Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 101

1.

Sliding window correlation analysis: Modulating window shape for dynamic brain connectivity in resting state.

Mokhtari F, Akhlaghi MI, Simpson SL, Wu G, Laurienti PJ.

Neuroimage. 2019 Feb 2;189:655-666. doi: 10.1016/j.neuroimage.2019.02.001. [Epub ahead of print]

PMID:
30721750
2.

Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states.

Shakil S, Lee CH, Keilholz SD.

Neuroimage. 2016 Jun;133:111-128. doi: 10.1016/j.neuroimage.2016.02.074. Epub 2016 Mar 4.

3.

An average sliding window correlation method for dynamic functional connectivity.

Vergara VM, Abrol A, Calhoun VD.

Hum Brain Mapp. 2019 Jan 19. doi: 10.1002/hbm.24509. [Epub ahead of print]

PMID:
30659699
4.

On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis.

Pedersen M, Omidvarnia A, Zalesky A, Jackson GD.

Neuroimage. 2018 Nov 1;181:85-94. doi: 10.1016/j.neuroimage.2018.06.020. Epub 2018 Jun 15.

PMID:
29890326
5.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

Sojoudi A, Goodyear BG.

Hum Brain Mapp. 2016 Dec;37(12):4566-4580. doi: 10.1002/hbm.23329. Epub 2016 Jul 28.

PMID:
27464464
6.

Realistic models of apparent dynamic changes in resting-state connectivity in somatosensory cortex.

Shi Z, Rogers BP, Chen LM, Morgan VL, Mishra A, Wilkes DM, Gore JC.

Hum Brain Mapp. 2016 Nov;37(11):3897-3910. doi: 10.1002/hbm.23284.

7.

Impact of global signal regression on characterizing dynamic functional connectivity and brain states.

Xu H, Su J, Qin J, Li M, Zeng LL, Hu D, Shen H.

Neuroimage. 2018 Jun;173:127-145. doi: 10.1016/j.neuroimage.2018.02.036. Epub 2018 Feb 21.

PMID:
29476914
8.

Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification.

Wee CY, Yang S, Yap PT, Shen D; Alzheimer’s Disease Neuroimaging Initiative.

Brain Imaging Behav. 2016 Jun;10(2):342-56. doi: 10.1007/s11682-015-9408-2.

9.

Dynamic regional phase synchrony (DRePS): An Instantaneous Measure of Local fMRI Connectivity Within Spatially Clustered Brain Areas.

Omidvarnia A, Pedersen M, Walz JM, Vaughan DN, Abbott DF, Jackson GD.

Hum Brain Mapp. 2016 May;37(5):1970-85. doi: 10.1002/hbm.23151. Epub 2016 Mar 28.

PMID:
27019380
10.

Sliding-window analysis tracks fluctuations in amygdala functional connectivity associated with physiological arousal and vigilance during fear conditioning.

Baczkowski BM, Johnstone T, Walter H, Erk S, Veer IM.

Neuroimage. 2017 Jun;153:168-178. doi: 10.1016/j.neuroimage.2017.03.022. Epub 2017 Mar 12.

PMID:
28300639
11.

On applicability of PCA, voxel-wise variance normalization and dimensionality assumptions for sliding temporal window sICA in resting-state fMRI.

Remes JJ, Abou Elseoud A, Ollila E, Haapea M, Starck T, Nikkinen J, Tervonen O, Silven O.

Magn Reson Imaging. 2013 Oct;31(8):1338-48. doi: 10.1016/j.mri.2013.06.002. Epub 2013 Jul 8.

PMID:
23845397
12.

Reveal Consistent Spatial-Temporal Patterns from Dynamic Functional Connectivity for Autism Spectrum Disorder Identification.

Zhu Y, Zhu X, Zhang H, Gao W, Shen D, Wu G.

Med Image Comput Comput Assist Interv. 2016 Oct;9900:106-114. doi: 10.1007/978-3-319-46720-7_13. Epub 2016 Oct 2.

13.

Dynamic effective connectivity in resting state fMRI.

Park HJ, Friston KJ, Pae C, Park B, Razi A.

Neuroimage. 2018 Oct 15;180(Pt B):594-608. doi: 10.1016/j.neuroimage.2017.11.033. Epub 2017 Nov 20.

14.

Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information.

Xie H, Zheng CY, Handwerker DA, Bandettini PA, Calhoun VD, Mitra S, Gonzalez-Castillo J.

Neuroimage. 2018 Dec 18;188:502-514. doi: 10.1016/j.neuroimage.2018.12.037. [Epub ahead of print]

PMID:
30576850
15.

Capturing Dynamic Connectivity from Resting State fMRI using Time-Varying Graphical Lasso.

Cai B, Zhang G, Zhang A, Stephen JM, Wilson TW, Calhoun VD, Wang Y.

IEEE Trans Biomed Eng. 2018 Nov 9. doi: 10.1109/TBME.2018.2880428. [Epub ahead of print]

PMID:
30418876
16.

Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information.

Yaesoubi M, Allen EA, Miller RL, Calhoun VD.

Neuroimage. 2015 Oct 15;120:133-42. doi: 10.1016/j.neuroimage.2015.07.002. Epub 2015 Jul 8.

17.

Education, and the balance between dynamic and stationary functional connectivity jointly support executive functions in relapsing-remitting multiple sclerosis.

Lin SJ, Vavasour I, Kosaka B, Li DKB, Traboulsee A, MacKay A, McKeown MJ.

Hum Brain Mapp. 2018 Dec;39(12):5039-5049. doi: 10.1002/hbm.24343. Epub 2018 Sep 21.

PMID:
30240533
18.

Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?

Hindriks R, Adhikari MH, Murayama Y, Ganzetti M, Mantini D, Logothetis NK, Deco G.

Neuroimage. 2016 Feb 15;127:242-256. doi: 10.1016/j.neuroimage.2015.11.055. Epub 2015 Nov 26. Erratum in: Neuroimage. 2016 May 15;132:115.

19.

Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure.

Liu F, Wang Y, Li M, Wang W, Li R, Zhang Z, Lu G, Chen H.

Hum Brain Mapp. 2017 Feb;38(2):957-973. doi: 10.1002/hbm.23430. Epub 2016 Oct 11.

PMID:
27726245
20.

Impact of 36 h of total sleep deprivation on resting-state dynamic functional connectivity.

Xu H, Shen H, Wang L, Zhong Q, Lei Y, Yang L, Zeng LL, Zhou Z, Hu D, Yang Z.

Brain Res. 2018 Jun 1;1688:22-32. doi: 10.1016/j.brainres.2017.11.011. Epub 2017 Nov 22.

PMID:
29174693

Supplemental Content

Support Center