@inproceedings{35efb1dc9f9247ab89fa97da60fc6166,
title = "Collaborative denoising of multi-subject fMRI data",
abstract = "We propose a novel collaborative denoising scheme for multi-subject fMRI data. The scheme assumes that subjects experience a common, synchronous stimulus and uses the across-subject shared response structure to jointly denoise each subject's fMRI response along the spatial or voxel domain. Denoising is accomplished by learning subject-specfic orthonormal bases that yield sparse representations in a common transform domain. We provide empirical results using a real-world, multi-subject fMRI dataset.",
keywords = "Procrustes problems, fMRI, principal axes, signal denoising",
author = "Alexander Lorbert and Guntupalli, {J. Swaroop} and Eis, {David J.} and Haxby, {James V.} and Ramadge, {Peter J.}",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6637801",
language = "English (US)",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "1008--1012",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}