Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details.

By Roberto D. Pascual-Marqui. Methods and Findings in Experimental and Clinical Pharmacology, 2002

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View Paper: https://www.semanticscholar.org/paper/6908a6e13a1aff03007d8478129403dbcbd6f348

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Citations in the corpus

Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization (2007, methodology): “19: ( )T α += +C KK H gives the sLORETA method (Pascual-Marqui 2002), where is the regularization parameter.”
A phase I trial of deep brain stimulation of memory circuits in Alzheimer's disease (2010, unknown): “images of statistically standardized current density distributions on a cortical grid of 6,239 voxels with accurate localization.(45)”
Microstates in Resting-State EEG: Current Status and Future Directions (2014, methodology): “Microstates are relatively easy to compute, and a few freely available software programs exist to help perform the analysis (Pascual-Marqui, 2002, Brunet et al., 2011, Koenig et al., 2011).”
A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data (2006, unknown): “In the Results section, we show performance of SAKETINI relative to MVAB and sLORETA (Pascual-Marqui, 2002) both in localization ability and in time course estimation for MEG data.”
A unified Bayesian framework for MEG/EEG source imaging (2009, unknown): “In this context, the inclusion of R as a normalization factor helps to compensate for depth bias, which is the propensity for deep current sources within the brain to be underrepresented at the scalp surface (Pascual-Marqui, 2002; Ramírez, 2005).”
MEG and EEG data analysis with MNE-Python (2013, unknown): “The most popular of these is the software namesake MNE, which stands for Minimum-Norm Estimate (Wang et al., 1992; Hämäläinen and Ilmoniemi, 1994), and its variants which include dSPM (Dale et al., 2000) and sLORETA (Pascual-Marqui, 2002).”
Electrophysiological Imaging of Brain Activity and Connectivity – Challenges and Opportunities (2011, background): “(LORETA) that further considers spatial smoothness of the neural activity [24], and their statistical analysis [27].”
Multiple sparse priors for the M/EEG inverse problem (2008, unknown): “ReML or restricted maximum likelihood was introduced by Patterson and Thompson (1971) as a technique for estimating variance components, which accounts for the loss in degrees of freedom that result from estimating fixed effects (Harville, 1977).”
Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. (2002, methodology): “In an accompanying paper in this issue (Pascual-Marqui, 2002), the new imaging method sLORETA is fully described.”
EEG source imaging. (2004, methodology): “The idea of normalization as a second step in the inverse solution has also been used by Dale et al. (2000) and by Pascual-Marqui (2002) in the sLORETA method.”
EEG-vigilance and BOLD effect during simultaneous EEG/fMRI measurement (2009, unknown): “The sLORETA software provides the possibility to locate intracortical sources of EEG activity (Pascual-Marqui, 2002).”
MNE software for processing MEG and EEG data (2013, methodology): “To quantify the statistical significance of the current estimates, noise normalization techniques have been developed (Dale et al., 2000; Pascual-Marqui, 2002) yielding a dimensionless statistical score instead of dipole amplitudes in units of ampere-meter (Am).”
Physicians down-regulate their pain empathy response: An event-related brain potential study (2010, methodology): “sLORETA enables the computation of statistical maps from EEG data that indicate the locations of the underlying source processes with low error (Pascual-Marqui, 2002).”
Penalized Least Squares Regression Methods and Applications to Neuroimaging (2010, unknown): “We refer the reader to Scherg and Voncramon (1986); Mosher and Leahy (1998); Uutela et al. (1999); Hämäläinen and Ilmoniemi (1994); Silvaa et al. (2004); Valdés-Sosa et al. (2009) and Pascual-Marqui et al. (1994); Pascual-Marqui (2002) among many others.”
Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks (2010, methodology): “The version of LORETA employed in the present study used the digitized Talairach atlas estimating the current source density distribution for 40ms epochs of brain electrical activity (Pascual-Marqui, 2002).”