ArticlePloS one2017
Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024Review
- Optimization of transfer learning based on source sample selection in Euclidean space for P300-based brain-computer interfaces.Frontiers in neuroscience · 2024Article
- A Collaborative Brain-Computer Interface Framework for Enhancing Group Detection Performance of Dynamic Visual Targets.Computational intelligence and neuroscience · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part II: Brain Signals.Sensors (Basel, Switzerland) · 2021Review
- Anytime collaborative brain-computer interfaces for enhancing perceptual group decision-making.Scientific reports · 2021Article
- A Cross-Session Dataset for Collaborative Brain-Computer Interfaces Based on Rapid Serial Visual Presentation.Frontiers in neuroscience · 2020Article
- Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects.Frontiers in human neuroscience · 2019Review
- Bridging Waves and Crucial Events in the Dynamics of the Brain.Frontiers in physiology · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizontal position of targets in aerial images. Images were presented by means of the rapid serial visual presentation technique at rates of 5, 6 and 10 Hz. We created three different cBCIs and tested a participant selection method in which groups are formed according to the similarity of participants' performance. The N2pc that is elicited in our experiments contains information about the position of the target along the horizontal axis. Moreover, combining information from multiple participants provides absolute median improvements in the area under the receiver operating characteristic curve of up to 21% (for groups of size 3) with respect to single-user BCIs. These improvements are bigger when groups are formed by participants with similar individual performance, and much of this effect can be explained using simple theoretical models. Our results suggest that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets.
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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.