@article {792,
	title = {Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI.},
	journal = {Neuroimage},
	volume = {102 Pt 2},
	year = {2014},
	month = {2014 Nov 15},
	pages = {938-44},
	abstract = {<p>Resting-state functional magnetic resonance imaging (rs-fMRI) is used to investigate synchronous activations in spatially distinct regions of the brain, which are thought to reflect functional systems supporting cognitive processes. Analyses are often performed using seed-based correlation analysis, allowing researchers to explore functional connectivity between data in a seed region and the rest of the brain. Using scan-rescan rs-fMRI data, we investigate how well the subject-specific seed-based correlation map from the second replication of the study can be predicted using data from the first replication. We show that one can dramatically improve prediction of subject-specific connectivity by borrowing strength from the group correlation map computed using all other subjects in the study. Even more surprisingly, we found that the group correlation map provided a better prediction of a subject{\textquoteright}s connectivity than the individual{\textquoteright}s own data. While further discussion and experimentation are required to understand how this can be used in practice, results indicate that shrinkage-based methods that borrow strength from the population mean should play a role in rs-fMRI data analysis.</p>},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2014.05.043},
	author = {Shou, Haochang and Eloyan, Ani and Nebel, Mary Beth and Mejia, Amanda and Pekar, James J and Mostofsky, Stewart and Caffo, Brian and Lindquist, Martin A and Crainiceanu, Ciprian M}
}
