Novel Source Localisation Approaches in MEG-Data: Basic and Clinical Applications

Chair

Michael Wibral und Peter J. Uhlhaas

Abstract

The past years have seen an important conceptual shift in algorithms for the electromagnetic inverse problem. Solutions that took into account only the geometry and properties of the head's tissue compartments have been replaced by adaptive measures that search for a solution that is optimally tailored to the data, most notably Beamforming and Bayesian approaches. Beamforming approaches are particularly suited to identify the sources of sustained oscillatory brain activity. Bayesian approaches promise to solve the decision problem between sparse and distributed solutions optimally. In the proposed symposium we will present results from the application of these novel source analysis algorithms to real world data, highlighting both gains and potential pitfalls. The invited speakers will cover beamforming analysis and Bayesian source analysis of data from experiments with clinical populations and data from normal populations that establish novel relations between source-related activity and cognitive processes.

Beiträge

• Source localization of high-frequency oscillations reveals widespread reductions in gamma-band activity in schizophrenia patients
  Grützner, C., Wibral, M., Kohler, A., Singer, W., Maurer, K., and Uhlhaas, P. J.
• Beaming memories: source localization of gamma oscillations reveals functional working memory network
  Roux, F., Mohr, H., Triezmielewska, J., Wibral, M., Singer, W., and Uhlhaas, P. J.
• MEG source analysis in SPM
  Mattout, J.
• Changes in local gamma power and functional connectivity with consolidation of declarative memory
  Nieuwenhuis, I. L. C., Takashima, A., Oostenveld, R., Fernández, G., and Jensen, O.
• Neuronal oscillations reveal the where and what of human working memory: an MEG source localization study
  Supp, G. G., Engel, A. K., and Hipp, J. F.