Echtzeit-Neurofeedback auf den Ruhezustand des Gehirns: Evaluation des therapeutischen Nutzens zur Anfallsreduktion bei Epilepsie
Final Report Abstract
Functional imaging of the brain at rest consistently reveals broad motifs of correlated activity, which have been termed resting state networks. Alterations of the resting state networks have been found in neurological and psychiatric diseases. Yet, the actual neurophysiological processes underlying these resting state networks remain to be uncovered, because fMRI only indirectly measures the neuronal activity. During my research fellowship at the Montreal Neurological Institute we used magnetoencephalography (MEG) during rest to analyze the resting state networks and their underlying neurophysiology. We demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signalling for long-range brain communication. These results will in the future help to understand changes seen in diseases of the brain. In the second part of the project it was shown that subjects can be trained with MEG to alter their ongoing brain activity. This first feasibility study opens up now the potential for developing therapeutic approaches in neurological or psychiatric diseases. These often show altered brain activity and helping patients to alter the brain activity might thus improve their symptoms. In my future research I plan to further test our results from MEG on the resting state through direct combined recordings of fMRI and neuronal data. The research fellowship at the MNI was very valuable to me, because I learned with MEG a new research technique and could develop based on the results at the MNI future research projects.
