The neural dynamics of real-time processing in the brain. The aim of this project is to investigate a new model for predictive coding of sensory processing in the brain in which the brain compensates for the time delays in neural transmission by maintaining a real-time temporal alignment of the neural activity. This results in a representation of sensory information that is aligned in time across the cortex, offering a new fundamental principle for how the brain functions in a highly dynamic wor ....The neural dynamics of real-time processing in the brain. The aim of this project is to investigate a new model for predictive coding of sensory processing in the brain in which the brain compensates for the time delays in neural transmission by maintaining a real-time temporal alignment of the neural activity. This results in a representation of sensory information that is aligned in time across the cortex, offering a new fundamental principle for how the brain functions in a highly dynamic world whose outcomes would provide a deeper understanding of brain function. It could also have profound significance for artificial intelligence and brain-inspired technologies, as well as benefit neural sensory prostheses and brain-machine interfaces.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
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
The encoding of friction by tactile mechanoreceptors - the key to fingertip force control during dexterous object manipulation by humans. Unmatched human ability to control the hand so that brittle objects are gently held without slipping, or being crushed by excessive force rely on sophisticated tactile sense in the fingertips. This project will record and analyse signals which human nerves are sending from fingertip receptors to the brain centres controlling hand actions.
Sensory mechanisms underlying human dexterity in object manipulation. This project aims to understand the sensory mechanisms and biomechanics underlying sensory encoding. Tactile sensory information is crucial for controlling grip forces so that delicate objects are held without slipping, or being crushed by excessive force. This project will record signals from single human tactile receptors using microneurography. By modelling the neural data with skin biomechanical events, this project aims t ....Sensory mechanisms underlying human dexterity in object manipulation. This project aims to understand the sensory mechanisms and biomechanics underlying sensory encoding. Tactile sensory information is crucial for controlling grip forces so that delicate objects are held without slipping, or being crushed by excessive force. This project will record signals from single human tactile receptors using microneurography. By modelling the neural data with skin biomechanical events, this project aims to reveal sensory mechanisms underlying the human ability to manipulate objects and use tools. This research could lead to next generation sensory-controlled prosthetics and robotic manipulators.Read moreRead less
Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve s ....Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve speed of operation, and reduce the cost and time of data acquisition and processing. Many applications are expected to benefit from this research including search and rescue, surveillance, security, and defence. The research outcomes are expected to enhance the capabilities of the Australian armed forces, counter-terrorism, police and law-enforcement agencies.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101297
Funder
Australian Research Council
Funding Amount
$429,000.00
Summary
A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the e ....A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the emerging field of biological imaging and to deliver an integrated imaging platform for mapping various tissue microscopic components at the cellular level. Successful outcomes have the potential for commercialisation and will accelerate a range of fundamental science and engineering studies requiring imaging techniques.Read moreRead less
Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi ....Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.Read moreRead less
Perceptually-motivated speech parameters for concurrent coding and noise-robust distributed recognition of human speech for mobile telephony systems. With speech being a simple and natural form of communication, speech recognition technology is being widely used in mobile phones. Nowadays, consumers can interact with remote systems via spoken words. This project will develop remote speech recognition with better accuracy and noise-robustness while using the existing mobile phone infrastructure.
Real-time friction sensing, feedback and control for dexterous prosthetic and robotic manipulation. Prosthetic and robotic hands demonstrate poor dexterity during object manipulation, often dropping objects. Humans rarely allow objects to slip because we can sense when an object is slippery and adjust our grip. Exceptionally little research has been directed at replicating this ability to sense friction. This project aims to enable artificial hands to estimate frictional properties while graspin ....Real-time friction sensing, feedback and control for dexterous prosthetic and robotic manipulation. Prosthetic and robotic hands demonstrate poor dexterity during object manipulation, often dropping objects. Humans rarely allow objects to slip because we can sense when an object is slippery and adjust our grip. Exceptionally little research has been directed at replicating this ability to sense friction. This project aims to enable artificial hands to estimate frictional properties while grasping an object. Non-invasive methods to feed back this frictional information to an amputee will also be investigated. Finally, the friction-sensing system will be used to improve robotic gripper control. The outcomes of this research will significantly advance the fields of prosthetics, telesurgery, and service and manufacturing robotics.Read moreRead less