Selma Supek , Cheryl J. Aine (Eds.)
Springer; 2014 edition (August 8, 2014); 1013 pages; ISBN-13: 978-3642330445
Mike X Cohen
The MIT Press; 1 edition (January 17, 2014); 600 pages; ISBN-13: 978-0262019873
Peter Hansen, Morten Kringelbach, and Riitta Salmelin
OUP USA; 1 edition (29 July 2010); 448 pages; ISBN-13: 978-0195307238
Andrew C. Papanicolaou
Cambridge University Press; 1 edition (14 September, 2009); 220 pages; ISBN-13: 978-0521873758
In: E. Niedermeyer & F. Lopes da Silva (Editors); Electroencephalography – Basic principles, clinical applications and related field.
Philadelphia: Lippincott William & Wilkins, S. 1165-97; 2005. ISBN 0-7817-5126-8
Software related articles
The Journal "Computational Intelligence & Neuroscience" has released in early 2011 a special issue entitled "Academic Software Applications for Electromagnetic Brain Mapping Using MEG and EEG" featuring Sylvain Baillet, Karl Friston, and Robert Oostenveld as Guest Editors. This special issue includes among others an article on "FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data" and "EEG and MEG Data Analysis in SPM8".
Stolk, A., Todorovic, A., Schoffelen, J.M., and Oostenveld, R. (2013). Online and offline tools for head movement compensation in MEG. Neuroimage 68, 39-48. DOI:10.1016/j.neuroimage.2012.11.047
Abstract: Magnetoencephalography (MEG) is measured above the head, which makes it sensitive to variations of the head position with respect to the sensors. Head movements blur the topography of the neuronal sources of the MEG signal, increase localization errors, and reduce statistical sensitivity. Here we describe two novel and readily applicable methods that compensate for the detrimental effects of head motion on the statistical sensitivity of MEG experiments. First, we introduce an online procedure that continuously monitors head position. Second, we describe an offline analysis method that takes into account the head position time-series. We quantify the performance of these methods in the context of three different experimental settings, involving somatosensory, visual and auditory stimuli, assessing both individual and group-level statistics. The online head localization procedure allowed for optimal repositioning of the subjects over multiple sessions, resulting in a 28% reduction of the variance in dipole position and an improvement of up to 15% in statistical sensitivity. Offline incorporation of the head position time-series into the general linear model resulted in improvements of group-level statistical sensitivity between 15% and 29%. These tools can substantially reduce the influence of head movement within and between sessions, increasing the sensitivity of many cognitive neuroscience experiments.
Hardware related articles
Hamalainen, M., Hari, R., Ilmoniemi, R.J., Knuutila, J., and Lounasmaa, O.V. (1993). Magnetoencephalography - Theory, Instrumentation, and Applications to Noninvasive Studies of the Working Human Brain. Rev Mod Phys 65, 413-497. DOI: 10.1103/RevModPhys.65.413