ArticleFrontiers in human neuroscience2021
Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces.
Article in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 45 citations in OpenAlex.
- Dynamics of cortical excitability in stimulus-response mapping for overt and covert movements is locked to visual stimulus: an LRP-TMS study.Experimental brain research · 2026Article
- Nature documentaries vs. quiet rest: no evidence for an impact on event-related desynchronization during motor imagery and neurofeedback.Frontiers in human neuroscience · 2025Article
- Exploring individual biases in BCI research and users: Does gender matter?Frontiers in human neuroscience · 2025Article
- Recognition of brain activities via graph-based long short-term memory-convolutional neural network.Frontiers in neuroscience · 2025Article
- The individual difference of motor imagery ability evoked by visual stimulus and its personality manifestation.Heliyon · 2024Article
- Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces.Brain computer interfaces (Abingdon, England) · 2024Article
- Brain-computer interfaces and human factors: the role of language and cultural differences-Still a missing gap?Frontiers in human neuroscience · 2024Article
- Leveraging Motor Imagery Rehabilitation for Individuals with Disabilities: A Review.Healthcare (Basel, Switzerland) · 2023Review
- The Action Cycle Theory of Perception and Mental Imagery.Vision (Basel, Switzerland) · 2023Review
- Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance.Frontiers in human neuroscience · 2023Review
- Dependence of Brain-Computer Interface Control Training on Personality Traits.Doklady. Biochemistry and biophysics · 2022Article
- 2020 International brain-computer interface competition: A review.Frontiers in human neuroscience · 2022Review
- Does Imagery Ability Matter for the Relationship Between Temperament and Self-Confidence in Team and Individual Sport Disciplines?Frontiers in psychology · 2022Article
- Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users.PloS one · 2022Article
- Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.Frontiers in human neuroscience · 2022Article
- Functional Connectivity Analysis in Motor-Imagery Brain Computer Interfaces.Frontiers in human neuroscience · 2021Article
- Improving Motor Imagery-Based Brain-Computer Interface Performance Based on Sensory Stimulation Training: An Approach Focused on Poorly Performing Users.Frontiers in neuroscience · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interfaces (BCIs) are communication bridges between a human brain and external world, enabling humans to interact with their environment without muscle intervention. Their functionality, therefore, depends on both the BCI system and the cognitive capacities of the user. Motor-imagery BCIs (MI-BCI) rely on the users' mental imagination of body movements. However, not all users have the ability to sufficiently modulate their brain activity for control of a MI-BCI; a problem known as BCI illiteracy or inefficiency. The underlying mechanism of this phenomenon and the cause of such difference among users is yet not fully understood. In this study, we investigated the impact of several cognitive and psychological measures on MI-BCI performance. Fifty-five novice BCI-users participated in a left- versus right-hand motor imagery task. In addition to their BCI classification error rate and demographics, psychological measures including personality factors, affinity for technology, and motivation during the experiment, as well as cognitive measures including visuospatial memory and spatial ability and Vividness of Visual Imagery were collected. Factors that were found to have a significant impact on MI-BCI performance were Vividness of Visual Imagery, and the personality factors of orderliness and autonomy. These findings shed light on individual traits that lead to difficulty in BCI operation and hence can help with early prediction of inefficiency among users to optimize training for them.
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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.