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Join the Data-Driven Neurotechnology Lab! Let’s leverage machine learning techniques to enhance brain-computer interfaces! If you are interested also in the psychology of learning and self-introspection, then join our team and the European Doctoral Network DONUT as PhD candidate!

We are investigating a novel method for a gaze-independent visual brain-computer interface (BCI) for communication, which could potentially be used by users who cannot communicate anymore, for instance ALS patients. For this project, we are recruiting healthy participants aged 18-35 years.

We are looking for two highly skilled PhD candidates to set up closed-loop brain-computer interface (stimulus) protocols with the human user in the loop, and to evaluate brain signals and the task performance of users.

The Doctoral Network for Neural Prostheses and Brain Research (DONUT) project, a large European consortium that will host 10 PhD condidates, has started. We are happy to collaborate with 15 academic and industrial partners included in this consortium.

In collaboration with our colleagues from Radboud University Medical Center, we are looking for a highly skilled PhD candidate. The research project focuses on deep learning methods to obtain objective rating of the severity of Parkinson’s disease based on video- and audio recordings and based on signals collected by wearables.

The data collection of this study has finished We are investigating novel methods for a visual brain-computer interface (BCI) for communication, which could potentially be used by users who cannot communicate anymore, for instance ALS patients.

New article on deep learning-based embeddings for BCI data published at the IEEE conference on Metrology for eXtended Reality, Artificial Intelligence, and Neural Engineering (MetroXRAINE). More details here: Pierre Guetschel, Thoedore Papadopoulo, Michael Tangermann (2022).

The Dutch Brain Interfacing Initiative, a large scale research project funded by the Dutch Research Counsil, has started. We are happy to team up with colleagues from multiple Dutch research institutions to tackle the challenges provided by this 10-year endeavour!

We are investigating a novel language training method based on an auditory BCI system, which shall be applied to patients after stroke. For this project, we are recruiting healthy participants aged 45-80 years who are native speakers of Dutch.

Pierre Guetschel won the Best Poster Award in the Theme 4: Natural Computing & Neurotechnology category at the Donders Poster Session 2022. The work he presented focused on learning EEG representations to reduce the calibration duration of BCI applications.