PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Correlation Based Multivariate Analysis of the Genetic Influence on Brain Volume
David Hardoon, Ulrich Ettinger, Janaina Mourao-Miranda, Elena Antonova, David Collier, Veena Kumari, Steven Williams and Michael Brammer
(2008) Technical Report. University College London.

Abstract

Considerable research effort has focused on achieving a better un- derstanding of the genetic correlates of individual differences in vol- umetric and morphological brain measures. The importance of these efforts is underlined by evidence suggesting that brain changes in a number of neuropsychiatric disorders are at least partly genetic in origin. The currently used methods to study these relationships are mostly based on single-genotype univariate analysis techniques. These methods are limited as multiple genes are likely to interact with each other in their influences on brain structure and function. In this paper we present a feasibility study where we show that by using kernel cor- relation analysis, with a new genotypes representation, it is possible to analyse the relative associations of several genetic polymorphisms interaction with brain structure. The implementation of the method is demonstrated on genetic and structural magnetic resonance imag- ing data acquired from a group of 16 healthy sub jects by showing the multivariate genetic influence on grey and white matter.

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EPrint Type:Monograph (Technical Report)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:4158
Deposited By:David Hardoon
Deposited On:09 August 2008