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
A new perspective on how we learn motor skills: two adaptation classes? The capacity to adapt and acquire movement skills is essential for success in almost every aspect of our lives. This project will test the idea that there are two fundamentally distinct classes of motor learning processes in the brain that are driven by different error types. Using brain recordings, robotic perturbation of movement, and novel variations of classical learning paradigms, the project aims to reveal the neurocom ....A new perspective on how we learn motor skills: two adaptation classes? The capacity to adapt and acquire movement skills is essential for success in almost every aspect of our lives. This project will test the idea that there are two fundamentally distinct classes of motor learning processes in the brain that are driven by different error types. Using brain recordings, robotic perturbation of movement, and novel variations of classical learning paradigms, the project aims to reveal the neurocomputational properties of these proposed adaptation classes across a range of sensorimotor learning paradigms. The knowledge gained from this project may identify new strategies for adapting movements that are widely applicable to industry, defence, sport, and health.Read moreRead less
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
Discovery Early Career Researcher Award - Grant ID: DE230100049
Funder
Australian Research Council
Funding Amount
$459,030.00
Summary
Towards automated Australian Sign Language translation. This project aims to address the computational modelling of Auslan. The project expects to generate knowledge by creating the largest Auslan dataset, enabling further advancements in this research area. The dataset will also play an essential role in other research fields, e.g., sign linguistics. Expected outcomes include the invention of the first Auslan recogniser and generator capable of distinguishing and synthesising 1000+ signs, repre ....Towards automated Australian Sign Language translation. This project aims to address the computational modelling of Auslan. The project expects to generate knowledge by creating the largest Auslan dataset, enabling further advancements in this research area. The dataset will also play an essential role in other research fields, e.g., sign linguistics. Expected outcomes include the invention of the first Auslan recogniser and generator capable of distinguishing and synthesising 1000+ signs, representing a substantial advancement towards fully automated Auslan translation. This should provide significant benefits for the Australian Deaf community, such as high-quality digital systems for education and communication, resulting in increased quality of life and inclusion in the Australian society.Read moreRead less
Comparative analysis of sensor noise for target detection in dragonfly eyes. Dragonflies hunt tiny prey in the low-light conditions of late dusk, a signal-to-noise problem that challenges any engineered system. Using a comparative approach across dragonfly species, we aim to use novel optical and physiological measures to determine how sensors with noise underlie target-detection, in varying scene brightness. The project outcomes will be a comparative characterisation of signal-to-noise measures ....Comparative analysis of sensor noise for target detection in dragonfly eyes. Dragonflies hunt tiny prey in the low-light conditions of late dusk, a signal-to-noise problem that challenges any engineered system. Using a comparative approach across dragonfly species, we aim to use novel optical and physiological measures to determine how sensors with noise underlie target-detection, in varying scene brightness. The project outcomes will be a comparative characterisation of signal-to-noise measures of dragonfly eye optics (including eye size) and early sensory neurons. We will match detection thresholds with downstream target-detecting neurons and dragonfly behaviour. This will provide insight into signal detection, which is a ubiquitous problem across information processing, computer vision and autonomous systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100380
Funder
Australian Research Council
Funding Amount
$447,683.00
Summary
The dynamics of object representations in the human brain. The human brain's ability to effortlessly recognise and categorise objects enables effective behavioural responses in complex everyday environments. Despite the apparent efficiency of this process, it is still unknown how the brain solves object recognition. This project capitalises on cutting-edge advances in artificial intelligence and neuroscience to resolve the spatiotemporal dynamics of object processing in the human brain. The outc ....The dynamics of object representations in the human brain. The human brain's ability to effortlessly recognise and categorise objects enables effective behavioural responses in complex everyday environments. Despite the apparent efficiency of this process, it is still unknown how the brain solves object recognition. This project capitalises on cutting-edge advances in artificial intelligence and neuroscience to resolve the spatiotemporal dynamics of object processing in the human brain. The outcomes will be a step change in our understanding of the nature and development of the multi-dimensional space underpinning neural object processing. This will ultimately facilitate the diagnosis and treatment of brain disorders across the lifespan and accelerate the development of intelligent machines.Read moreRead less