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Research Topic : MENTAL RETARDATION
Australian State/Territory : VIC
Field of Research : Signal Processing
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  • Funded Activity

    Linkage Projects - Grant ID: LP0776235

    Funder
    Australian Research Council
    Funding Amount
    $223,012.00
    Summary
    Diagnosis of depressive disorder and risk for depression in adolescents using acoustic speech analysis. Depression is the most common mental health problem in young people in Australia. Early diagnosis can minimise the disturbance of typical functioning and development of social and academic skills. Current assessment techniques consume significant time in urgent clinical situations, where an immediate assessment of risk is required. An automatic diagnostic system will provide an important objec .... Diagnosis of depressive disorder and risk for depression in adolescents using acoustic speech analysis. Depression is the most common mental health problem in young people in Australia. Early diagnosis can minimise the disturbance of typical functioning and development of social and academic skills. Current assessment techniques consume significant time in urgent clinical situations, where an immediate assessment of risk is required. An automatic diagnostic system will provide an important objective indicator giving an immediate quantitative assessment of the mental state of a patient. The quantitative measure given by the diagnostic system proposed will give physicians and therapists an improved metric by which they can gauge the effectiveness of various treatments in reducing depression and suicidality.
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    Funded Activity

    Linkage - International - Grant ID: LX0882154

    Funder
    Australian Research Council
    Funding Amount
    $78,648.00
    Summary
    Computational methods for precise reconstruction of white-matter fibre tracts in the human brain using diffusion tensor imaging. One in five Australians will experience a mental illness. This project will facilitate a new method for: (1) brain researchers to advance the fundamental understanding of mental illnesses and brain disorders; (2) medical clinicians to diagnose and assess the growing incidence of mental illness confronting Australia's ageing population, thereby addressing the ageing wel .... Computational methods for precise reconstruction of white-matter fibre tracts in the human brain using diffusion tensor imaging. One in five Australians will experience a mental illness. This project will facilitate a new method for: (1) brain researchers to advance the fundamental understanding of mental illnesses and brain disorders; (2) medical clinicians to diagnose and assess the growing incidence of mental illness confronting Australia's ageing population, thereby addressing the ageing well and ageing productively national research priority; and, (3) neurosurgeons to guide surgery via localisation of major neural tracts. In addition to contributing to the understanding, diagnosis and treatment of Australia's endemic mental health burden, this project will advance Australia's skill-base and international standing in basic scientific research.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200100757

    Funder
    Australian Research Council
    Funding Amount
    $490,877.00
    Summary
    Multiscale and multimodal modelling of brain dynamics. This project aims to understand dynamics of how several brain regions work together to process information. This project will generate new knowledge in brain sciences by using state of the art computational modelling and neuroimaging methods like functional and diffusion magnetic resonance imaging and electromagnetic measurements. This project will develop technologies to compute multiscale, multimodal and directed connectivity in the brain. .... Multiscale and multimodal modelling of brain dynamics. This project aims to understand dynamics of how several brain regions work together to process information. This project will generate new knowledge in brain sciences by using state of the art computational modelling and neuroimaging methods like functional and diffusion magnetic resonance imaging and electromagnetic measurements. This project will develop technologies to compute multiscale, multimodal and directed connectivity in the brain. Expected outcomes of this project will enhance our understanding of the brain’s functional organization and dynamics. The benefits of this project will include breakthroughs in development of new neuro-technologies like brain-machine interfaces and neuroscience inspired artificial intelligence.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE170100128

    Funder
    Australian Research Council
    Funding Amount
    $395,000.00
    Summary
    Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts .... Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts research. This project is expected to advance our understanding of information processing in the brain by providing a mechanistic approach to functional integration.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT130101394

    Funder
    Australian Research Council
    Funding Amount
    $606,740.00
    Summary
    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.
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