Moritz Grosse-Wentrup
search externally:   Google Scholar,   Springer,   CiteSeer,   Microsoft Academic Search,   Scirus ,   DBlife


My primary research interest is developing new methods for non-invasive brain-computer interfaces (BCIs). BCIs are devices that allow subjects to communicate by intentionally modulating the electromagnetic field of the brain. While nowadays most healthy subjects are capable of operating a BCI that allows basic communication, up to date subjects in late stages of amyotrophic lateral sclerosis (ALS) have failed to communicate by means of a BCI. It is my conviction that in order to advance the current state-of-the-art in BCIs, and enable BCI-communication for subjects in late stages of ALS, we need a better understanding how different brain regions interact in order to solve specific (BCI-related) tasks.

Accordingly, my research focuses on developing and applying methods for connectivity/causal inference in neuroimaging data. Approaches I currently pursue include

  • Network information theory
  • Causal Bayesian networks
  • Granger causality.

It is a particular concern of mine to foster exchange between neuroimaging and machine learning, e.g. by organizing the NIPS 2009 Workshop on Connectivity Inference in Neuroimaging.

I am also interested in spatial filtering for BCIs, particularly in

  • Beamforming
  • Multiclass Common Spatial Patterns
  • Independent Component Analysis.


flag An introduction to causal inference in neuroimaging
as author at  BBCI Winter School on Neurotechnology, Berlin 2014,
flag Video Journal of Machine Learning Abstracts - Volume 4
as author at  Video Journal of Machine Learning Abstracts - Volume 4,
together with: John Shawe-Taylor (editor), Alfons Juan-Císcar (editor), Samuel Kaski (editor), Davor Orlič (editor), Jan Rupnik,