| EPSRC Reference: |
EP/J016292/1 |
| Title: |
Robust graph analysis of brain connectivity |
| Principal Investigator: |
Clayden, Dr J |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Institute of Child Health |
| Organisation: |
UCL |
| Scheme: |
Standard Research |
| Starts: |
24 September 2012 |
Ends: |
23 September 2015 |
Value (£): |
348,664
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| EPSRC Research Topic Classifications: |
| Biomedical neuroscience |
Medical Imaging |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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03 Feb 2012
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Engineering Prioritisation Meeting - 3 Feb 2012
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Announced
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Summary on Grant Application Form |
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A broad range of neurological diseases and disorders have been linked with pathological alterations in the connectivity of the brain. However, robust methods for identifying and characterising abnormalities in connectivity, their evolution over time and response to treatments, are lacking; and addressing this omission represents a pressing clinical need. In this proposal we aim to meet this need using novel methods based on medical imaging and graph theory, a well-established mathematical framework with which to describe and characterise interconnected systems. To establish a clear baseline, we will characterise the typical "normal" connectivity network, and model statistically its variability in a healthy population. We will also investigate approaches to classifying graphs into groups, and identify common factors underlying structural and functional connectivity, to be used as new biomarkers. We will use magnetic resonance imaging (MRI) and electroencephalography (EEG) to obtain connectivity information in the living brain; and childhood epilepsy and autism spectrum disorders will be investigated as neurological disorders which can display altered brain connectivity. Our developments will also be applicable to other data which can be represented graphically. This work will provide major novel tools for graph analysis of brain connectivity, thereby driving connectivity network methods towards reliable and routine clinical application. Through our close links with clinical colleagues we will ensure that our developments are well positioned for wide-ranging applicability, elucidating connectivity failures in disease and their recovery with treatment.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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