Establishing The Physiological And Sleep Disruption Characteristics Of Wind Farm Versus Traffic Noise Disturbances In Sleep
Funder
National Health and Medical Research Council
Funding Amount
$1,357,652.00
Summary
Good sleep is essential for normal daytime functioning and health. Wind farm noise includes audible and unusually low frequency sound components, including infrasound, that could potentially disturb sleep through chronic sleep disruption and/or insomnia. This project will, for the first time, directly evaluate the sleep and physiological disturbance characteristics of wind farm noise compared to traffic noise reproduced in a specialised and carefully controlled laboratory environment.
Target detection in three-dimensional optic flow. This project aims to understand the behavioural, neural, and computational mechanisms underlying the visualisation of moving targets. Insects have poorer eyesight and smaller brains than humans, but can chase small targets at high speed. This project will use intracellular electrophysiology, information content analysis and model development to decipher the underlying neural tuning mechanisms of hoverflies, which could suggest advanced computatio ....Target detection in three-dimensional optic flow. This project aims to understand the behavioural, neural, and computational mechanisms underlying the visualisation of moving targets. Insects have poorer eyesight and smaller brains than humans, but can chase small targets at high speed. This project will use intracellular electrophysiology, information content analysis and model development to decipher the underlying neural tuning mechanisms of hoverflies, which could suggest advanced computational optimisation and miniaturisation. The project may generate algorithms for rapid and reliable information extraction from large, noisy inputs, useful for developing unmanned vehicles and in Big Data analysis. The results could be useful in developing anti-collision control systems in vehicles using less computational power.Read moreRead less
Neural mechanisms for visual target detection and attention in complex scenes. This project will study neurons in the insect brain that solve one of the biggest problems for computer vision systems - tracking the motion of tiny targets moving against strongly camouflaged backgrounds. The results will be used to develop a novel biologically inspired model for target tracking with applications for smart cameras and robotics.
Strategies for neural summation in space and time for night vision. This project will study motion vision in nocturnal and day-active insects to understand how the brain sees in darkness, even when individual light sensitive cells in the eye perform poorly. This will help to identify optimal strategies that have evolved in nature to deal with noisy signals in low light and has implications for man-made night cameras.
From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden ....From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100548
Funder
Australian Research Council
Funding Amount
$359,000.00
Summary
Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The p ....Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The project aims to examine how expectation and attention are encoded in the brain and will build an autonomous robot using computational models bio-inspired from this neuronal processing. Robots capable of visually perceiving and interacting with targets in natural environments have applications in health, surveillance and defence.Read moreRead less
Hierarchical information processing in the primate visual cortex. This project aims to understand how visual information is transformed across hierarchical levels in the brain. Neuroscientists have long recognised that the visual cortex can be conceptualised as a hierarchical processing network. This became apparent when learning algorithms based on hierarchical networks ("deep learning") changed artificial intelligence. This project will combine high-throughput electrophysiology with analytical ....Hierarchical information processing in the primate visual cortex. This project aims to understand how visual information is transformed across hierarchical levels in the brain. Neuroscientists have long recognised that the visual cortex can be conceptualised as a hierarchical processing network. This became apparent when learning algorithms based on hierarchical networks ("deep learning") changed artificial intelligence. This project will combine high-throughput electrophysiology with analytical tools adopted from deep learning. By explaining the physiological properties of higher-level neurons in terms of hierarchical networks, the project expects to address long standing questions in neuroscience, and provide insights on biological hierarchical computation.Read moreRead less