I am particularly interested in functional neuroimaging and connectivity analyses. I aim to complement these methods with Bayesian computational modelling to investigate the functional architecture underlying mismatch processing. I believe the resulting study of the asynchrony between top-down and bottom-up signalling may be highly informative for investigating general computational theories of brain function, with a focus on the predictive coding framework. The current goal will be to study these cortical dynamics on various levels.

Additionally, my interests include neuropsychopharmacology and its application in brain disorders and the study of consciousness.

Grundei, M., Schröder, P., Gijsen, S., & Blankenburg, F. (2023). EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision. Human Brain Mapping, 1–25. https://doi-org.unimib.idm.oclc.org/10.1002/hbm.26303

Gijsen, S., Grundei, M., & Blankenburg, F. (2022). Active inference and the two-step task. Scientific Reports, 12:17682. doi: https://doi.org/10.1038/s41598-022-21766-4

Gijsen, S*., Grundei, M.*, Lange, R. T., Ostwald, D., & Blankenburg, F. (2021). Neural surprise in somatosensory Bayesian learning. PLoS computational biology, 17(2), e1008068. https://doi.org/10.1371/journal.pcbi.1008068

*equal contribution