top of page

research objectives & methods

coding efficiency in the human visual cortex

To reveal how knowledge allows our brain to better process sensory information, our objective is to determine if attention and expectation increase the efficiency with which image information is encoded in the human visual cortex. To this end we use trained deep constitutional neural networks to create 'feature-reduce' versions of natural images, and combine advanced psychophysical and fMRI methods to determine if expectation and attention increase the encoding of the most informative image features.    

speeding up information processing in the human brain

To reveal how knowledge allows our brain to faster process sensory information, we will measure 'brain-speed' as the time it takes to transform visual sensations into meaningful concepts of what we are looking at (semantics). This we will realize by synergizing state of the art knowledge on 'semantic distances' between images and multivariate analysis of EEG response patterns

changing information flow between brain areas

To gain more insights into how knowledge changes perception, we will unravel how expectations and attention change the way in which information flows between brain areas. To this end, we will measure how these two processes alter the similarity with which brain areas encode a wide range of images. This we realize by using fMRI and pattern analysis to measure 'representational geometry' for all cortical brain areas. Furthermore, we will combine this data with EEG data to determine the direction of observed effects. 

bottom of page