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Results: 1 to 20 of 101

Similar articles for PubMed (Select 24443693)

1.

IDENTIFYING PATTERNS IN TEMPORAL VARIATION OF FUNCTIONAL CONNECTIVITY USING RESTING STATE FMRI.

Eavani H, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C.

Proc IEEE Int Symp Biomed Imaging. 2013 Dec 31;2013:1086-1089.

2.

Unsupervised learning of functional network dynamics in resting state fMRI.

Eavani H, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C.

Inf Process Med Imaging. 2013;23:426-37.

3.

Sparse dictionary learning of resting state fMRI networks.

Eavani H, Filipovych R, Davatzikos C, Satterthwaite TD, Gur RE, Gur RC.

Int Workshop Pattern Recognit Neuroimaging. 2012 Jul 2:73-76.

4.

Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study.

Klumpers LE, Cole DM, Khalili-Mahani N, Soeter RP, Te Beek ET, Rombouts SA, van Gerven JM.

Neuroimage. 2012 Nov 15;63(3):1701-11. doi: 10.1016/j.neuroimage.2012.07.051. Epub 2012 Aug 1.

PMID:
22885247
5.

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. 2015 Jun 28. [Epub ahead of print]

PMID:
26123390
6.

Whole brain resting state functional connectivity abnormalities in schizophrenia.

Venkataraman A, Whitford TJ, Westin CF, Golland P, Kubicki M.

Schizophr Res. 2012 Aug;139(1-3):7-12. doi: 10.1016/j.schres.2012.04.021. Epub 2012 May 26.

7.

Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks.

Karahanoğlu FI, Van De Ville D.

Nat Commun. 2015 Jul 16;6:7751. doi: 10.1038/ncomms8751.

PMID:
26178017
8.

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task.

Ciuciu P, Varoquaux G, Abry P, Sadaghiani S, Kleinschmidt A.

Front Physiol. 2012 Jun 15;3:186. doi: 10.3389/fphys.2012.00186. eCollection 2012.

9.

Identifying Sparse Connectivity Patterns in the brain using resting-state fMRI.

Eavani H, Satterthwaite TD, Filipovych R, Gur RE, Gur RC, Davatzikos C.

Neuroimage. 2015 Jan 15;105:286-99. doi: 10.1016/j.neuroimage.2014.09.058. Epub 2014 Oct 2.

PMID:
25284301
10.

The spatial structure of resting state connectivity stability on the scale of minutes.

Gonzalez-Castillo J, Handwerker DA, Robinson ME, Hoy CW, Buchanan LC, Saad ZS, Bandettini PA.

Front Neurosci. 2014 Jun 11;8:138. doi: 10.3389/fnins.2014.00138. eCollection 2014.

11.

Brain connectivity during resting state and subsequent working memory task predicts behavioural performance.

Sala-Llonch R, Peña-Gómez C, Arenaza-Urquijo EM, Vidal-Piñeiro D, Bargalló N, Junqué C, Bartrés-Faz D.

Cortex. 2012 Oct;48(9):1187-96. doi: 10.1016/j.cortex.2011.07.006. Epub 2011 Aug 5.

PMID:
21872853
12.

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 Jul 8. pii: S1053-8119(15)00609-6. doi: 10.1016/j.neuroimage.2015.07.002. [Epub ahead of print]

PMID:
26162552
13.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

Lv J, Jiang X, Li X, Zhu D, Chen H, Zhang T, Zhang S, Hu X, Han J, Huang H, Zhang J, Guo L, Liu T.

Med Image Anal. 2015 Feb;20(1):112-34. doi: 10.1016/j.media.2014.10.011. Epub 2014 Nov 8.

PMID:
25476415
14.

Metabolic brain covariant networks as revealed by FDG-PET with reference to resting-state fMRI networks.

Di X, Biswal BB; Alzheimer's Disease Neuroimaging Initiative.

Brain Connect. 2012;2(5):275-83. doi: 10.1089/brain.2012.0086.

15.

State-dependent differences between functional and effective connectivity of the human cortical motor system.

Rehme AK, Eickhoff SB, Grefkes C.

Neuroimage. 2013 Feb 15;67:237-46. doi: 10.1016/j.neuroimage.2012.11.027. Epub 2012 Nov 29.

PMID:
23201364
16.

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.

17.

Investigating the neural basis for fMRI-based functional connectivity in a blocked design: application to interregional correlations and psycho-physiological interactions.

Kim J, Horwitz B.

Magn Reson Imaging. 2008 Jun;26(5):583-93. doi: 10.1016/j.mri.2007.10.011. Epub 2008 Jan 10.

PMID:
18191524
18.

A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data.

Wu GR, Liao W, Stramaglia S, Ding JR, Chen H, Marinazzo D.

Med Image Anal. 2013 Apr;17(3):365-74. doi: 10.1016/j.media.2013.01.003. Epub 2013 Jan 29.

PMID:
23422254
19.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

Córdova-Palomera A, Tornador C, Falcón C, Bargalló N, Nenadic I, Deco G, Fañanás L.

Hum Brain Mapp. 2015 Jun 19. doi: 10.1002/hbm.22876. [Epub ahead of print]

PMID:
26096943
20.

Non-invasive electrical stimulation of the brain (ESB) modifies the resting-state network connectivity of the primary motor cortex: a proof of concept fMRI study.

Alon G, Roys SR, Gullapalli RP, Greenspan JD.

Brain Res. 2011 Jul 27;1403:37-44. doi: 10.1016/j.brainres.2011.06.013. Epub 2011 Jun 13.

PMID:
21696709
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