Magnetic resonance-based eye tracking using deep neural networks

DeepMReye is an open-source deep-learning framework for eye tracking in fMRI without camera. It reconstructs viewing behavior from the MR-signal of the eyeballs. It works even in existing datasets and when the eyes are closed.

The Paper, Code, Data & User Documentation are all open access!

Functional imaging of the human medial temporal lobe.
A neuroscientist's guide to fMRI pulse sequence optimization

The medial temporal lobe (MTL) is difficult to image with fMRI due to magnetic field inhomogeneities and low signal-to-noise ratios. Here, I compiled some information about fMRI pulse sequences and how they affect your data, along with a few tips on how to get a good signal in the MTL. Find it here on Open Science Framework!

Behavioral encoding modeling

This code creates, fits & tests an encoding model of virtual head direction using simulated fMRI voxel time courses.

It can be easily adapted for other behavioral domains & imaging techniques (MEG, 2p-imaging...) to study the neural underpinnings of behavior across species.


HERE you find my fMRI crash course slides, covering the MR-imaging basics, data preprocessing, the general linear model and simple analyses.

HERE you find my lecture slides on visual field mapping.