Postdoctoral Research Fellow: Laminar Computations of Sensory Surprise

We are looking for a postdoctoral researcher with expertise in neuroimaging and an interest in the predictive brain to participate in the ERC Consolidator project SURPRISE. The goal of this project is to advance our understanding of how the human brain uses prediction error to guide perception and behaviour.

Computational models of perception have proposed that each cortical area has an explicit representation of surprise, which represents the mismatch between predictions and input. Specifically, there may be a separation between input, predictions, and prediction error signals within the neocortex by virtue of their distinct laminar profile: neurons in the deep layers of the cortex may represent hypotheses about the causes of our sensory inputs, whereas neurons in the superficial layers represent the mismatch between these hypotheses and current inputs: prediction errors.

The aim of this research project is to empirically address this question by using ultra-high field (7T) fMRI to distinguish neuronal activity within the different layers of the visual cortex in humans. You will be involved in designing critical experiments to isolate computations related to prediction and surprise. You will also be involved in the collection and, most notably, analysis of 7T fMRI data at laminar resolution to examine layer-specific neural activity modulations induced by prediction and surprise.