Dr. Floris de Lange
Education:
| Obtained degree | Institution | Supervisor / Lab | Focus of work | ||||||||
| PhD (2003-2007) | Donders Institute, Nijmegen | Ivan Toni | Neural mechanisms of mental imagery / internal simulation of perception and action | ||||||||
Post-doctoral:
| Position | Institution | Supervisor / Lab | Focus of work | ||||||||
| post-doc (2007-2009) | Neurospin | Stanislas Dehaene | Conscious and unconscious decision-making | ||||||||
| tenure track PI (2009-2013) | Donders Institute, Nijmegen | founded by own lab (Predictive Brain Lab) | |||||||||
| tenured PI (2013-current) | Donders Institute, Nijmegen | Predictive Brain Lab | |||||||||
Talk title: Predictive neural representations in vision and beyond
We live in a largely predictable world. Capitalizing on this structure allows us to predict events and agents around us. The ability to predict future input is potentially useful for more efficient encoding, learning and recognition of input.
In my talk, I will discuss recent studies from my lab, investigating behavior and brain activity, in which we are trying to elucidate the nature of predictive processing. I will argue that the visual brain represents a temporally discounted representation of future expected states (aka successor representation). This representational format may lead to an efficient neural processing of expected input, and directs information sampling to situations of maximal uncertainty and surprise. I will illustrate this general principle in the realm of visual perception, natural language understanding and music.
About Dr. Floris de Lange:
In Dr. Floris de Lange’s work, he focuses on the question of how the processing of sensory information in the brain is shaped by various sorts of prior knowledge. It has become a popular notion that the brain may perform something akin to Bayesian inference during perception, optimally combining prior expectations with incoming data. The neural implementation of this algorithm, however, is still largely unclear. The Predictive Brain Lab sets out to better understand this interplay between knowledge and sensation. When, where and how does knowledge impinge on our perception? They use a complementary set of techniques (non-invasive brain measurements in humans, MEG and fMRI), behavioral measurements, and computational models to advance our understanding of this interplay.
Additional info (awards, memberships, extracurricular, etc)
- ERC Starting Grant, 2015
- ERC Consolidator Grant, 2020
- Ammodo award for fundamental science (2021)
- USERN prize in Social Sciences (2016)