Title :
A voxel selection method for the multivariate analysis of imaging genetics data
Author :
Seo, Sambu ; Mohr, Johannes ; Heekeren, Hauke ; Heinz, Andreas ; Eppinger, Ben ; Li, Shu-Chen ; Obermayer, Klaus
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Berlin Inst. of Technol., Berlin, Germany
Abstract :
We suggest a multivariate genotype-phenotype association test for functional magnetic resonance imaging (fMRI) data. The method uses a voxel selection and ranking scheme based on iterative adaptive Lasso for defining a functional region of interest. A classifier-based test is used to assess the significance of potential associations between the differential activity pattern within that region and a set of candidate genetic variants. We applied the method to a small sample dataset from an ongoing imaging genetics study and identified a significant genetic association to a stimulus-locked imaging phenotype.
Keywords :
biomedical MRI; genetics; image classification; iterative methods; medical image processing; candidate genetic variants; classifier-based test; differential activity pattern; fMRI data; functional magnetic resonance imaging data; functional region of interest; genetic association; imaging genetics data; iterative adaptive Lasso; multivariate analysis; multivariate genotype-phenotype association test; potential associations; ranking scheme; sample dataset; stimulus-locked imaging phenotype; voxel selection method; Algorithm design and analysis; Genetics; Imaging; Markov processes; Prediction algorithms; Testing; Training;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252766