Springe direkt zu Inhalt

Johannes Singer

Johannes Bild

Neural Dynamics of Visual Cognition Group

PhD Candidate

Habelschwerdter Allee 45
Room JK 25/228
14195 Berlin

I joined the lab in March 2021. Before that, I obtained a bachelor’s degree in psychology from the University of Salzburg and a master’s degree in neuro-cognitive psychology from the Ludwig-Maximilians-University in Munich.

For my master thesis, I worked at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig with Dr. Martin Hebart on a project investigating the representation of abstract object images (eg. drawings, sketches) in deep neural networks and human behavior.

When I am not in the lab I like playing the guitar and drums, longboarding and going to concerts.

For more details see my CV.


General research interests: 

I am generally interested in the spatio-temporal dynamics of visual processing and how these dynamics can be modelled and better understood by using deep neural networks. In my research I use a combination of M/EEG, fMRI, multivariate pattern analysis methods and computational modelling (e.g. deep learning). I am co-supervised by Dr. Martin Hebart and I am an affiliated researcher with the Vision and Computational Cognition group at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig. 

My research is currently funded by the DFG (German Research Foundation). The project runs at least until March 2023. 

At the moment I have two ongoing research projects which are described below. 

Research projects: 

Project 1: In the first project of my PhD I will investigate the spatio-temporal dynamics of object recognition for images across different levels of visual abstraction (e.g. drawings, sketches). For this, I combine MEG and fMRI data by using representational similarity analysis to resolve the neural dynamics during object recognition in both space and time. This project is carried out in collaboration with Dr. Martin Hebart (MPI Leipzig).

Project 2: The second project will be concerned with the question of which visual features (simple vs. complex) the brain relies on for perceptual decision making. To test this, I will generate stimuli that are maximally controversial in terms of simple and complex visual features by using deep learning. Subsequently, I will show these images to participants in the MRI and will ask which features are most associated with the decision making in human behavior when simple and complex features predict different decisions about an image. This project is carried out in collaboration with Prof. Obermayer (TU Berlin).

Student supervision & opportunities 

I am currently supervising Ülkü Tonbuloglu (Msc student, Free University Berlin). 

I am not actively looking for interns or thesis students. However, if the above mentioned projects sound interesting to you feel free to contact me to discuss the possibilities.