Related Publications

Relationship to the Human Connectome Project

The dHCP will take advantage of, and complement, work in progress to map the normal adult connectome. The Human Connectome Project (HCP) is developing a comprehensive open source informatics infrastructure based on XNAT software that allows continued addition of data and refinement in analysis, and the dHCP will utilize and extend aspects of this informatics architecture to leverage scientific, practical and financial efficiencies and avoiding expensive re-invention of informatics technologies; this informatics strategy means that both projects can contribute together to an evolving 4D lifecourse connectome. We will also collaborate with an HCP group developing improve MR coil hardware. We will maintain close contact with European adult connectome researchers in the Human Brain Project and EU Connect. Reseachers from all these groups have joined the dHCP Advisory Board.

Human Connectome Project

As previously mentioned, the dHCP extends upon the current research on mapping the normal adult brain connectome carried-out by the Human Connectome Project.

Much of the work leading up to the dHCP can be found in these HCP articles:

  • D.M. Barch, G.C. Burgess, M.P. Harms, S.E. Petersen, B.L. Schlaggar, M. Corbetta, M.F. Glasser, S. Curtiss, S. Dixit, C. Feldt, D. Nolan, E. Bryant, T. Hartley, O. Footer, J.M. Bjork, R. Poldrack, S. Smith, H. Johansen-Berg, A.Z. Snyder, and Van Essen, D. – for the WU-Minn HCP Consortium. Function in the Human Connectome: Task-fMRI and individual differences in behavior. NeuroImage, 80:169-189, 2013.
  • T. Blumensath, S. Jbabdi, M.F. Glasser, D.C. Van Essen, K. Ugurbil, T.E. Behrens, and S.M. Smith. Spatially constrained hierarchical parcellation of the brain with resting-state FMRI. NeuroImage, 76:313-324, 2013.
  • M.F. Glasser, S.N. Sotiropoulos, J.A. Wilson, T.S. Coalson, B. Fischl, J.L. Andersson, J. Xu, S. Jbabdi, M. Webster, J.R. Polimeni, D.C. Van Essen, and Jenkinson, M. – for the WU-Minn HCP Consortium. The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage, 80:105-124, 2013.
  • A. Hyvärinen and S.M. Smith. Pairwise likelihood ratios for estimation of non-Gaussian structural equation models. Journal of Machine Learning Research, 14:111-152, 2013.
  • S. Jbabdi, S.N. Sotiropoulos, and T. E. Behrens. The topographic connectome. Current Opinion in Neurobiology, 23(2):207-15, 2013.
  • S. Jbabdi, J.F. Lehman, S.N. Haber, and T. E. Behrens. Human and monkey ventral prefrontal fibers use the same organizational principles to reach their targets: tracing versus tractography. Journal of Neuroscience, 33(7):3190-201, 2013.
  • D.S. Marcus, M.P. Harms, A.Z. Snyder, M. Jenkinson, J.A. Wilson, M.F. Glasser, D.M. Barch, K.A. Archie, G.C. Burgess, M. Ramaratnam, M. Hodge, W. Horton, R. Herrick, T. Olsen, M. McKay, M. House, M. Hileman, E. Reid, J. Harwell, T. Coalson, J. Schindler, J. Elam, S.W. Curtiss, and Van Essen, D. – for the WU-Minn HCP Consortium. Human Connectome Project informatics: Quality control, database services, and data visualization. NeuroImage, 80:202-219, 2013.
  • S.M. Smith, J. Andersson, E.J. Auerbach, C.F. Beckmann, J. Bijsterbosch, G. Douaud, E. Duff, D.A. Feinberg, L. Griffanti, M.P. Harms, M. Kelly, T. Laumann, K.L. Miller, S. Moeller, S. Petersen, J. Power, G. Salimi-Khorshidi, A.Z. Snyder, A. Vu, M.W. Woolrich, J. Xu, E. Yacoub, K. Ugurbil, D.C. Van Essen, and Glasser, M. – for the WU-Minn HCP Consortium. Resting-state fMRI in the Human Connectome Project. NeuroImage, 80:144-168, 2013.
  • S.M. Smith, D. Vidaurre, C.F. Beckmann, M.F. Glasser, M. Jenkinson, K.L. Miller, T.E. Nichols, E. Robinson, G. Salimi-Khorshidi, M.W. Woolrich, D.M. Barch, K. Ugurbil, and D.C. Van Essen. Functional connectomics from resting-state fMRI. Trends in Cognitive Sciences, 2013. In press.
  • S.N. Sotiropoulos, S. Jbabdi, J. Xu, J.L. Andersson, S. Moeller, E.J. Auerbach, M.F. Glasser, M. Hernandez, G. Sapiro, M. Jenkinson, D. Feinberg, E. Yacoub, C. Lenglet, D.C. Van Essen, K. Ugurbil, and Behrens, T. – for the WU-Minn HCP Consortium. Advances in diffusion MRI acquisition and processing in the Human Connectome Project. NeuroImage, 80:125-143, 2013.
  • K. Ugurbil, J. Xu, E.J. Auerbach, S. Moeller, A. Vu, J.M. Duarte-Carvajalino, C. Lenglet, X. Wu, S. Schmitter, P.F. Van de Moortele, J. Strupp, G. Sapiro, F. De Martino, D. Wang, N. Harel, M. Garwood, L. Chen, D.A. Feinberg, S.M. Smith, K.L. Miller, S.N. Sotiropoulos, S. Jbabdi, J.L. Andersson, T.E.J. Behrens, M.F. Glasser, D.C. Van Essen, and Yacoub, E. – for the WU-Minn HCP Consortium.
  • Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. NeuroImage, 80:80-104, 2013.
  • D.C. Van Essen, S.M. Smith, D.M. Barch, T.E. Behrens, E. Yacoub, and Ugurbil, K. – for the WU-Minn HCP Consortium. The WU-Minn Human Connectome Project: An overview. NeuroImage, 80:62-79, 2013.
  • M. W. Woolrich and K. E. Stephan. Biophysical network models and the human connectome. Neuroimage, 80:330-338, Oct 2013.
  • J. Xu, S. Moeller, E.J. Auerbach, J. Strupp, S.M. Smith, D.A. Feinberg, E. Yacoub, and K. Ugurbil. Evaluation of slice accelerations using multiband echo planar imaging at 3 Tesla. NeuroImage, 2013. In press.
  • C.F. Beckmann. Modelling with independent components. NeuroImage, 62:891-901, 2012.
  • M.J. Hawrylycz, E.S. Lein, A.L. Guillozet-Bongaarts, E.H. Shen, L. Ng, J.A. Miller, L.N. van de Lagemaat, K.A. Smith, A. Ebbert, Z.L. Riley, C. Abajian, C.F. Beckmann, A. Bernard, D. Bertagnolli, A.F. Boe, P.M. Cartagena, M.M. Chakravarty, M. Chapin, J. Chong, R.A. Dalley, B.D. Daly, C. Dang, S. Datta, N. Dee, T.A. Dolbeare, V. Faber, D. Feng, D.R. Fowler, J. Goldy, B.W. Gregor, Z. Haradon, D.R. Haynor, J.G. Hohmann, S. Horvath, R.E. Howard, A. Jeromin, J.M. Jochim, M. Kinnunen, C. Lau, E.T. Lazarz, C. Lee, T.A. Lemon, L. Li, Y. Li, J.A. Morris, C.C. Overly, P.D. Parker, S.E. Parry, M. Reding, J.J. Royall, J. Schulkin, P.A. Sequeira, C.R. Slaughterbeck, S.C. Smith, A.J. Sodt, S. Sunkin, B.E. Swanson, M.P. Vawter, D. Williams, P. Wohnoutka, H.R. Zielke, D.H. Geschwind, P.R. Hof, S.M. Smith, C. Koch, S.G.N. Grant, and A.R. Jones. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature, 489:391-399, 2012.
  • S. Jbabdi, Stamatios N. Sotiropoulos, Alexander M. Savio, Manuel Grana, and T. E. Behrens. Model-based analysis of multishell diffusion MR data for tractography: How to get over fitting problems. Magnetic Resonance in Medicine, 68(6):1846-55, 2012.
  • S. Jbabdi and T. E. Behrens. Specialization: The connections have it. Nature Neuroscience, 15(2):171-172, 2012.
  • S.M. Smith. The future of FMRI connectivity. NeuroImage, 62:1257-1266, 2012.
  • S.M. Smith, K.L. Miller, S. Moeller, J. Xu, E.J. Auerbach, M.W. Woolrich, C.F. Beckmann, M. Jenkinson, J. Andersson, M.F. Glasser, D. Van Essen, D. Feinberg, E. Yacoub, and K. Ugurbil. Temporally-independent functional modes of spontaneous brain activity. Proc Natl Acad Sci USA (PNAS), 109(8):3131-6, 2012.
  • D.C. Van Essen, K. Ugurbil, E. Auerbach, D. Barch, T.E.J. Behrens, R. Bucholz, A. Chang, L. Chen, M. Corbetta, S.W. Curtiss, S. Della Penna, D. Feinberg, M.F. Glasser, N. Harel, A.C. Heath, L. Larson-Prior, D. Marcus, G. Michalareas, S. Moeller, R. Oostenveld, S.E. Petersen, F. Prior, B.L. Schlaggar, S.M. Smith, A.Z. Snyder, J. Xu, E. Yacoub, and WU-Minn HCP Consortium. The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4):2222-2231, 2012.
  • G. Douaud, S. Jbabdi, T. Behrens, R. Menke, A. Gass, A. Monsch, A. Rao, B. Whitcher, G. Kindlmann, P. Matthews, and S. Smith. DTI measures in crossing-fibre areas: Increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer’s disease. NeuroImage, 55(3):880-890, 2011.
  • D.S. Marcus, J. Harwell, T. Olsen, M. Hodge, M.F. Glasser, F. Prior, M. Jenkinson, T. Laumann, S.W. Curtiss, and D.C. Van Essen. Informatics and data mining tools and strategies for the Human Connectome Project. Frontiers in Neuroinformatics, 5(4), 2011.
  • K.L. Miller, C.J. Stagg, G. Douaud, S. Jbabdi, S.M. Smith, T.E. Behrens, M. Jenkinson, S.A. Chance, M.M. Esiri, N.L. Voets, N. Jenkinson, T.Z. Aziz, M. Turner, H. Johansen-Berg, and J.A. McNab. Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner. NeuroImage, 57(1):167-181, 2011.
  • S.M. Smith, K.L. Miller, G. Salimi-Khorshidi, M. Webster, C.F. Beckmann, T.E. Nichols, J.D. Ramsey, and M.W. Woolrich. Network modelling methods for FMRI. NeuroImage, 54:875-891, 2011.
  • D.A. Feinberg, S. Moeller, S.M. Smith, E. Auerbach, S. Ramanna, M.F. Glasser, K.L. Miller, K. Ugurbil, and E. Yacoub. Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging. PLoS ONE, 5(12):e15710, 2010.
  • Elad, A., Keller, Y.,  and Kimmel, R.  Texture Mapping via Spherical Multidimensional Scaling. International Conference on Scale-Space Theories in Computer Vision  (2005): 443–455.
  • Malik, SJ, Price AN, and Hajnal JV. Optimized Amplitude Modulated) Muli-Band RF pulses. In Proc ISMRM 2015: p2398