General bibliography

The references below are arranged alphabetically by first author.

  1. Pierre Ablin, Jean-Francois Cardoso, and Alexandre Gramfort. Faster Independent Component Analysis by preconditioning with hessian approximations. IEEE Transactions on Signal Processing, 66(15):4040–4049, 2018. doi:10.1109/TSP.2018.2844203.

  2. David J. Acunzo, Graham MacKenzie, and Mark C.W. van Rossum. Systematic biases in early ERP and ERF components as a result of high-pass filtering. Journal of Neuroscience Methods, 209(1):212–218, 2012. doi:10.1016/j.jneumeth.2012.06.011.

  3. Fiorenzo Artoni, Arnaud Delorme, and Scott Makeig. Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition. NeuroImage, 175:176–187, 2018. doi:10.1016/j.neuroimage.2018.03.016.

  4. Brian B. Avants, Charles L. Epstein, Murray C. Grossman, and James C. Gee. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1):26–41, 2008. doi:10.1016/j.media.2007.06.004.

  5. Sylvain Baillet, John C. Mosher, and Richard M. Leahy. Electromagnetic brain mapping. IEEE Signal Processing Magazine, 18(6):14–30, 2001. doi:10.1109/79.962275.

  6. David Barber. Bayesian Reasoning and Machine Learning. Cambridge University Press, Cambridge, 2012. ISBN 978-0-521-51814-7. URL: http://www.cs.ucl.ac.uk/staff/d.barber/brml/.

  7. Yousra Bekhti, Daniel Strohmeiery, Mainak Jas, Roland Badeau, and Alexandre Gramfort. M/EEG source localization with multi-scale time-frequency dictionaries. In Proceedings of PRNI-2016, 1–4. Trento, 2016. IEEE. doi:10.1109/PRNI.2016.7552337.

  8. Anthony J. Bell and Terrence J. Sejnowski. An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7(6):1129–1159, 1995. doi:10.1162/neco.1995.7.6.1129.

  9. Anna Rita Bentivoglio, Susan B. Bressman, Emanuele Cassetta, Donatella Carretta, Pietro Tonali, and Alberto Albanese. Analysis of blink rate patterns in normal subjects. Movement Disorders, 12(6):1028–1034, 1997. doi:10.1002/mds.870120629.

  10. Patrick Berg and Michael Scherg. A fast method for forward computation of multiple-shell spherical head models. Electroencephalography and Clinical Neurophysiology, 90(1):58–64, 1994. doi:10.1016/0013-4694(94)90113-9.

  11. Benjamin Blankertz, Ryota Tomioka, Steven Lemm, Motoaki Kawanabe, and Klaus-Robert Müller. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Processing Magazine, 25(1):41–56, 2008. doi:10.1109/MSP.2008.4408441.

  12. Fred L. Bookstein. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(6):567–585, 1989. doi:10.1109/34.24792.

  13. Matthew J. Brookes, Jiri Vrba, Stephen E. Robinson, Claire M. Stevenson, Andrew M. Peters, Gareth R. Barnes, Arjan Hillebrand, and Peter G. Morris. Optimising experimental design for MEG beamformer imaging. NeuroImage, 39(4):1788–1802, 2008. doi:10.1016/j.neuroimage.2007.09.050.

  14. Filipa Campos Viola, Jeremy Thorne, Barrie Edmonds, Till Schneider, Tom Eichele, and Stefan Debener. Semi-automatic identification of independent components representing EEG artifact. Clinical Neurophysiology, 120(5):868–877, 2009. doi:10.1016/j.clinph.2009.01.015.

  15. Stanislas Chambon, Mathieu N. Galtier, Pierrick J. Arnal, Gilles Wainrib, and Alexandre Gramfort. A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(4):758–769, 2018. doi:10.1109/TNSRE.2018.2813138.

  16. Yilun Chen, Ami Wiesel, Yonina C. Eldar, and Alfred O. Hero. Shrinkage algorithms for MMSE covariance estimation. IEEE Transactions on Signal Processing, 58(10):5016–5029, 2010. doi:10.1109/TSP.2010.2053029.

  17. Radoslaw Martin Cichy, Dimitrios Pantazis, and Aude Oliva. Resolving human object recognition in space and time. Nature Neuroscience, 17(3):455–462, 2014. doi:10.1038/nn.3635.

