ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2024
Evaluating the Feasibility of Visual Imagery for an EEG-Based Brain-Computer Interface.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Technical system of electroencephalography-based brain-computer interface: Advances, applications, and challenges.Neural regeneration research · 2026Article
- A Deep Learning Framework for EEG-Based Decoding of Visually Imagined Arrows with Different Colors and Directions.Biosensors · 2026Article
- Recent Progress in In-Ear EEG Technology and Its Emerging Real-World Applications: A Review.Micromachines · 2026Review
- A visual imagery paradigm for BCI strategies using imagined flickering patterns.Scientific reports · 2026Article
- An EEG Dataset for Visual Imagery-Based Brain-Computer Interface.Scientific data · 2026Article
- Recent Advances in Portable Dry Electrode EEG: Architecture and Applications in Brain-Computer Interfaces.Sensors (Basel, Switzerland) · 2025Review
- Using data from cue presentations results in grossly overestimating semantic BCI performance.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
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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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.