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

R. Goebel*, R. van Hoof, S. Bhat, M. Luhrs, M. Senden

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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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.
Original languageEnglish
Title of host publication10th International Winter Conference On Brain-computer Interface (Bci2022)
PublisherIEEE
Number of pages2
ISBN (Print)9781665413374
DOIs
Publication statusPublished - 2022
Event10th International Winter Conference on Brain-Computer Interface (BCI) - High1 resort, Korea, Republic of
Duration: 21 Feb 202223 Feb 2022
https://brain.korea.ac.kr/bci2022/

Publication series

SeriesInternational Winter Conference on Brain-Computer Interface BCI
ISSN2572-7672

Conference

Conference10th International Winter Conference on Brain-Computer Interface (BCI)
Abbreviated titleIEEE
Country/TerritoryKorea, Republic of
Period21/02/2223/02/22
Internet address

Keywords

  • fMRI
  • letter speller
  • imagery
  • population receptive fields
  • denoising autoencoder

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