NDLI: Inference of functional connectivity from direct and indirect structural brain connections

Content Provider	IEEE Xplore Digital Library
Author	Deligianni, F. Robinson, E. Beckmann, C.F. Sharp, D. Edwards, A.D. Rueckert, D.
Copyright Year	2011
Description	Author affiliation: Department of Computing, Imperial College London, UK (Deligianni, F.; Robinson, E.; Rueckert, D.) \|\| Clinical Neuroscience Department, Imperial College London, UK (Beckmann, C.F.; Sharp, D.) \|\| Institute of Clinical Sciences, Imperial College London and MRC Clinical Sciences Centre, UK (Edwards, A.D.)
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).
Starting Page	849
Ending Page	852
File Size	266401
Page Count	4
File Format	PDF
ISBN	9781424441273
ISSN	19457928
DOI	10.1109/ISBI.2011.5872537
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Correlation Diffusion tensor imaging Input variables Principal component analysis Predictive models indirect structural connections Brain connectivity rs-fMRI whole-brain connectivity matrices functional connectivity structural connectivity
Content Type	Text
Resource Type	Article

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