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Hi Members, I am collecting multimodal neuroimaging data on human subjects for emotions. As you know, there is space and time tradeoff for every kind of neuroimaging. To deal with this tradeoff, I am designing the experiment using EEG-sMRI and simultaneous EEG-fMRI. With EEG-sMRI, I will be getting both time resolution and space resolution but, as you know, the inverse modeling is not based on particular solution but optimal solution. Moreover, it is not possible to get the information about subcortical processing with source localization technique. However, with the sMRI, one can do imaging upto 1x1x1 mm voxel size. With this spatial resolution features and functions which are lumped together can be analyzed separately. That means high spatial resolution but with poor coregistration and reachability. The limitation of poor coregistration and reachability up to subcortical nuclei can be compensated using simultaneous EEG-fMRI recording. But with 3T machine the limitation is voxel size. In both kind of collected data I want to analyze dynamic causal interaction. Please suggest me if I am heading in the right direction. Thanks & Best, Sudhakar Mishra Research Scholar