  18. David Cohen and Hidehiro Hosaka. Part II magnetic field produced by a current dipole. Journal of Electrocardiology, 9(4):409–417, 1976. doi:10.1016/S0022-0736(76)80041-6.

  19. Michael J. Crosse, Giovanni M. Di Liberto, Adam Bednar, and Edmund C. Lalor. The multivariate temporal response function (mTRF) toolbox: a MATLAB toolbox for relating neural signals to continuous stimuli. Frontiers in Human Neuroscience, 2016. doi:10.3389/fnhum.2016.00604.

  20. Sarang S. Dalal, Adrian G. Guggisberg, Erik Edwards, Kensuke Sekihara, Anne M. Findlay, Ryan T. Canolty, Mitchel S. Berger, Robert T. Knight, Nicholas M. Barbaro, Heidi E. Kirsch, and Srikantan S. Nagarajan. Five-dimensional neuroimaging: localization of the time–frequency dynamics of cortical activity. NeuroImage, 40(4):1686–1700, 2008. doi:10.1016/j.neuroimage.2008.01.023.

  21. Anders M. Dale, Bruce Fischl, and Martin I. Sereno. Cortical surface-based analysis: I. segmentation and surface reconstruction. NeuroImage, 9(2):179–194, 1999. doi:10.1006/nimg.1998.0395.

  22. Anders M. Dale, Arthur K. Liu, Bruce R. Fischl, Randy L. Buckner, John W. Belliveau, Jeffrey D. Lewine, and Eric Halgren. Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron, 26(1):55–67, 2000. doi:10.1016/S0896-6273(00)81138-1.

  23. Anders M. Dale and Martin I. Sereno. Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. Journal of Cognitive Neuroscience, 5(2):162–176, 1993. doi:10.1162/jocn.1993.5.2.162.

  24. Jürgen Dammers, Michael Schiek, Frank Boers, Carmen Silex, Mikhail Zvyagintsev, Uwe Pietrzyk, and Klaus Mathiak. Integration of amplitude and phase statistics for complete artifact removal in independent components of neuromagnetic recordings. IEEE Transactions on Biomedical Engineering, 55(10):2353–2362, 2008. doi:10.1109/TBME.2008.926677.

  25. Felix Darvas, John J. Ermer, John C. Mosher, and Richard M. Leahy. Generic head models for atlas-based EEG source analysis. Human Brain Mapping, 27(2):129–143, 2006. doi:10.1002/hbm.20171.

  26. Christophe Destrieux, Bruce Fischl, Anders Dale, and Eric Halgren. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. NeuroImage, 53(1):1–15, 2010. doi:10.1016/j.neuroimage.2010.06.010.

  27. Stéphane Dufau, Jonathan Grainger, Katherine J. Midgley, and Phillip J. Holcomb. A thousand words are worth a picture: snapshots of printed-word processing in an event-related potential megastudy. Psychological Science, 26(12):1887–1897, 2015. doi:10.1177/0956797615603934.

  28. Sven Dähne, Frank C. Meinecke, Stefan Haufe, Johannes Höhne, Michael Tangermann, Klaus-Robert Müller, and Vadim V. Nikulin. SPoC: a novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters. NeuroImage, 86:111–122, 2014. doi:10.1016/j.neuroimage.2013.07.079.

  29. Bradley Efron and Trevor Hastie. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Number 5 in Institute of Mathematical Statistics Monographs. Cambridge University Press, New York, 2016. ISBN 978-1-107-14989-2. URL: https://web.stanford.edu/~hastie/CASI/.

  30. Denis A. Engemann and Alexandre Gramfort. Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals. NeuroImage, 108:328–342, 2015. doi:10.1016/j.neuroimage.2014.12.040.

  31. Bruce Fischl, David H. Salat, André J.W. van der Kouwe, Nikos Makris, Florent Ségonne, Brian T. Quinn, and Anders M. Dale. Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23:S69–S84, 2004. doi:10.1016/j.neuroimage.2004.07.016.

  32. Bruce Fischl, Martin I. Sereno, and Anders M. Dale. Cortical surface-based analysis: II. inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2):195–207, 1999. doi:10.1006/nimg.1998.0396.

