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
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
Risky choices: From cells and circuits to computations and behaviour. This project aims to ask and answer fundamental questions about how we safely make risky decisions to guide our behaviour. It combines theoretically driven approaches from experimental psychology with state-of-the-art technology for mapping and manipulating brain function. The project expects to show, with unprecedented behavioural, brain cell type, and circuit precision, how we safely make choices, how these choices are shape ....Risky choices: From cells and circuits to computations and behaviour. This project aims to ask and answer fundamental questions about how we safely make risky decisions to guide our behaviour. It combines theoretically driven approaches from experimental psychology with state-of-the-art technology for mapping and manipulating brain function. The project expects to show, with unprecedented behavioural, brain cell type, and circuit precision, how we safely make choices, how these choices are shaped by experience, and how controlling these cells and circuits controls choice. This outcome should provide significant benefits including a new knowledge base bridging behavioural, cognitive, and neural sciences to advance theories of behaviour and laying a new basic science platform to understand impulsive behaviours.Read moreRead less
Decoding the brain network of memory formation. This project aims to uncover how the brain network supports the formation of long-lasting memory using cutting-edge imaging, intervention and computational modelling. The project is anticipated to generate new knowledge of the neural activity and circuitry that facilitate memory formation, and targets for modulating network activity and behaviour. This will have significant benefits for neuroscience, engineering and imaging, as well as future appli ....Decoding the brain network of memory formation. This project aims to uncover how the brain network supports the formation of long-lasting memory using cutting-edge imaging, intervention and computational modelling. The project is anticipated to generate new knowledge of the neural activity and circuitry that facilitate memory formation, and targets for modulating network activity and behaviour. This will have significant benefits for neuroscience, engineering and imaging, as well as future applications in humans with technology for detecting, predicting and modulating cognitive performance.Read moreRead less
Neurochemical predictors of cognition and the impact of brain stimulation. This project aims to determine how neurochemical equilibrium between excitation and inhibition (E/I balance), across the brain, is associated with executive function and how this balance is influenced by non-invasive brain stimulation. Brain stimulation shows immense promise for enhancing executive function in applied settings, but the neurochemical basis for this is unknown. Using advanced imaging and stimulation techniq ....Neurochemical predictors of cognition and the impact of brain stimulation. This project aims to determine how neurochemical equilibrium between excitation and inhibition (E/I balance), across the brain, is associated with executive function and how this balance is influenced by non-invasive brain stimulation. Brain stimulation shows immense promise for enhancing executive function in applied settings, but the neurochemical basis for this is unknown. Using advanced imaging and stimulation techniques, the project aims to provide comprehensive insights into the causal relationship between stimulation, E/I balance and executive function. Outcomes and benefits include identifying neurochemical characteristics that determine stimulation efficacy and informing the design of protocols for applied use.Read moreRead less
How the brain learns and uses inhibitory predictions. Humans and other animals readily learn about cues and actions that predict the absence of important events. Yet, how and where such inhibitory predictions are processed in the mammalian brain remains unclear. This project aims to demonstrate that inhibitory predictions are generally encoded and retrieved in the medial prefrontal cortex, without any detailed information about the absent events. It combines a unique behavioural approach with th ....How the brain learns and uses inhibitory predictions. Humans and other animals readily learn about cues and actions that predict the absence of important events. Yet, how and where such inhibitory predictions are processed in the mammalian brain remains unclear. This project aims to demonstrate that inhibitory predictions are generally encoded and retrieved in the medial prefrontal cortex, without any detailed information about the absent events. It combines a unique behavioural approach with the latest tools for manipulation of brain activity in behaving rodents. The project expects to generate new insights into how the mammalian brain extracts inhibitory predictions from the environment to guide our behaviours and decisions in the most optimal way.Read moreRead less