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Items: 1 to 20 of 100

1.

A symmetric multivariate leakage correction for MEG connectomes.

Colclough GL, Brookes MJ, Smith SM, Woolrich MW.

Neuroimage. 2015 Aug 15;117:439-48. doi: 10.1016/j.neuroimage.2015.03.071. Epub 2015 Apr 7.

2.

Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode.

Maldjian JA, Davenport EM, Whitlow CT.

Neuroimage. 2014 Aug 1;96:88-94. doi: 10.1016/j.neuroimage.2014.03.065. Epub 2014 Mar 31.

3.

Disclosing large-scale directed functional connections in MEG with the multivariate phase slope index.

Basti A, Pizzella V, Chella F, Romani GL, Nolte G, Marzetti L.

Neuroimage. 2018 Jul 15;175:161-175. doi: 10.1016/j.neuroimage.2018.03.004. Epub 2018 Mar 7.

4.

Adaptive cortical parcellations for source reconstructed EEG/MEG connectomes.

Farahibozorg SR, Henson RN, Hauk O.

Neuroimage. 2018 Apr 1;169:23-45. doi: 10.1016/j.neuroimage.2017.09.009. Epub 2017 Sep 8.

5.

Task- and stimulus-related cortical networks in language production: Exploring similarity of MEG- and fMRI-derived functional connectivity.

Liljeström M, Stevenson C, Kujala J, Salmelin R.

Neuroimage. 2015 Oct 15;120:75-87. doi: 10.1016/j.neuroimage.2015.07.017. Epub 2015 Jul 11.

6.

Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of conditions of mild cognitive impairment.

Pineda-Pardo JA, Bruña R, Woolrich M, Marcos A, Nobre AC, Maestú F, Vidaurre D.

Neuroimage. 2014 Nov 1;101:765-77. doi: 10.1016/j.neuroimage.2014.08.002. Epub 2014 Aug 8.

7.

Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses.

Wang SH, Lobier M, Siebenhühner F, Puoliväli T, Palva S, Palva JM.

Neuroimage. 2018 Jun;173:610-622. doi: 10.1016/j.neuroimage.2018.01.056. Epub 2018 Jan 31.

8.

Adding dynamics to the Human Connectome Project with MEG.

Larson-Prior LJ, Oostenveld R, Della Penna S, Michalareas G, Prior F, Babajani-Feremi A, Schoffelen JM, Marzetti L, de Pasquale F, Di Pompeo F, Stout J, Woolrich M, Luo Q, Bucholz R, Fries P, Pizzella V, Romani GL, Corbetta M, Snyder AZ; WU-Minn HCP Consortium.

Neuroimage. 2013 Oct 15;80:190-201. doi: 10.1016/j.neuroimage.2013.05.056. Epub 2013 May 20.

9.

Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity.

Houck JM, Çetin MS, Mayer AR, Bustillo JR, Stephen J, Aine C, Cañive J, Perrone-Bizzozero N, Thoma RJ, Brookes MJ, Calhoun VD.

Neuroimage. 2017 Jan 15;145(Pt A):96-106. doi: 10.1016/j.neuroimage.2016.10.011. Epub 2016 Oct 8.

10.

How reliable are MEG resting-state connectivity metrics?

Colclough GL, Woolrich MW, Tewarie PK, Brookes MJ, Quinn AJ, Smith SM.

Neuroimage. 2016 Sep;138:284-293. doi: 10.1016/j.neuroimage.2016.05.070. Epub 2016 Jun 1.

11.

Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution.

Hillebrand A, Barnes GR, Bosboom JL, Berendse HW, Stam CJ.

Neuroimage. 2012 Feb 15;59(4):3909-21. doi: 10.1016/j.neuroimage.2011.11.005. Epub 2011 Nov 9.

12.

The electrophysiological connectome is maintained in healthy elders: a power envelope correlation MEG study.

Coquelet N, Mary A, Peigneux P, Goldman S, Wens V, De Tiège X.

Sci Rep. 2017 Oct 25;7(1):13984. doi: 10.1038/s41598-017-13829-8.

13.

MEG source reconstruction based on identification of directed source interactions on whole-brain anatomical networks.

Fukushima M, Yamashita O, Knösche TR, Sato MA.

Neuroimage. 2015 Jan 15;105:408-27. doi: 10.1016/j.neuroimage.2014.09.066. Epub 2014 Oct 5. Erratum in: Neuroimage. 2015 Apr 1;109:529.

14.

What graph theory actually tells us about resting state interictal MEG epileptic activity.

Niso G, Carrasco S, Gudín M, Maestú F, Del-Pozo F, Pereda E.

Neuroimage Clin. 2015 May 23;8:503-15. doi: 10.1016/j.nicl.2015.05.008. eCollection 2015.

15.

Assessment and elimination of the effects of head movement on MEG resting-state measures of oscillatory brain activity.

Messaritaki E, Koelewijn L, Dima DC, Williams GM, Perry G, Singh KD.

Neuroimage. 2017 Oct 1;159:302-324. doi: 10.1016/j.neuroimage.2017.07.038. Epub 2017 Jul 20.

16.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

Sohrabpour A, Ye S, Worrell GA, Zhang W, He B.

IEEE Trans Biomed Eng. 2016 Dec;63(12):2474-2487. Epub 2016 Oct 11.

17.

Using variance information in magnetoencephalography measures of functional connectivity.

Hall EL, Woolrich MW, Thomaz CE, Morris PG, Brookes MJ.

Neuroimage. 2013 Feb 15;67:203-12. doi: 10.1016/j.neuroimage.2012.11.011. Epub 2012 Nov 17.

PMID:
23165323
18.

Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach.

Tewarie P, Hillebrand A, van Dijk BW, Stam CJ, O'Neill GC, Van Mieghem P, Meier JM, Woolrich MW, Morris PG, Brookes MJ.

Neuroimage. 2016 Nov 15;142:324-336. doi: 10.1016/j.neuroimage.2016.07.057. Epub 2016 Aug 3.

PMID:
27498371
19.

A signal-processing pipeline for magnetoencephalography resting-state networks.

Mantini D, Della Penna S, Marzetti L, de Pasquale F, Pizzella V, Corbetta M, Romani GL.

Brain Connect. 2011;1(1):49-59. doi: 10.1089/brain.2011.0001.

PMID:
22432954
20.

Thresholding functional connectomes by means of mixture modeling.

Bielczyk NZ, Walocha F, Ebel PW, Haak KV, Llera A, Buitelaar JK, Glennon JC, Beckmann CF.

Neuroimage. 2018 May 1;171:402-414. doi: 10.1016/j.neuroimage.2018.01.003. Epub 2018 Jan 5.

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