Faculty member

Research Interests

How does our brain allow us to make sense of our visual world? Our group works on unraveling the cascade of visual and semantic processing in the human brain and discover how the emerging representations allow us to interact effectively with our environment. To achieve this aim, we combine large-scale behavioral studies and densely sampled functional MRI and MEG with state-of-the-art artificial intelligence methods of vision and semantics (convolutional neural networks and large language models).

Available PhD projects

(1) What is the role of context in our mental representations of objects? We have acquired a massive behavioral dataset that allows addressing this question from a behavioral perspective, using computational modeling. This could be complemented by MEG and fMRI studies focused on the role of visual and semantic context. Useful backgrounds are Experimental Psychology or Cognitive Science with strong programming skills in Python, ideally with previous experience in fMRI or MEG.

(2) What are the core representational dimensions underlying visual brain regions? This project would look at this question using deep learning and computational modeling applied to existing or newly-acquired large-scale fMRI or MEG data. Useful background are Computer Science or Psychology/Cognitive Science with strong programming skills.

(3) Improving the speed of functional MRI: what is the ideal presentation rate for functional MRI studies? Recent evidence indicates that we can present stimuli at a much faster pace than previously thought, which would offer the potential for massive gains in statistical efficiency. The project would involve simple models of the neural dynamics underlying the BOLD signal. This is targeted at students with any background with good programming skills in Python or Matlab, good quantitative skills, and a desire to play around with data. Previous fMRI experience is a plus.

 

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