ArticleFrontiers in human neuroscience2018
A P300-Based Brain-Computer Interface for Improving Attention.
Article in Frontiers in human neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.
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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.
Dynamic Difficulty Adjustment in a P300 Speller Task for Attention Training
Identification and Quantification of Neurological Responses in Patients with Dentine Hypersensitivity
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain-Computer Interfaces: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2021Pooled it
- P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2020Pooled it
- Electrocortical Indices of Default Mode Network-Related Activity in ADHD and Modulation Through Mindfulness-Based Cognitive Therapy.Brain topography · 2026Trial
- Multimodal Assessment of Consciousness with Brain-Computer Interfaces and Artificial Intelligence: From Acquired Brain Injury to Neurodegenerative Disease.Journal of clinical medicine · 2026Review
- Neurotechnology for enhancing human operation of robotic and semi-autonomous systems.Frontiers in robotics and AI · 2025Review
- A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome.Cognitive neurodynamics · 2024Review
- Post-stroke aphasia rehabilitation using an adapted visual P300 brain-computer interface training: improvement over time, but specificity remains undetermined.Frontiers in human neuroscience · 2024Article
- Efficacy of neurofeedback training for improving attentional performance in healthy adults: A systematic review and meta-analysis.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Adaptive P300-Based Brain-Computer Interface for Attention Training: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2023Article
- Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity.The European journal of neuroscience · 2023Article
- Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical communications of different cognitive tasks.Brain informatics · 2022Article
- A simultaneous electroencephalography and eye-tracking dataset in elite athletes during alertness and concentration tasks.Scientific data · 2022Article
- Methodology and preliminary data on feasibility of a neurofeedback protocol to improve visual attention to letters in mild Alzheimer's disease.Contemporary clinical trials communications · 2022Article
- Beyond the brain-computer interface: Decoding brain activity as a tool to understand neuronal mechanisms subtending cognition and behavior.Frontiers in neuroscience · 2022Review
- A Regional Smoothing Block Sparse Bayesian Learning Method With Temporal Correlation for Channel Selection in P300 Speller.Frontiers in human neuroscience · 2022Article
- Active Brain-Computer Interfacing for Healthy Users.Frontiers in neuroscience · 2022Article
- Decoding Covert Speech From EEG-A Comprehensive Review.Frontiers in neuroscience · 2021Review
- Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions.Frontiers in human neuroscience · 2021Review
- Combining Statistical Analysis and Machine Learning for EEG Scalp Topograms Classification.Frontiers in systems neuroscience · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A Brain-computer Interface (BCI) can be used as a neurofeedback training tool to improve cognitive performance. BCIs aim to improve the effectiveness and efficiency of the conventional neurofeedback methods by focusing on the self-regulation of individualized neuromarkers rather than generic ones in a graphically appealing training environment. In this work, for the first time, we have modified a widely used P300-based speller BCI and used it as an engaging neurofeedack training game to enhance P300. According to the user's performance the game becomes more difficult in an adaptive manner, requiring the generation of a larger and stronger P300 (i.e., in terms of total energy) in response to target stimuli. Since the P300 is generated naturally without conscious effort in response to a target trial, unlike many rhythm-based neurofeedback tools, the ability to control the proposed P300-based neurofeedback training is obtained after a short calibration without undergoing tedious trial and error sessions. The performance of the proposed neurofeedback training was evaluated over a short time scale (approximately 30 min training) using 28 young adult participants who were randomly assigned to either the experimental group or the control group. In summary, our results show that the proposed P300-based BCI neurofeedback training yielded a significant enhancement in the ERP components of the target trials (i.e., 150-550 ms after the onset of stimuli which includes P300) as well as attenuation in the corresponding ERP components of the non-target trials. In addition, more centro-parietal alpha suppression was observed in the experimental group during the neurofeedback training as well as a post-training spatial attention task. Interestingly, a significant improvement in the response time of a spatial attention task performed immediately after the neurofeedback training was observed in the experimental group. This paper, as a proof-of-concept study, suggests that the proposed neurofeedback training tool is a promising tool for improving attention particularly for those who are at risk of attention deficiency.
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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.