PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

KCCA for fMRI Analysis
David Hardoon, John Shawe-Taylor and Ola Friman
In: The Medical Image Understanding and Analysis conference (MIUA) 2004, 23-24 September 2004, London, UK.


Understanding the functional processes of the brain is still a new and difficult task. Functional Magnetic Resonance Imaging (fMRI) is a relatively new tool with the purpose of mapping the sensor, motor and cognitive tasks to specific regions in the brain. We present a Kernel Canonical Correlation Analysis (KCCA) approach to measure the active regions of the brain using fMRI scans and their activity signal.

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EPrint Type:Conference or Workshop Item (Poster)
Additional Information:This is the abstract page submitted to the meeting. The proceedings version (4 pages) will be entered to the eprints separately.
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:239
Deposited By:David Hardoon
Deposited On:23 November 2004