Parallel processing of somatosensory information: Evidence from dynamic causal modeling of MEG data

The advent of methods to investigate network dynamics has led to discussion of whether somatosensory inputs are processed in serial or in parallel. Both hypotheses are supported by DCM analyses of fMRI studies. In the present study, we revisited this controversy using DCM on magnetoencephalographic (MEG) data during somatosensory stimulation. Bayesian model comparison was used to allow for direct inference on the processing stream. Additionally we varied the duration of the time-window of analyzed data after the somatosensory stimulus. This approach allowed us to explore time dependent changes in the processing stream of somatosensory information and to evaluate the consistency of results. We found that models favoring a parallel processing route best describe neural activities elicited by somatosensory stimuli. This result was consistent for different time-windows. Although it is assumed that the majority of somatosensory information is delivered to the SI, the current results indicate that at least a small part of somatosensory information is delivered in parallel to the SII. These findings emphasize the importance of data analysis with high temporal resolution.