R. Salmelin, J. Kujala, M. Liljeström, L. Parkkonen, R. Salmelin
Visitor: J. Gross (Düsseldorf, Germany)
Collaborator: Department of Neurology, Heinrich-Heine University, Düsseldorf, Germany
When using time-sensitive imaging techniques (e.g. MEG), subjects are shown a large number of isolated stimuli, or they perform a specific task several times (80-100 repetitions), and brain activity is averaged over the repetitions. This approach enhances the systematic task-related changes of cortical activation and reduces the effect of random background activity. For natural, continuous language tasks averaging of MEG signals with respect to fixed triggers is not possible or meaningful. Instead, one should be able to describe possible connections between different brain areas based directly on the time series of activation in these areas. In collaboration with the MEG group at the University of Düsseldorf, we have recently developed the first analysis and visualization tool for extracting cortico-cortical interaction strengths and interareal delays from MEG signals. So far, our novel method has been tested on analysis of simple finger movements. We are now developing DICS into a tool that can be directly applied to characterization of natural linguistic processes.
Gross J., Timmermann L., Kujala J., Salmelin R., Schnitzler A., Properties of MEG tomographic maps obtained with spatial filtering. Neuroimage (2003) 19, pp 1329-1336.
Tarkiainen A., Liljeström M., Seppä M., Salmelin R., The 3D topography of MEG source localization accuracy: effects of conductor model and noise. Clin Neurophysiol (2003) 114, pp 1977-1992.