Écompleted her PhD on EEG correlates of musical imagery, with specific attention to rhythm, supervised by Peter Desain. Her work was embedded in an STW-funded project: 'On-line interpretation of Imagined Temporal Patterns from EEG: The next step towards neuronal control of motor and communication prostheses.'
Abstract: The BCI-project embedded in the Music, Mind, Machine Group aims to combine recent advances in brain imaging and signal processing to develop new tools for direct man-machine interaction through a so-called Brain-Computer Interface (BCI).
The key idea of this project is to use temporal modulation of EEG by imagining temporal patterns, such as musical rhythm, imagining a task at a frequency of 1Hz or a Morse-like code, to enhance the correct decoding rate by exploiting the time-dimension more fully than has been done in BCI-research untill now. Traces of neural activity caused by mental imagery are picked up by sensors (EEG) and are classified into discrete categories.
The approach used here is to use non-invasive techniques, and discrete (symbolic) output. Eventually, the system itself will be adaptive to recognize EEG patterns as representations of response categories on the basis of previous measurements, instead of relying on intensive (bio-feedback) training of the user.
For this project, we collaborate with the Biophysics Department of Radboud University, as well as the St. Maartenskliniek for rehabilitation in Nijmegen.