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References to review papers and teaching material

Here we try to compile a list of background reading/studying material. If you know of good papers or other material, please add it by clicking on the edit button.

Sylvain Baillet wrote a recent review manuscript on Magnetoencephalography for brain electrophysiology and imaging in Nature Neuroscience (2017).

A comprehensive introduction in the neurophysiology and biophysics of EEG (also relevant for MEG) is given in Electric Fields of the Brain: The Neurophysics of EEG, 2nd Edition by Paul L. Nunez and Ramesh Srinivasan.

Steven J Luck, An Introduction to the Event-Related Potential Technique, MIT Press: 2005, ISBN 0262621967. This book is reviewed here: Peter Hagoort (2006)Event-related potentials from the user's perspective; Nature Neuroscience 9, 463.

The brain in time: insights from neuromagnetic recordings by Riitta Hari, Lauri Parkkonen and Cathy Nangini gives a comprehensive introduction to MEG.

MEG: An Introduction to Methods. by Peter Hansen, Morten Kringelbach, Riitta Salmelin. Pdf, Amazon.

References to review papers and teaching material

Here we try to compile a list of background reading/studying material. If you know of good papers or other material, please add it by clicking on the edit button.

MathWorks provides online tutorials to help you get started with the desktop and programming environment.

For an introduction to MATLAB have a look at the excellent tutorial and exercises in MATLAB for Psychologists.

Mike X. Cohen, MATLAB for Brain and Cognitive Scientists, MIT Press, 2017.

Wilson G, Aruliah DA, Brown CT, Chue Hong NP, Davis M, Guy RT, et al. (2014) Best Practices for Scientific Computing. PLoS Biol 12(1): e1001745. https://doi.org/10.1371/journal.pbio.1001745

For data sharing we recommend that you consider organizing your data along the lines of the BIDS standard. See The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments for an introduction and MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. The data2bids function helps to organize your data in the BIDS structure.

A good example for a data publication is given in A multi-subject, multi-modal human neuroimaging dataset, which includes MEG, EEG and fMRI. The dataset itself is available from OpenfMRI.

The Human Connectome Project (HCP) also provides good examples for data sharing and documentation. In Adding dynamics to the Human Connectome Project with MEG the MEG component of the HCP is described, which is available for download from the HCP website.

Analyzing Neural Time Series Data: Theory and Practice. by Mike X. Cohen.

Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques Donald B. Percival and Andrew T. Walden, 1993.

Bruns A. Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches? J Neurosci Methods. 2004 Aug 30;137(2):321-32.

The Brief History of the EEG Surface Laplacian by Paul L. Nunez explains how the surface Laplacian and SCD relate. The surface laplacian is further explained on the EGI website.

The following paper illustrates several problems associated with the lack of robustness and gives recommendations: Rousselet, G.A. & Pernet, C.R. (2012) Improving standards in brain-behavior correlation analyses. Frontiers in human neuroscience, 6, 119.

The blog post Correlations in neuroscience: are small n, interaction fallacies, lack of illustrations and confidence intervals the norm? by Guillaume Rousselet has some interesting observations and recommendations.

Michel, C.M. et al. EEG source imaging. Clin Neurophysiol, 2004; 115(10):2195-222.

Baillet, S and Mosher, J.C. Electomagnetic Brain Mapping IEEE Signal Processing Magazine, 2001; November:14-30.

The following paper is a review and gentle introduction into beamforming: Hillebrand A, Singh KD, Holliday IE, Furlong PL, Barnes GR. A new approach to neuroimaging with magnetoencephalography. Hum Brain Mapp. 2005 Jun;25(2):199-211.

Schoffelen JM, Gross J. Source connectivity analysis with MEG and EEG. Hum Brain Mapp. 2009 Jun;30(6):1857-65.

O’Neill GC, Barratt EL, Hunt BAE, Tewarie PK, Brookes, MJ. Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods. Physics in Medicine and Biology, 2015 60(21), R271–R295.