Group research topics:

Broadly methodology for analysis and modelling of neuroimaging data, in particular:

• Unsupervised decomposition methods for neuroimaging data
• Analysis of neuroimaging data with time critical applications (real-time)
• Modelling and quantification of complex networks
• Source modelling for EEG/MEG data

Group members:

Selected publications:

Madsen KH, Ewald L, Siebner HR, Thielscher A. Transcranial Magnetic Stimulation: An Automated Procedure to Obtain Coil-specific Models for Field Calculations. Brain Stimul 2015. doi:10.1016/j.brs.2015.07.035.

Andersen KW, Madsen KH, Siebner HR, et al. Non-parametric Bayesian graph models reveal community structure in resting state fMRI. Neuroimage 2014;100C:301–15. doi:10.1016/j.neuroimage.2014.05.083.

Jørgensen KW, Mørup M, Siebner HR, Madsen KH, Hansen LK. Identifying Modular Relations in Complex Brain Networks. IEEE Int. Work. Mach. Learn. Signal Process., 2012.

Mørup M, Hansen LK, Madsen KH. Frequency Constrained ShiftCP Modeling of Neuroimaging Data. Procedings Asilomar Conf. Signals, Syst. Comput. 2011, 2011.

Rasmussen PM, Madsen KH, Lund TE, Hansen LK. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps. Neuroimage 2011;55:1120–31. doi:10.1016/j.neuroimage.2010.12.035.

Rasmussen PM, Abrahamsen TJ, Madsen KH, Hansen LK. Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation. Neuroimage 2012;60:1807–18. doi:10.1016/j.neuroimage.2012.01.096.

Mørup M, Hansen LK, Arnfred SM, Lim L-H, Madsen KH. Shift-invariant multilinear decomposition of neuroimaging data. Neuroimage 2008;42:1439–50. doi:10.1016/j.neuroimage.2008.05.062.

Jacobsen DJ, Hansen LK, Madsen KH. Bayesian model comparison in nonlinear BOLD fMRI hemodynamics. Neural Comput 2008;20:738–55. doi:10.1162/neco.2007.07-06-282.

Nielsen FA, Christensen MS, Madsen KH, Lund TE, Hansen LK. fMRI neuroinformatics. IEEE Eng Med Biol Mag 2006;25:112–9.

Lund TE, Madsen KH, Sidaros K, Luo W-L, Nichols TE. Non-white noise in fMRI: does modelling have an impact? Neuroimage 2006;29:54–66. doi:10.1016/j.neuroimage.2005.07.005.