IEEE Transactions on Neural Systems and Rehabilitation Engineering (Jan 2024)

Evaluating the Feasibility of Visual Imagery for an EEG-Based Brain–Computer Interface

  • Justin Kilmarx,
  • Ivan Tashev,
  • Jose del R. Millan,
  • James Sulzer,
  • Jarrod Lewis-Peacock

DOI
https://doi.org/10.1109/TNSRE.2024.3410870
Journal volume & issue
Vol. 32
pp. 2209 – 2219

Abstract

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Visual imagery, or the mental simulation of visual information from memory, could serve as an effective control paradigm for a brain-computer interface (BCI) due to its ability to directly convey the user’s intention with many natural ways of envisioning an intended action. However, multiple initial investigations into using visual imagery as a BCI control strategies have been unable to fully evaluate the capabilities of true spontaneous visual mental imagery. One major limitation in these prior works is that the target image is typically displayed immediately preceding the imagery period. This paradigm does not capture spontaneous mental imagery as would be necessary in an actual BCI application but something more akin to short-term retention in visual working memory. Results from the present study show that short-term visual imagery following the presentation of a specific target image provides a stronger, more easily classifiable neural signature in EEG than spontaneous visual imagery from long-term memory following an auditory cue for the image. We also show that short-term visual imagery and visual perception share commonalities in the most predictive electrodes and spectral features. However, visual imagery received greater influence from frontal electrodes whereas perception was mostly confined to occipital electrodes. This suggests that visual perception is primarily driven by sensory information whereas visual imagery has greater contributions from areas associated with memory and attention. This work provides the first direct comparison of short-term and long-term visual imagery tasks and provides greater insight into the feasibility of using visual imagery as a BCI control strategy.

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