Cited by 149EEG and Brain-Computer InterfacesGaze Tracking and Assistive TechnologyNeural and Behavioral Psychology Studies

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A review of rapid serial visual presentation-based brain–computer interfaces

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Lees, Stephanie, Dayan, Natalie, Cecotti, Hubert, McCullagh, Paul, Maguire, Liam, Lotte, Fabien, Coyle, Damien·2018·Journal of Neural Engineering

DOI 10.1088/1741-2552/aa9817

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Abstract

Rapid serial visual presentation (RSVP) combined with the detection of event-related brain responses facilitates the selection of relevant information contained in a stream of images presented rapidly to a human. Event related potentials (ERPs) measured non-invasively with electroencephalography (EEG) can be associated with infrequent targets amongst a stream of images. Human-machine symbiosis may be augmented by enabling human interaction with a computer, without overt movement, and/or enable optimization of image/information sorting processes involving humans. Features of the human visual system impact on the success of the RSVP paradigm, but pre-attentive processing supports the identification of target information post presentation of the information by assessing the co-occurrence or time-locked EEG potentials. This paper presents a comprehensive review and evaluation of the limited, but significant, literature on research in RSVP-based brain-computer interfaces (BCIs). Applications that use RSVP-based BCIs are categorized based on display mode and protocol design, whilst a range of factors influencing ERP evocation and detection are analyzed. Guidelines for using the RSVP-based BCI paradigms are recommended, with a view to further standardizing methods and enhancing the inter-relatability of experimental design to support future research and the use of RSVP-based BCIs in practice.

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An introduction to ROC analysis
Fawcett, T. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.10.010 · Cited by 21,879
Untitled work
(2005) · Cited by 5,977
A review of classification algorithms for EEG-based brain–computer interfaces
Lotte, F., Congedo, M., Lécuyer, A., Lamarche, F., & Arnaldi, B. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/2/r01 · Cited by 2,665
Self-citation
The distinct modes of vision offered by feedforward and recurrent processing
Lamme, V. A. F., & Roelfsema, P. R. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01657-x · Cited by 2,338
Temporary suppression of visual processing in an RSVP task: An attentional blink?
Raymond, J. E., Shapiro, K. L., & Arnell, K. M. (1992) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.18.3.849 · Cited by 2,286
Analyzing Neural Time Series Data: Theory and Practice
Cohen, M. X. (2014) · doi:10.7551/mitpress/9609.001.0001 · Cited by 2,105
Temporary suppression of visual processing in an RSVP task: an attentional blink?
Raymond, J. E., Shapiro, K. L., & Arnell, K. M. (1992) · Journal of Experimental Psychology: Human Perception and Performance · doi:10.1037/0096-1523.18.3.849 · Cited by 1,649
Toward Direct Brain-Computer Communication
Vidal, J. J. (1973) · Annual Review of Biophysics and Bioengineering · doi:10.1146/annurev.bb.02.060173.001105 · Cited by 1,311
Event-related potential studies of attention.
Luck, S., Woodman, G., & Vogel, E. (2000) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01545-x · Cited by 1,209
A Metric for Thought: A Comparison of P300 Latency and Reaction Time
McCarthy, G., & Donchin, E. (1981) · Science · doi:10.1126/science.7444452 · Cited by 1,147

Show all 120 references

Research works printed but not linked: 22

Bohannon A W, 2017, 2016 IEEE Int. Conf. on Systems, Man, and Cybernetics, SMC 2016—Conf. Proc., 4046
Cecotti H, 2011, Conf. Proc., Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conf., 6381
Cecotti H, 2011, Conf. Proc., Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conf., 6311
Cecotti H, 2012, Conf. Proc., Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conf., 1723
Erdogmus D, 2006, 2006 IEEE Int. Joint Conf. on Neural Network Proc., 1136
Healy G, 2011, Proc. of HCI 2011—25th BCS Conf. on Human Computer Interaction, 157
Hild K E, 2011, ACL HLT 2011—49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of Student Session, 38
Huang Y, 2006, 2006 IEEE Int. Joint Conf. on Neural Network Proc., 1136
Huang Y, 2007, Proc. of the 3rd Int. IEEE EMBS Conf. on Neural Engineering, 473
Huang Y, 2008, IEEE Int. Conf. on Acoustics, Speech and Signal Processing, 429
Kindermans P-J, 2014, J. Neural Eng., 11
Marathe A, 2015, IEEE Trans. Neural Syst. Rehabil. Eng., 4320, 1
Matran-Fernandez A, 2014, 6th Computer Science and Electronic Engineering Conf. CEEC 2014—Conf. Proc., 127
Orhan U, 2011, Conf. Proc. Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conf., 5774
Orhan U, 2012, Conf. Proc., Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conf., 2497
Orhan U, 2012, ICASSP, IEEE Int. Conf. on Acoustics, Speech and Signal Processing—Proc., 645
Rensink R A, 2000, Change, 6, 458
Saavedra C, 2012, NeuroComp/KEOpS’12 Workshop
10.1109/JSTSP.2014.2313022 · DOI
Sajda P, 2003, Proc. 1st Int. IEEE EMBS Conf. on Neural Engineering, 7
Zander T O, 2011, J. Neural Eng., 8
Zhang Y, 2012, J. Neural Eng., 9