  33. Bruce Fischl, Martin I. Sereno, Roger B.H. Tootell, and Anders M. Dale. High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8(4):272–284, 1999. doi:10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4.

  34. Matthew F. Glasser, Timothy S. Coalson, Emma C. Robinson, Carl D. Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, Jesper Andersson, Christian F. Beckmann, Mark Jenkinson, Stephen M. Smith, and David C. Van Essen. A multi-modal parcellation of human cerebral cortex. Nature, 536(7615):171–178, 2016. doi:10.1038/nature18933.

  35. Ary L. Goldberger, Luis A. N. Amaral, Leon Glass, Jeffrey M. Hausdorff, Plamen Ch. Ivanov, Roger G. Mark, Joseph E. Mietus, George B. Moody, Chung-Kang Peng, and H. Eugene Stanley. PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation, 2000. doi:10.1161/01.CIR.101.23.e215.

  36. Daniel M. Goldenholz, Seppo P. Ahlfors, Matti S. Hämäläinen, Dahlia Sharon, Mamiko Ishitobi, Lucia M. Vaina, and Steven M. Stufflebeam. Mapping the signal-to-noise-ratios of cortical sources in magnetoencephalography and electroencephalography. Human Brain Mapping, 30(4):1077–1086, 2009. doi:10.1002/hbm.20571.

  37. Sónia I. Gonçalves, Jan Casper de Munck, Jeroen P. A. Verbunt, Fetsje Bijma, Rob M. Heethaar, and Fernando Lopes da Silva. In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head. IEEE Transactions on Biomedical Engineering, 50(6):754–767, 2003. doi:10.1109/TBME.2003.812164.

  38. Bernhard Graimann, Jane E. Huggins, Simon P. Levine, and Gert Pfurtscheller. Visualization of significant ERD/ERS patterns in multichannel EEG and ECoG data. Clinical Neurophysiology, 113(1):43–47, 2002. doi:10.1016/S1388-2457(01)00697-6.

  39. Alexandre Gramfort, Matthieu Kowalski, and Matti S. Hämäläinen. Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods. Physics in Medicine and Biology, 57(7):1937–1961, 2012. doi:10.1088/0031-9155/57/7/1937.

  40. Alexandre Gramfort, Daniel Strohmeier, Jens Haueisen, Matti S. Hämäläinen, and Matthieu Kowalski. Functional brain imaging with M/EEG using structured sparsity in time-frequency dictionaries. In Gábor Székely and Horst K. Hahn, editors, Information Processing in Medical Imaging, volume 6801, pages 600–611. Springer, Berlin; Heidelberg, 2011. doi:10.1007/978-3-642-22092-0_49.

  41. Alexandre Gramfort, Daniel T. Strohmeier, Jens Haueisen, Matti S. Hämäläinen, and Matthieu Kowalski. Time-frequency mixed-norm estimates: sparse M/EEG imaging with non-stationary source activations. NeuroImage, 70:410–422, 2013. doi:10.1016/j.neuroimage.2012.12.051.

  42. Douglas N. Greve, Lise Van der Haegen, Qing Cai, Steven Stufflebeam, Mert R. Sabuncu, Bruce Fischl, and Marc Brysbaert. A surface-based analysis of language lateralization and cortical asymmetry. Journal of Cognitive Neuroscience, 25(9):1477–1492, 2013. doi:10.1162/jocn_a_00405.

  43. Joachim Groß, Jan Kujala, Matti S. Hämäläinen, Lars Timmermann, Alfons Schnitzler, and Riitta Salmelin. Dynamic imaging of coherent sources: studying neural interactions in the human brain. Proceedings of the National Academy of Sciences, 98(2):694–699, 2001. doi:10.1073/pnas.98.2.694.

  44. Riitta Hari and Riitta Salmelin. Human cortical oscillations: a neuromagnetic view through the skull. Trends in Neurosciences, 20(1):44–49, 1997. doi:10.1016/S0166-2236(96)10065-5.

  45. Stefan Haufe, Frank Meinecke, Kai Görgen, Sven Dähne, John-Dylan Haynes, Benjamin Blankertz, and Felix Bießmann. On the interpretation of weight vectors of linear models in multivariate neuroimaging. NeuroImage, 87:96–110, 2014. doi:10.1016/j.neuroimage.2013.10.067.

