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Contact

For the possibility of internships or lab visits, please contact Mario Senden via mario.senden@maastrichtuniversity.nl


Department of Cognitive Neuroscience

Maastricht University

Oxfordlaan 55
6229EV Maastricht





Department of Cognitive Neuroscience

Maastricht University

Oxfordlaan 55
6229EV Maastricht



Reading Imagined Letter Shapes from the Mind’s Eye Using Real-time 7 Tesla fMRI


Journal article


R. Goebel, R. V. Hoof, Salil Bhat, M. Lührs, M. Senden
Balkan Conference in Informatics, 2022

Semantic Scholar DBLP DOI
Cite

Cite

APA   Click to copy
Goebel, R., Hoof, R. V., Bhat, S., Lührs, M., & Senden, M. (2022). Reading Imagined Letter Shapes from the Mind’s Eye Using Real-time 7 Tesla fMRI. Balkan Conference in Informatics.


Chicago/Turabian   Click to copy
Goebel, R., R. V. Hoof, Salil Bhat, M. Lührs, and M. Senden. “Reading Imagined Letter Shapes from the Mind’s Eye Using Real-Time 7 Tesla FMRI.” Balkan Conference in Informatics (2022).


MLA   Click to copy
Goebel, R., et al. “Reading Imagined Letter Shapes from the Mind’s Eye Using Real-Time 7 Tesla FMRI.” Balkan Conference in Informatics, 2022.


BibTeX   Click to copy

@article{r2022a,
  title = {Reading Imagined Letter Shapes from the Mind’s Eye Using Real-time 7 Tesla fMRI},
  year = {2022},
  journal = {Balkan Conference in Informatics},
  author = {Goebel, R. and Hoof, R. V. and Bhat, Salil and Lührs, M. and Senden, M.}
}

Abstract

We present a 7 Tesla fMRI proof-of-concept study of the first letter speller BCI that decodes imagined letter shapes from activity patterns in early visual cortical areas. New tools are developed to enable real-time population receptive field retinotopic mapping for encoding and decoding. Using two different letter shapes (H and T), classification performance of generated activity patterns during imagery reaches 80% accuracy in each individual. Using a denoising autoencoder, recognizable letter shapes could be reconstructed and displayed as feedback to participants in the scanner.


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