SigProC and CBU
In this Wiki, we collect material that may be relevant for the possible collaboration between SigProC and CBU. If you want to have something added here, but you don't have rights to modify the page, please send your suggestion to Olaf or Matti.
EEG/MEG
General EEG/MEG papers
Review articles:
- M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, and O. V. Lounasmaa, "Magnetoencephalography - theory, instrumentation, and applications to noninvasive studies of the working human brain," Reviews of Modern Physics, vol. 65, pp. 413-497, 1993.
- S. Baillet, J. C. Mosher, and R. M. Leahy, "Electromagnetic Brain Mapping," IEEE Signal Processing Magazine, vol. 18, pp. 14 - 30, 2001.
Inverse problem of EEG/MEG
Evaluating and comparing different inversion methods:
O. Hauk, D.G. Wakeman, R. Henson (2011). [http://ukpmc.ac.uk/abstract/MED/20884360 Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics], NeuroImage 54(3), 1966-1974.
Basics of distributed approaches to the EEG/MEG inverse problem:
- Hauk, O. (2004). [attachment:HaukMN.pdf Keep it simple: a case for using classical minimum norm estimation in the analysis of EEG and MEG data]. Neuroimage, 21(4), 1612-1621.
Geometrical description of fMRI-weighted minimum norm estimation:
Ahlfors, S. P., & Simpson, G. V. (2004). [attachment:AhlforsfMRI.pdf Geometrical interpretation of fMRI-guided MEG/EEG inverse estimates]. Neuroimage, 22(1), 323-332.
Previous work done at the BECS, Aalto University:
Thesis "[http://lib.tkk.fi/Diss/2008/isbn9789512291434/ Hierarchical Bayesian Aspects of Distributed Neuromagnetic Source Models]" by Aapo Nummenmaa
Thesis "[http://lib.tkk.fi/Diss/2007/isbn9789512289547/ Computational Methods for Bayesian Estimation of Neuromagnetic Sources]" by Toni Auranen
Basic physics and forward modeling
Thesis "[http://lib.tkk.fi/Diss/2008/isbn9789512295876/ Boundary Element Method in Spatial Characterization of the Electrocardiogram]" by Matti Stenroos (this is about electrocardiography, but the physics and the forward solution is in principle the same as in EEG/MEG)
Multimodal Integration
- Review of our Parametric Empirical Bayesian (Gaussian process modelling) efforts for combining fMRI, EEG, MEG
[http://www.mrc-cbu.cam.ac.uk/people/rik.henson/personal/HensonEtAl_FiN_11_PEB_MEEG_review.pdf HensonEtAl_FiN_11_PEB_MEEG_review.pdf]
Connectivity analysis
- Recent review of Dynamic Causal Modelling (DCM), particularly for experimental perturbations
attachment:DaunizeauEtAl_11_NI_DCM_review.pdf
- Recent application of DCM to discovering networks in endogenous (eg resting state) data
attachment:FristonEtAl_NI_11_DCM_discovery.pdf
Pattern Classification
Review of pattern classification approaches in neuroimaging:
Kriegeskorte, N. [attachment:KriegeskortePattern.pdf Pattern-information analysis: from stimulus decoding to computational-model testing]. Neuroimage, 56(2), 411-421.