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Bayesian

Bayesian methods use probabilistic frameworks to estimate source activity, incorporating prior knowledge about source distributions. They can provide uncertainty estimates and often yield sparser solutions than minimum norm methods.

This category contains 14 solvers.

Solvers

Full Name Solver ID Description
Bayesian Compressive Sensing BCS Sparse Bayesian inverse method based on Bayesian compressive sensing, using hierarchical priors to promote sparse sou...
Champagne (Sparse Bayesian Learning) Champagne Sparse Bayesian learning method for M/EEG/EEG source imaging using Type-II maximum likelihood / evidence maximization...
Noise-Learning Champagne Champagne-NL Champagne sparse Bayesian learning variant that jointly estimates per-channel noise parameters/covariance while updat...
Flex-Champagne FLEX-CHAMPAGNE Flexible-extent Champagne variant using a multi-order diffusion-smoothed leadfield dictionary to jointly select sourc...
Flex-NL-Champagne FLEX-NL-CHAMPAGNE Two-pass refined flexible-extent Champagne variant using a multi-order diffusion dictionary with Convexity/MM updates...
Gamma Maximum A Posteriori Gamma-MAP Sparse Bayesian inverse solution using a Gamma hyperprior (ARD-style) within the unified Bayesian source imaging fram...
Gamma MAP with MSP Priors Gamma-MAP-MSP Gamma-MAP sparse Bayesian inverse approach combined with MSP-style spatial smoothness/patch priors.
Multiple Sparse Priors MSP Bayesian source imaging method that combines multiple spatial priors and estimates their hyperparameters with Restric...
OmniChampagne OMNI-CHAMPAGNE Adaptive sparse Bayesian solver that selects between a dipole-only Champagne-style model and a multi-order patch-dict...
SubspaceSBL (SSM + NL-Champagne) SUBSPACE-SBL Two-stage solver that detects sources with signal subspace matching and refines amplitudes/noise parameters using NL-...
Source Maximum A Posteriori Source-MAP Sparse Bayesian inverse solution computing a source MAP estimate in the unified Bayesian source imaging framework.
Source MAP with MSP Priors Source-MAP-MSP Source-MAP sparse Bayesian inverse approach augmented with MSP-style spatial priors/patch smoothing (conceptually rel...
Variational Bayes Sparse Bayesian Learning VB-SBL Variational Bayesian ARD/SBL solver with Gamma hyperpriors, implemented with efficient sensor-space updates.
Coherent Maximum Entropy on the Mean cMEM Maximum-entropy-on-the-mean approach using graphical models and parcel-wise optimization (data-driven parcellation) t...