks of human intelligence by advancing and building on the most recent advances in neuroimaging analyses. It will determine the interaction of different brain processes by developing novel connectivity methods that track the flow of information through the brain with high temporal and spatial accuracy. The outcomes will be fundamental insights into the mechanisms of human intelligence and new connectivity analysis software that will have wide application in brain research.Read moreRead less
The Biology Of Risk For Bipolar Disorder: Genetic Effects In A High-risk Longitudinal Study
Funder
National Health and Medical Research Council
Funding Amount
$856,412.00
Summary
Bipolar disorder is a severe mood disorder affecting over 350,000 Australians. Some children of bipolar disorder patients will also become ill, although currently we have no tools to predict which of these genetically at-risk young individuals will eventually develop symptoms. This study will use genetic information plus brain structural changes to predict which at-risk individuals are likely to become ill. This study will help elucidate early clinical and biological markers of bipolar disorder.
Non-invasive Detection Of Hypoglycaemia In People With Diabetes Using Brain Wave Activity
Funder
National Health and Medical Research Council
Funding Amount
$330,447.00
Summary
Hypoglycaemia remains a major cause of morbidity and mortality in people with both type 1 diabetes and type 2 diabetes who require insulin therapy. Current treatments for nocturnal hypoglycaemia are usually ineffective. Combining brain wave recording and artificial intelligence, we will identify the changes that precipitate an episode of hypoglycaemia allowing the development of a non-invasive device to prevent or alleviate these fearful and potentially life-threatening events.