Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm.

A general Bayesian treatment for MEG source reconstruction incorporating lead field uncertainty.

There is uncertainty introduced when a cortical surface based model derived from an anatomical MRI is used to reconstruct neural activity with MEG data. This is a specific case of a problem with uncertainty in parameters on which M/EEG lead fields depend non-linearly. Here we present a general mathematical treatment of any such problem with a particular focus on co-registration. We use a Metropolis search followed by Bayesian Model Averaging over multiple sparse prior source inversions with different headlocation/orientation parameters. Based on MEG data alone we can locate the cortex to within 4mm at empirically realistic signal to noise ratios. We also show that this process gives improved posterior distributions on the estimated current distributions, and can be extended to make inference on the locations of local maxima by providing confidence intervals for each source.

Genotoxic effects of niclosamide in Aspergillus nidulans.

A 2-5-month treatment with niclosamide, a widely used drug in developing countries, has been reported to induce lymphosarcomas in toad liver and kidney. The genotoxic effects of this drug have also been evaluated in Salmonella typhimurium, in somatic and germinal cells of mice and in human lymphocytes exposed in vitro and in vivo. The present study shows that niclosamide is also capable of inducing mitotic crossing-over and non-disjunction in Aspergillus nidulans, which points to the wide potential of this drug as a genotoxic agent.