Uncertainty calibration in Bayesian M/EEG source imaging

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Bayesian methodssource imaginguncertainty quantificationM/EEG

2611.06979

Builder Relevance

70%

3h ago

Abstract

The paper presents a simulation-based framework for uncertainty quantification and calibration in Bayesian M/EEG source imaging.

Reality Card

Core Claim

SBL+S-FLEX provides more focal localization and tighter uncertainties than BMN+sLORETA, suggesting greater statistical power for identifying bilateral auditory sources.

Method / Result

SBL+S-FLEX yields lower Wasserstein localization error and smaller posterior uncertainty compared to BMN+sLORETA.

Limitations

Residual miscalibration remains, and transfer across mismatched SNR, sparsity, and head models is condition dependent.

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