Wenderoth N - Search Results

1

Mapping pathological changes in brain structure by combining T1- and T2-weighted MR imaging data.

Ganzetti M, Wenderoth N, Mantini D. Ganzetti M, et al. Among authors: wenderoth n. Neuroradiology. 2015 Sep;57(9):917-28. doi: 10.1007/s00234-015-1550-4. Epub 2015 Jun 24. Neuroradiology. 2015. PMID: 26104102 Free PMC article.

2

Homologous involvement of striatum and prefrontal cortex in rodent and human water maze learning.

Woolley DG, Laeremans A, Gantois I, Mantini D, Vermaercke B, Op de Beeck HP, Swinnen SP, Wenderoth N, Arckens L, D'Hooge R. Woolley DG, et al. Among authors: wenderoth n. Proc Natl Acad Sci U S A. 2013 Feb 19;110(8):3131-6. doi: 10.1073/pnas.1217832110. Epub 2013 Feb 4. Proc Natl Acad Sci U S A. 2013. PMID: 23382228 Free PMC article.

3

Whole brain myelin mapping using T1- and T2-weighted MR imaging data.

Ganzetti M, Wenderoth N, Mantini D. Ganzetti M, et al. Among authors: wenderoth n. Front Hum Neurosci. 2014 Sep 2;8:671. doi: 10.3389/fnhum.2014.00671. eCollection 2014. Front Hum Neurosci. 2014. PMID: 25228871 Free PMC article.

4

Virtual water maze learning in human increases functional connectivity between posterior hippocampus and dorsal caudate.

Woolley DG, Mantini D, Coxon JP, D'Hooge R, Swinnen SP, Wenderoth N. Woolley DG, et al. Among authors: wenderoth n. Hum Brain Mapp. 2015 Apr;36(4):1265-77. doi: 10.1002/hbm.22700. Epub 2014 Nov 21. Hum Brain Mapp. 2015. PMID: 25418860 Free PMC article.

5

Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification.

Zerbi V, Grandjean J, Rudin M, Wenderoth N. Zerbi V, et al. Among authors: wenderoth n. Neuroimage. 2015 Dec;123:11-21. doi: 10.1016/j.neuroimage.2015.07.090. Epub 2015 Aug 18. Neuroimage. 2015. PMID: 26296501

6

Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model.

Liu Q, Balsters JH, Baechinger M, van der Groen O, Wenderoth N, Mantini D. Liu Q, et al. Among authors: wenderoth n. J Neural Eng. 2015 Oct;12(5):056012. doi: 10.1088/1741-2560/12/5/056012. Epub 2015 Aug 25. J Neural Eng. 2015. PMID: 26305167 Free PMC article.

7

Quantitative Evaluation of Intensity Inhomogeneity Correction Methods for Structural MR Brain Images.

Ganzetti M, Wenderoth N, Mantini D. Ganzetti M, et al. Among authors: wenderoth n. Neuroinformatics. 2016 Jan;14(1):5-21. doi: 10.1007/s12021-015-9277-2. Neuroinformatics. 2016. PMID: 26306865 Free PMC article.

8

Intensity Inhomogeneity Correction of Structural MR Images: A Data-Driven Approach to Define Input Algorithm Parameters.

Ganzetti M, Wenderoth N, Mantini D. Ganzetti M, et al. Among authors: wenderoth n. Front Neuroinform. 2016 Mar 15;10:10. doi: 10.3389/fninf.2016.00010. eCollection 2016. Front Neuroinform. 2016. PMID: 27014050 Free PMC article.

9

Connectivity-based parcellation increases network detection sensitivity in resting state fMRI: An investigation into the cingulate cortex in autism.

Balsters JH, Mantini D, Apps MAJ, Eickhoff SB, Wenderoth N. Balsters JH, et al. Among authors: wenderoth n. Neuroimage Clin. 2016 Mar 25;11:494-507. doi: 10.1016/j.nicl.2016.03.016. eCollection 2016. Neuroimage Clin. 2016. PMID: 27114898 Free PMC article.

10

Automated detection and labeling of high-density EEG electrodes from structural MR images.

Marino M, Liu Q, Brem S, Wenderoth N, Mantini D. Marino M, et al. Among authors: wenderoth n. J Neural Eng. 2016 Oct;13(5):056003. doi: 10.1088/1741-2560/13/5/056003. Epub 2016 Aug 3. J Neural Eng. 2016. PMID: 27484621 Free article.

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