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Items: 1 to 20 of 182


Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination.

Shirer WR, Jiang H, Price CM, Ng B, Greicius MD.

Neuroimage. 2015 Aug 15;117:67-79. doi: 10.1016/j.neuroimage.2015.05.015. Epub 2015 May 15.


Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.

Bright MG, Murphy K.

Neuroimage. 2015 Jul 1;114:158-69. doi: 10.1016/j.neuroimage.2015.03.070. Epub 2015 Apr 7.


Using Edge Voxel Information to Improve Motion Regression for rs-fMRI Connectivity Studies.

Patriat R, Molloy EK, Birn RM.

Brain Connect. 2015 Nov;5(9):582-95. doi: 10.1089/brain.2014.0321. Epub 2015 Sep 28.


Reduction of motion-related artifacts in resting state fMRI using aCompCor.

Muschelli J, Nebel MB, Caffo BS, Barber AD, Pekar JJ, Mostofsky SH.

Neuroimage. 2014 Aug 1;96:22-35. doi: 10.1016/j.neuroimage.2014.03.028. Epub 2014 Mar 18.


A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

Patel AX, Kundu P, Rubinov M, Jones PS, Vértes PE, Ersche KD, Suckling J, Bullmore ET.

Neuroimage. 2014 Jul 15;95:287-304. doi: 10.1016/j.neuroimage.2014.03.012. Epub 2014 Mar 21.


Functional connectivity in the rat at 11.7T: Impact of physiological noise in resting state fMRI.

Kalthoff D, Seehafer JU, Po C, Wiedermann D, Hoehn M.

Neuroimage. 2011 Feb 14;54(4):2828-39. doi: 10.1016/j.neuroimage.2010.10.053. Epub 2010 Oct 23.


Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR).

Wong CK, Zotev V, Misaki M, Phillips R, Luo Q, Bodurka J.

Neuroimage. 2016 Apr 1;129:133-147. doi: 10.1016/j.neuroimage.2016.01.042. Epub 2016 Jan 27.


Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI.

Pruim RH, Mennes M, Buitelaar JK, Beckmann CF.

Neuroimage. 2015 May 15;112:278-87. doi: 10.1016/j.neuroimage.2015.02.063. Epub 2015 Mar 11.


An improved model of motion-related signal changes in fMRI.

Patriat R, Reynolds RC, Birn RM.

Neuroimage. 2017 Jan 1;144(Pt A):74-82. doi: 10.1016/j.neuroimage.2016.08.051. Epub 2016 Aug 25.


Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI.

Spisák T, Jakab A, Kis SA, Opposits G, Aranyi C, Berényi E, Emri M.

PLoS One. 2014 Sep 4;9(9):e104947. doi: 10.1371/journal.pone.0104947. eCollection 2014.


Removing motion and physiological artifacts from intrinsic BOLD fluctuations using short echo data.

Bright MG, Murphy K.

Neuroimage. 2013 Jan 1;64:526-37. doi: 10.1016/j.neuroimage.2012.09.043. Epub 2012 Sep 21.


Integrated strategy for improving functional connectivity mapping using multiecho fMRI.

Kundu P, Brenowitz ND, Voon V, Worbe Y, Vértes PE, Inati SJ, Saad ZS, Bandettini PA, Bullmore ET.

Proc Natl Acad Sci U S A. 2013 Oct 1;110(40):16187-92. doi: 10.1073/pnas.1301725110. Epub 2013 Sep 13.


The global signal in fMRI: Nuisance or Information?

Liu TT, Nalci A, Falahpour M.

Neuroimage. 2017 Apr 15;150:213-229. doi: 10.1016/j.neuroimage.2017.02.036. Epub 2017 Feb 16.


An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.

Satterthwaite TD, Elliott MA, Gerraty RT, Ruparel K, Loughead J, Calkins ME, Eickhoff SB, Hakonarson H, Gur RC, Gur RE, Wolf DH.

Neuroimage. 2013 Jan 1;64:240-56. doi: 10.1016/j.neuroimage.2012.08.052. Epub 2012 Aug 25.


Head Motion and Correction Methods in Resting-state Functional MRI.

Goto M, Abe O, Miyati T, Yamasue H, Gomi T, Takeda T.

Magn Reson Med Sci. 2016;15(2):178-86. doi: 10.2463/mrms.rev.2015-0060. Epub 2015 Dec 22. Review.


Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy.

Chen JE, Jahanian H, Glover GH.

Brain Connect. 2017 Feb;7(1):13-24. doi: 10.1089/brain.2016.0441. Epub 2017 Jan 5.


Denoising the speaking brain: toward a robust technique for correcting artifact-contaminated fMRI data under severe motion.

Xu Y, Tong Y, Liu S, Chow HM, AbdulSabur NY, Mattay GS, Braun AR.

Neuroimage. 2014 Dec;103:33-47. doi: 10.1016/j.neuroimage.2014.09.013. Epub 2014 Sep 16.


Deconvolution filtering: temporal smoothing revisited.

Bush K, Cisler J.

Magn Reson Imaging. 2014 Jul;32(6):721-35. doi: 10.1016/j.mri.2014.03.002. Epub 2014 Mar 15.


Potential pitfalls when denoising resting state fMRI data using nuisance regression.

Bright MG, Tench CR, Murphy K.

Neuroimage. 2017 Jul 1;154:159-168. doi: 10.1016/j.neuroimage.2016.12.027. Epub 2016 Dec 23.

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