  46. Olaf Hauk, Matt H. Davis, Michael A. Ford, Friedmann Pulvermüller, and William D. Marslen-Wilson. The time course of visual word recognition as revealed by linear regression analysis of ERP data. NeuroImage, 30(4):1383–1400, 2006. doi:10.1016/j.neuroimage.2005.11.048.

  47. Gary W. Heiman. Research Methods in Psychology. Houghton Mifflin Company, Boston, 3 edition, 2002. ISBN 978-0-618-17028-9.

  48. Joerg F Hipp, David J Hawellek, Maurizio Corbetta, Markus Siegel, and Andreas K Engel. Large-scale cortical correlation structure of spontaneous oscillatory activity. Nature Neuroscience, 15(6):884–890, 2012. doi:10.1038/nn.3101.

  49. Joerg F. Hipp, Andreas K. Engel, and Markus Siegel. Oscillatory synchronization in large-scale cortical networks predicts perception. Neuron, 69(2):387–396, 2011. doi:10.1016/j.neuron.2010.12.027.

  50. Christopher R. Holdgraf, Wendy de Heer, Brian Pasley, Jochem Rieger, Nathan Crone, Jack J. Lin, Robert T. Knight, and Frédéric E. Theunissen. Rapid tuning shifts in human auditory cortex enhance speech intelligibility. Nature Communications, 2016. doi:10.1038/ncomms13654.

  51. Aapo Hyvärinen. Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks, 10(3):626–634, 1999. doi:10.1109/72.761722.

  52. Matti S. Hämäläinen and Riitta Hari. Magnetoencephalographic characterization of dynamic brain activation: basic principles and methods of data collection and source analysis. In Arthur W. Toga and John C. Mazziotta, editors, Brain Mapping: The Methods, pages 227 – 253. Academic Press, San Diego, 2 edition, 2002. doi:10.1016/B978-012693019-1/50012-5.

  53. Matti S. Hämäläinen, Riitta Hari, Risto J. Ilmoniemi, Jukka Knuutila, and Olli V. Lounasmaa. Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Reviews of Modern Physics, 65(2):413–497, 1993. doi:10.1103/RevModPhys.65.413.

  54. Matti S. Hämäläinen and Ilmoniemi Ilmoniemi, Risto J. Interpreting magnetic fields of the brain: minimum norm estimates. Medical & Biological Engineering & Computing, 32(1):35–42, 1994. doi:10.1007/BF02512476.

  55. Matti S. Hämäläinen and Risto J. Ilmoniemi. Interpreting measured magnetic fields of the brain: estimates of current distributions. Technical Report TKK-F-A559, Helsinki University of Technology, Helsinki, 1984.

  56. Matti S. Hämäläinen and Jukka Sarvas. Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data. IEEE Transactions on Biomedical Engineering, 36(2):165–171, 1989. doi:10.1109/10.16463.

  57. Emmanuel C. Ifeachor and Barrie W. Jervis. Digital Signal Processing: A Practical Approach. Pearson, 2 edition, 2002.

  58. Kevin A. Jones, Bernice Porjesz, David Chorlian, Madhavi Rangaswamy, Chella Kamarajan, Ajayan Padmanabhapillai, Arthur Stimus, and Henri Begleiter. S-transform time-frequency analysis of P300 reveals deficits in individuals diagnosed with alcoholism. Clinical Neurophysiology, 117(10):2128–2143, 2006. doi:10.1016/j.clinph.2006.02.028.

  59. Jorge Jovicich, Silvester Czanner, Douglas Greve, Elizabeth Haley, Andre van der Kouwe, Randy Gollub, David Kennedy, Franz Schmitt, Gregory Brown, James MacFall, Bruce Fischl, and Anders Dale. Reliability in multi-site structural MRI studies: effects of gradient non-linearity correction on phantom and human data. NeuroImage, 30(2):436–443, 2006. doi:10.1016/j.neuroimage.2005.09.046.

  60. Emily S. Kappenman and Steven J. Luck. The effects of electrode impedance on data quality and statistical significance in ERP recordings. Psychophysiology, 2010. doi:10.1111/j.1469-8986.2010.01009.x.

