Prof. Dr. Daniel Kaiser
Spatiotemporal prediction in the cortical processing of natural visual information
Predictive processing theories view cortical feedback mechanisms as essential for vision in natural environments. Although recent research shows that feedback is coded in specific brain rhythms, we do not know enough about how such oscillatory feedback orchestrates key computations in perception.
In this project, we employ a combination of spatially, temporally, and spectrally resolved neural recordings and computational modelling to resolve how predictive feedback supports two critical computations in real-world environments:
(1) the integration of information across visual space, and
(2) the interpolation of information that is momentarily unavailable