Donders Institute for Brain, Cognition and Behaviour

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Brain oscillations have been linked to cortical information processing and routing. Thus, those patterns seem to reflect fundamental principles of neuronal communication. Alpha oscillations are thought to moderate the signal flow between brain areas, while gamma oscillations were found to reflect direct computations on the features and their respective cross-area signalling. Both frequency bands have been differentially related to feedback and feedforward processes anatomically implemented across differ-ent cortical layers. To investigate alpha, beta and gamma oscillations during feature selective stimulus processing on a laminar level, a simultaneous EEG-fMRI experiment was set up. Left and right ori-ented Tukey-filtered gratings, served as feature manipulation. Layer specific fMRI signals were obtained through a spatial regression, fitting a feature specific activation template for superficial middle and deep layers to the recorded BOLD activity in V1, V2 and V3. The obtained surrogate feature and layer specific BOLD signals were correlated with source level time-frequency data responses for alpha, beta and gamma bands. Virtual channel data reconstructed using an LCMV beamforming approach was used for that purpose. Due to the novelty of the presented approach, an extensive piloting phase was planned to establish the measurement and analysis protocol. This thesis aims to summerize those findings. It will be demonstrated that all major technical and methodological questions were addressed successfully. Implications for the "real" experiment as well as the potential outcomes of this study are discuss.
Faculteit der Sociale Wetenschappen