Inference of Functional Connectivity From Direct and Indirect Structural Brain Connections

Deligianni, F. , Robinson, E., Beckmann, C. F., Sharp, D., Edwards, A. D. and Rueckert, D. (2011) Inference of Functional Connectivity From Direct and Indirect Structural Brain Connections. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Chicago, IL, USA, 30 Mar - 02 Apr 2011, pp. 849-852. ISBN 9781424441273 (doi:10.1109/ISBI.2011.5872537)

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Abstract

We propose statistical inference based on the Least Absolute Shrinkage and Selective Operator (Lasso) regression as a framework to investigate the relationship between structural brain connectivity data (DTI) and functional connectivity data (fMRI). Regions of interest (ROIs) are obtained from an accurate atlas-based segmentation. We use direct structural connections to model indirect (higher-order) structural connectivity. Subsequently, we use Lasso to associate each functional connection with a subset of structural connections. Lasso offers the advantage of simultaneous dimensionality reduction and variable selection. We use a cohort of 22 subjects with both resting-state fMRI and DTI and we provide both qualitative and quantitative results based on leave-one-out cross validation. The results demonstrate that the performance of prediction is enhanced through the incorporation of indirect connections. In fact, the mean explained variance was improved from 54%±6.53 to 58%±4.31 when indirect connections of up to second order are added and the improvement in performance was statistically significant (p <; 0.05).

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Deligianni, Dr Fani
Authors: Deligianni, F., Robinson, E., Beckmann, C. F., Sharp, D., Edwards, A. D., and Rueckert, D.
College/School:College of Science and Engineering > School of Computing Science
ISSN:1945-8452
ISBN:9781424441273
Published Online:09 June 2011

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