  61. B. Kemp, A. H. Zwinderman, B. Tuk, H. A. C. Kamphuisen, and J. J. L. Oberyé. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG. IEEE Transactions on Biomedical Engineering, 47(9):1185–1194, 2000. doi:10.1109/10.867928.

  62. Sheraz Khan and David Cohen. Note: magnetic noise from the inner wall of a magnetically shielded room. Review of Scientific Instruments, 84(5):056101, 2013. doi:10.1063/1.4802845.

  63. Sheraz Khan, Javeria A. Hashmi, Fahimeh Mamashli, Konstantinos Michmizos, Manfred G. Kitzbichler, Hari Bharadwaj, Yousra Bekhti, Santosh Ganesan, Keri-Lee A. Garel, Susan Whitfield-Gabrieli, Randy L. Gollub, Jian Kong, Lucia M. Vaina, Kunjan D. Rana, Steven M. Stufflebeam, Matti S. Hämäläinen, and Tal Kenet. Maturation trajectories of cortical resting-state networks depend on the mediating frequency band. NeuroImage, 174:57–68, 2018. doi:10.1016/j.neuroimage.2018.02.018.

  64. Jean-Rémi King and Stanislas Dehaene. Characterizing the dynamics of mental representations: the temporal generalization method. Trends in Cognitive Sciences, 18(4):203–210, 2014. doi:10.1016/j.tics.2014.01.002.

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  67. Jukka E. T. Knuutila, Antti I. Ahonen, Matti S. Hämäläinen, Matti J. Kajola, P. P. Laine, Olli V. Lounasmaa, Lauri T. Parkkonen, Juha T. A. Simola, and Claudia D. Tesche. A 122-channel whole-cortex SQUID system for measuring the brain’s magnetic fields. IEEE Transactions on Magnetics, 29(6):3315–3320, 1993. doi:10.1109/20.281163.

  68. Zoltan J. Koles. The quantitative extraction and topographic mapping of the abnormal components in the clinical EEG. Electroencephalography and Clinical Neurophysiology, 79(6):440–447, 1991. doi:10.1016/0013-4694(91)90163-X.

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  71. Aarre Laakso and Garrison Cottrell. Content and cluster analysis: assessing representational similarity in neural systems. Philosophical Psychology, 13(1):47–76, 2000. doi:10.1080/09515080050002726.

  72. Jean-Philippe Lachaux, Eugenio Rodriguez, Jacques Martinerie, and Francisco J. Varela. Measuring phase synchrony in brain signals. Human Brain Mapping, 8(4):194–208, 1999. doi:10.1002/(SICI)1097-0193(1999)8:4<194::AID-HBM4>3.0.CO;2-C.

  73. Eric Larson and Adrian K.C. Lee. The cortical dynamics underlying effective switching of auditory spatial attention. NeuroImage, 64:365–370, 2013. doi:10.1016/j.neuroimage.2012.09.006.

  74. Eric Larson and Samu Taulu. The importance of properly compensating for head movements during MEG acquisition across different age groups. Brain Topography, 30(2):172–181, 2017. doi:10.1007/s10548-016-0523-1.

  75. Eric Larson and Samu Taulu. Reducing sensor noise in MEG and EEG recordings using oversampled temporal projection. IEEE Transactions on Biomedical Engineering, 65(5):1002–1013, 2018. doi:10.1109/TBME.2017.2734641.

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  92. M. S. Mourtazaev, B. Kemp, A. H. Zwinderman, and H. A. C. Kamphuisen. Age and gender affect different characteristics of slow waves in the sleep EEG. Sleep, 18(7):557–564, 1995. doi:10.1093/sleep/18.7.557.

  93. Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort, and Joseph Salmon. GAP safe screening rules for sparse-group lasso. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, editors, Advances in Neural Information Processing Systems 29, 388–396. Curran Associates, Inc., 2016. URL: http://papers.nips.cc/paper/6405-gap-safe-screening-rules-for-sparse-group-lasso.pdf.

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  95. Guido Nolte, Ou Bai, Lewis Wheaton, Zoltan Mari, Sherry Vorbach, and Mark Hallett. Identifying true brain interaction from EEG data using the imaginary part of coherency. Clinical Neurophysiology, 115(10):2292–2307, 2004. doi:10.1016/j.clinph.2004.04.029.

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