Flashing characters with famous faces improves ERP-based brain–computer interface performance

By Tobias Kaufmann, Stefan M. Schulz, C. Grünzinger, Andrea Kübler. Journal of Neural Engineering, 2011

303 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/382ff8ea2ea9ffd95d1307752b8dcec2c2fc8d51

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Brendan Z. Allison
2. Andrea Kübler
3. Eric W. Sellers
4. Christoph Guger
5. Reza Fazel-Rezai
6. Sonja C. Kleih
7. Ivan Volosyak
8. Jonathan R. Wolpaw

In Electrical and Electronic Engineering

1. Ivan Volosyak
2. Andrea Kübler
3. Christoph Guger
4. Brendan Z. Allison
5. Eric W. Sellers

Citations in the corpus

• P300 brain computer interface: current challenges and emerging trends (2012, methodology): “Familiar faces, which are known to elicit the N170 and N400f (“f” for faces) components of the ERP (Eimer, 2000), have also been used in a P300 BCI (Kaufmann et al., 2011).”
• EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy (2019, unknown): “To enhance the signal quality, two additional settings were incorporated into theoriginalrow-columnspellerdesign,namely,random-setpre-sentation [45] and face stimuli [39].”
• Brain–Computer Interface Spellers: A Review (2018, background): “In [50], a 6 × 6 Matrix Speller was described; however, each character was superimposed by a semitransparent picture of a familiar (famous) face.”