Reading Imagined Letter Shapes from the Mind’s Eye Using Real-time 7 Tesla fMRI
Open accessAbstract
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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It is currently possible to accurately predict human cortical receptive field mapping based on anatomical scans or other retinotopic mapping strategies that do not rely on visual input.
“it is currently possible to accurately predict human cortical receptive field mapping based on anatomical scans (Benson et al., 2012; Benson et al., 2014), or other retinotopic mapping strategies that do not rely on visual input (Goebel et al., 2022; Bock et al., 2015).”
From Towards biologically plausible phosphene simulation for the differentiable optimization of visual cortical prostheses (2024) · cites this paper as Goebel et al., 2022
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Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946 · see citing works
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van der Grinten, M., de Ruyter van Steveninck, J., Lozano, A., Pijnacker, L., Rueckauer, B., Roelfsema, P., van Gerven, M., van Wezel, R., Güçlü, U., & Güçlütürk, Y. (2024) · eLife · doi:10.7554/elife.85812 · Cited by 39 · see citing works
“Thanks to the machine learning compatibility, the model can also be used for the pre-operative optimization of the implant placement and design ( van Hoof, 2022 ).”
Methodvan der Grinten, M., de Ruyter van Steveninck, J., Lozano, A., Pijnacker, L., Rückauer, B., Roelfsema, P., van Gerven, M., van Wezel, R., Güçlü, U., & Güçlütürk, Y. (2022) · doi:10.1101/2022.12.23.521749 · Cited by 39 · see citing works
- Authors
- Goebel, R., van Hoof, R., Bhat, S., Luhrs, M., & Senden, M.
- Affiliations
- Maastricht University (NL)
- Maastricht University,Department of Cognitive Neuroscience,Maastricht,Netherlands
- Venue
- 2022 10th International Winter Conference on Brain-Computer Interface (BCI)
- Publisher
- IEEE
- Published
- 2022-02-21
- Pages
- 1-3
- OpenAlex
- W4220804474
- Cited by
- 8
- References
- 1
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 1
- FWCI
- 3.23
- Type
- conference paper
- Language
- en
- Open access
- Locations
- International Winter Conference on Brain-Computer Interface (BCI) (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- brain-computer interface, early visual cortex, population receptive field mapping, retinotopic mapping, real-time fMRI, denoising autoencoder, neural decoding, visual feedback
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