MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images-Reference-Cited by-同舟云学术

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images

Published:2014-01 Issue: Volume:84 Page:585-604
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Huang Ming-Xiong,Huang Charles W.,Robb Ashley,Angeles AnneMarie,Nichols Sharon L.,Baker Dewleen G.,Song Tao,Harrington Deborah L.,Theilmann Rebecca J.,Srinivasan Ramesh,Heister David,Diwakar Mithun,Canive Jose M.,Edgar J. Christopher,Chen Yu-Han,Ji Zhengwei,Shen Max,El-Gabalawy Fady,Levy Michael,McLay Robert,Webb-Murphy Jennifer,Liu Thomas T.,Drake Angela,Lee Roland R.

Funder

Department of Veterans Affairs

National Institute of Health Grants

National Football League Grant

McDonnell Foundation Grant

Brain Trauma Foundation

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference81 articles.

1. Multistart algorithms for MEG empirical data analysis reliably characterize locations and time courses of multiple sources;Aine;NeuroImage,2000