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
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
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.
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
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
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
Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an in ....Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an increased understanding of neural mechanisms underlying sensory selectivity, the development of novel techniques, and enhanced capacity for interdisciplinary collaborations. The project will provide significant knowledge as the developed biomimetic algorithms should be applicable for increased performance in drones or other unmanned vehicles.Read moreRead less
How does timing affect mammalian brain development and evolution? This project aims to generate fundamental knowledge on the origin of diversity in mammalian brain circuits by studying development of marsupials and rodents. The expected outcome is to elucidate how differences in the timing, rate and sequence of development of gene expression, cell differentiation and circuit formation can relate to the origin of key evolutionary innovations in the mammalian brain. The significance of understandi ....How does timing affect mammalian brain development and evolution? This project aims to generate fundamental knowledge on the origin of diversity in mammalian brain circuits by studying development of marsupials and rodents. The expected outcome is to elucidate how differences in the timing, rate and sequence of development of gene expression, cell differentiation and circuit formation can relate to the origin of key evolutionary innovations in the mammalian brain. The significance of understanding the dynamics of developmental systems that shape complex brain traits includes establishing new developmental paradigms in evolutionary theory, generating new tools to investigate and manipulate brain gene expression in vivo, and the potential discovery of the causes of neurodevelopmental dysfunction.Read moreRead less
Cellular bases of enteric neural circuitry underlying gut propulsion. This project aims to investigate the neural bases of behaviour in the mammalian gut. The Enteric Nervous System (ENS) plays a critical role in the propulsion of intestinal contents. This project expects to establish how specific functional classes of enteric neurons control propulsion along the gut. By recording the simultaneous neural activity from hundreds of different functional classes of enteric nerve cells simultaneously ....Cellular bases of enteric neural circuitry underlying gut propulsion. This project aims to investigate the neural bases of behaviour in the mammalian gut. The Enteric Nervous System (ENS) plays a critical role in the propulsion of intestinal contents. This project expects to establish how specific functional classes of enteric neurons control propulsion along the gut. By recording the simultaneous neural activity from hundreds of different functional classes of enteric nerve cells simultaneously, whilst recording intestinal muscle electrical activity and the movements of the gut wall, the project expects to identify which enteric neurochemical classes of neurons generate specific motor patterns along the intestine.Read moreRead less
Target detection in visual clutter. The interdisciplinary nature of the project will offer a stimulating environment for training a postdoctoral worker in the hot topic of computational neuroscience. While computationally expensive solutions to moving target detection in clutter have been implemented using conventional engineering, this project will offer insight into the efficiency of the biological brain (with benefit of millions of years of evolution towards compact, economical and optimal so ....Target detection in visual clutter. The interdisciplinary nature of the project will offer a stimulating environment for training a postdoctoral worker in the hot topic of computational neuroscience. While computationally expensive solutions to moving target detection in clutter have been implemented using conventional engineering, this project will offer insight into the efficiency of the biological brain (with benefit of millions of years of evolution towards compact, economical and optimal solutions). The results will assist development of efficient artificial intelligence. It will also assist our ongoing collaborations with defence partners to develop and apply algorithms in artificial vision systems. Read moreRead less