Spatiotemporal Models

Traditionally, data analysis methods for fMRI data have primarily used time-series models whereas in M/EEG the analysis methods required for source reconstruction have been primarily spatial. It is the working hypothesis of this project that both M/EEG and fMRI could benefit from a full spatio-temporal analysis.

For fMRI this requires augmenting time series models with spatial priors and for M/EEG augmenting spatial with temporal models. We have shown that these methods provide neuroscientists with more sensitive detection tools. This allows them to find subtle neuronal activations that would otherwise be obscured in experimental noise.

The picture above shows bilateral activation of occipital cortex (in red) obtained using a spatial wavelet prior. This provides much better resolution than the standard approach of `smoothing the data’. My colleague Lee Harrison has used such methods to establish that anterior brain regions integrate information over longer time periods than posterior regions.

This project is an ongoing collaboration with a number of researchers including Nelson Trujillo-Barreto (Havana), Lee Harrison, Guillaume Flandin and Maria Joao (all from UCL).