Employing experiments that range from studying isolated pairs of lobster neurons to looking at electrical and magnetic signals from human test subjects, physicists are applying concepts from nonlinear systems, chaos and control theory to improve our understanding of neuronal dynamics. Exemplifying this approach, a collaboration in Germany between neurologists at the University of Düsseldorf and physicists at the University of Potsdam has recently demonstrated the potential of a new nonlinear analysis technique—phase synchronization—for neuronal studies. With this tool, the researchers found evidence in magnetoencephalography (MEG) data for synchronous activity between different parts of the brain and between the brain and the muscles during the tremor of a patient with Parkinson's disease (see the figure below).

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