Correlations and t-tests of the minimum-norm data were calculated with R. Rosenthal's r was calculated as effect size [ 35].
Unconventional anatomically constrained signed minimum norm estimates of MEG data were most sensitive to the primary experimental manipulation, suggesting that the conventional unsigned unconstrained method is sub-optimal for studying written word processing.
Supplementary data 1 L2 minimum norm source estimations.
Minimum norm estimation provides chronometric and localization data showing that regions known to be involved in the mentalizing, "mirror neuron" and social perception networks have simultaneous activations between 100 and 700 ms post-stimulus, a period which may be thought as corresponding to early stages of social processes.
A major advantage of beamformer analysis relative to alternative source localisation techniques such as equivalent current dipole modelling or minimum norm estimation (which take evoked-average data as input) is the ability to image changes in cortical oscillatory power that do not give rise to a strong signal in the evoked-average response [11].
Occam's approach is an algorithm for generating a smooth minimum norm model to an appropriate fit of the data.
The algorithm used for this study (EXTERIORPTS in SOLO + MIA) uses the extremes of the mean-centered one-norm data as initial guesses based on a user defined threshold for the minimum norm value (a low threshold was used in this study to guarantee that contributions for low Z elements and paints used marginally would be extracted).
The underlying source current covariance matrix is diagonal, and the amplitude of its elements is estimated from the data, rather than sensor-source space geometry as used in weighted minimum norm solutions.
For these data, multiple, valid, binary, and variance fMRI priors proved best for a standard Minimum Norm inversion.
Using L2-based minimum norm estimate (MNE) and its variants, such as dynamic Statistical Parametric Mapping (dSPM), several studies demonstrated the added value of fusing EEG/MEG data using either simulated data (Liu et al. 2002), visual evoked responses (Sharon et al. 2007) and electrical median nerve stimulation (Molins et al. 2008).
65 (1970) 161) minimum norm quadratic unbiased estimator (MINQUE).
