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Items: 1 to 20 of 100

1.

Spatiotemporal Empirical Mode Decomposition of Resting-State fMRI Signals: Application to Global Signal Regression.

Moradi N, Dousty M, Sotero RC.

Front Neurosci. 2019 Jul 23;13:736. doi: 10.3389/fnins.2019.00736. eCollection 2019.

2.

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

Erdoğan SB, Tong Y, Hocke LM, Lindsey KP, deB Frederick B.

Front Hum Neurosci. 2016 Jun 28;10:311. doi: 10.3389/fnhum.2016.00311. eCollection 2016.

3.

Global signal regression acts as a temporal downweighting process in resting-state fMRI.

Nalci A, Rao BD, Liu TT.

Neuroimage. 2017 May 15;152:602-618. doi: 10.1016/j.neuroimage.2017.01.015. Epub 2017 Jan 9.

PMID:
28089677
4.

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

Carbonell F, Bellec P, Shmuel A.

Neuroimage. 2014 Feb 1;86:343-53. doi: 10.1016/j.neuroimage.2013.10.013. Epub 2013 Oct 12.

PMID:
24128734
5.

Resting state networks in empirical and simulated dynamic functional connectivity.

Glomb K, Ponce-Alvarez A, Gilson M, Ritter P, Deco G.

Neuroimage. 2017 Oct 1;159:388-402. doi: 10.1016/j.neuroimage.2017.07.065. Epub 2017 Aug 3.

PMID:
28782678
6.

Advances in functional magnetic resonance imaging data analysis methods using Empirical Mode Decomposition to investigate temporal changes in early Parkinson's disease.

Cordes D, Zhuang X, Kaleem M, Sreenivasan K, Yang Z, Mishra V, Banks SJ, Bluett B, Cummings JL.

Alzheimers Dement (N Y). 2018 Jun 14;4:372-386. doi: 10.1016/j.trci.2018.04.009. eCollection 2018.

7.

Structurofunctional resting-state networks correlate with motor function in chronic stroke.

Kalinosky BT, Berrios Barillas R, Schmit BD.

Neuroimage Clin. 2017 Jul 29;16:610-623. doi: 10.1016/j.nicl.2017.07.002. eCollection 2017.

8.

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA.

Neuroimage. 2009 Feb 1;44(3):893-905. doi: 10.1016/j.neuroimage.2008.09.036. Epub 2008 Oct 11.

9.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

Carbonell F, Bellec P, Shmuel A.

Brain Connect. 2011;1(6):496-510. doi: 10.1089/brain.2011.0065. Epub 2012 Mar 23.

10.

Functional connectivity in BOLD and CBF data: similarity and reliability of resting brain networks.

Jann K, Gee DG, Kilroy E, Schwab S, Smith RX, Cannon TD, Wang DJ.

Neuroimage. 2015 Feb 1;106:111-22. doi: 10.1016/j.neuroimage.2014.11.028. Epub 2014 Nov 21.

11.

Estimation of resting-state functional connectivity using random subspace based partial correlation: a novel method for reducing global artifacts.

Chen T, Ryali S, Qin S, Menon V.

Neuroimage. 2013 Nov 15;82:87-100. doi: 10.1016/j.neuroimage.2013.05.118. Epub 2013 Jun 5.

12.

How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

Andoh J, Ferreira M, Leppert IR, Matsushita R, Pike B, Zatorre RJ.

Neuroimage. 2017 Feb 15;147:726-735. doi: 10.1016/j.neuroimage.2016.11.065. Epub 2016 Nov 27.

PMID:
27902936
13.

Effects of model-based physiological noise correction on default mode network anti-correlations and correlations.

Chang C, Glover GH.

Neuroimage. 2009 Oct 1;47(4):1448-59. doi: 10.1016/j.neuroimage.2009.05.012. Epub 2009 May 14.

14.

Anticorrelations in resting state networks without global signal regression.

Chai XJ, Castañón AN, Ongür D, Whitfield-Gabrieli S.

Neuroimage. 2012 Jan 16;59(2):1420-8. doi: 10.1016/j.neuroimage.2011.08.048. Epub 2011 Aug 26.

15.

Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

DSouza AM, Abidin AZ, Leistritz L, Wismüller A.

J Neurosci Methods. 2017 Aug 1;287:68-79. doi: 10.1016/j.jneumeth.2017.06.007. Epub 2017 Jun 16.

16.

Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome.

Zöller D, Schaer M, Scariati E, Padula MC, Eliez S, Van De Ville D.

Neuroimage. 2017 Apr 1;149:85-97. doi: 10.1016/j.neuroimage.2017.01.064. Epub 2017 Jan 29.

PMID:
28143774
17.

Altered resting-state connectivity in Huntington's disease.

Werner CJ, Dogan I, Saß C, Mirzazade S, Schiefer J, Shah NJ, Schulz JB, Reetz K.

Hum Brain Mapp. 2014 Jun;35(6):2582-93. doi: 10.1002/hbm.22351. Epub 2013 Aug 24.

PMID:
23982979
18.

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

Cheng L, Zhu Y, Sun J, Deng L, He N, Yang Y, Ling H, Ayaz H, Fu Y, Tong S.

Int J Neural Syst. 2018 Sep;28(7):1850002. doi: 10.1142/S0129065718500028. Epub 2018 Jan 25.

PMID:
29607681
19.

Sensitivity enhancement of task-evoked fMRI using ensemble empirical mode decomposition.

Lin SH, Lin GH, Tsai PJ, Hsu AL, Lo MT, Yang AC, Lin CP, Wu CW.

J Neurosci Methods. 2016 Jan 30;258:56-66. doi: 10.1016/j.jneumeth.2015.10.009. Epub 2015 Oct 30.

PMID:
26523767
20.

An empirical Bayes normalization method for connectivity metrics in resting state fMRI.

Chen S, Kang J, Wang G.

Front Neurosci. 2015 Sep 16;9:316. doi: 10.3389/fnins.2015.00316. eCollection 2015.

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