Details of Grant 

EPSRC Reference:	GR/T02669/01
Title:	Probabilistic Brain Connectivity Mapping
Principal Investigator:	Parker, Professor GJM
Other Investigators:
Researcher Co-Investigators:
Project Partners:	UCL
Department:	Medical and Human Sciences
Organisation:	University of Manchester, The
Scheme:	First Grant Scheme Pre-FEC
Starts:	21 February 2005	Ends:	20 February 2008	Value (£):	124,952
EPSRC Research Topic Classifications:	Biomedical neuroscience Image & Vision Computing Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:	Healthcare Information Technologies
Related Grants:
Panel History:
Summary on Grant Application Form
Statistical methods for examining the routes of connection within the living brain using diffusion weighted magnetic resonance imaging (MRI) have recently been introduced. These methods form a framework for assigning confidence to identified connections, thus promising quantitative assessment of brain connections. However, the quantitative basis for available methods is currently lacking. There is a void between applied models of fibre tract orientation and the relationship between the acquired MRI signal and the measured information, especially in circumstances where more than one fibre tract is present in an imaging voxel. This work proposed at the University of Manchester will address these problems by focussing on the definition of more realistic probability density functions for use in probabilistic fibre tracking and methods for application to whole-brain population connectivity analyses. In addition to such fundamental issues, there is a lack of statistical fibre tracking software available for general use. This will be addressed by the development of efficient, quantitative, and freely available brain connection mapping software. Steps in the project will include the development of portable code in collaboration with Dr Daniel Alexander of University College London, the establishment of statistical whole-brain fibre tracking algorithms, and the dissemination of resulting code and novel findings. This project, at a cost of approximately 120,000, will provide novel methods and software tools whilst also demonstrating initial application; it therefore fits well with the EPSRC Life Sciences Interface Programme.
Key Findings
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Potential use in non-academic contexts
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Further Information:
Organisation Website:	http://www.man.ac.uk