Predicting text from electroencephalography (EEG) recordings / Fall 2018 - Master Thesis
We have recorded a new dataset  of simultaneous eye-tracking and EEG recording while subjects are reading natural sentences. A research questions that has not been explored until now, due to the lack of data, is whether words or syntactic categories can be predicted from EEG signals. Can a system be built that predicts the next word a person is reading in a sentence purely by his EEG signal?
Even a negative research result to this hypothesis, will greatly advance our knowledge of the components of EEG signals and will facilitate future projects. If necessary, more data can be recorded.
Supervised by Nora Hollenstein
-  Hollenstein, N., Langer, N., Pedroni, A., Troendle, M., Rotsztejn, J., & Zhang, C. (2018, May 28). Zurich Cognitive Language Processing Corpus: A simultaneous EEG and eye-tracking resource to analyze the human reading process. Retrieved from osf.io/q3zws