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Peters, B., Celik, B., Gaines, D. C., Galvin-McLaughlin, D., Imbiriba, T., Kinsella, M., Klee, D., Lawhead, M., Memmott, T., Smedemark-Margulies, N., et al. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/ada8e0 · Cited by 3
Affective Video Tagging Framework using Human Attention Modelling through EEG Signals
Sharma, S., Dubey, A. K., & Ranjan, P. (2022) · International Journal of Intelligent Information Technologies · doi:10.4018/ijiit.306968 · Cited by 3
Combining multi-scale convolutional neural network and Transformers for EEG-Based RSVP detection
Lu, G., Zhang, Y., Chu, X., Liu, Y., & Yu, Y. (2022) · Youth Academic Annual Conference of Chinese Association of Automation (YAC) · doi:10.1109/yac57282.2022.10023688 · Cited by 3
Multi-source domain adaptation based tempo-spatial convolution network for cross-subject EEG classification in RSVP task
Wang, X., Li, B., Lin, Y., & Gao, X. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad2710 · Cited by 3
[A spatial-temporal hybrid feature extraction method for rapid serial visual presentation of electroencephalogram signals].
Cui, Y., Xie, S., Xie, X., Duan, X., & Gao, C. (2022) · PubMed Central · doi:10.7507/1001-5515.202104049 · Cited by 3
Quick breast cancer detection via classification of evoked EEG potentials in the mammologist's brain
Sulimova, V. V., Windridge, D., Bukhonov, S., Mottl, V., & Krasotkina, O. (2019) · International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) · doi:10.1109/sibircon48586.2019.8958286 · Cited by 3
Single-trial detection of EEG error-related potentials in serial visual presentation paradigm
Parashiva, P. K., & Vinod, A. P. (2021) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ac4200 · Cited by 3
Object Detection in Surveillance Video using EEG with Domain Adaptation Approach
Yun, M.-H., Jang, H., Ahn, S., & Kim, H. (2024) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/bci60775.2024.10480519 · Cited by 2
Real-Time BCI System for Target Detection
Won, E., Lim, S., Kim, Y., & Dong, S.-Y. (2024) · International Winter Conference on Brain-Computer Interface (BCI) · doi:10.1109/bci60775.2024.10480516 · Cited by 3
A novel RSVP-based system using EEG and eye-movement for classification and localization
Wu, H., Li, F., Chu, W., Li, H., Ji, Y., Li, Y., Niu, Y., Wang, H., Chen, Y., & Shi, G. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107331 · Cited by 2
Adaptive attention graph convolution network with normalized embedded Gaussian for rapid serial visualization presentation decoding
Zhao, M., Ai, Q., Chen, K., Liu, Q., Xie, S. Q., & Ma, L. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112093 · Cited by 2
An active recursive state estimation framework for brain-interfaced typing systems
Koçanaoğulları, A., Marghi, Y. M., Akçakaya, M., & Deniz Erdogmus, B. (2019) · Brain-Computer Interfaces · doi:10.1080/2326263x.2020.1729652 · Cited by 2
A multi-scale EEGNet for cross-subject RSVP-based BCI system
Wang, X., Lin, Y., Tan, Y. C., Guo, R., & Gao, X. (2022) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei56279.2022.9980258 · Cited by 2
The Connection between Neurophysiological Correlates of Trust and Distrust and Isolated HEXACO Dimensions
Külzer, D., Kalt, S., & Walla, P. (2024) · Life · doi:10.3390/life14030362 · Cited by 2
Pupillometry Analysis of Rapid Serial Visual Presentation at Five Presentation Rates
Luo, X. L., Lin, Y., Guo, R., Zhao, X., Zhang, S., & Gao, X. (2023) · Tsinghua Science & Technology · doi:10.26599/tst.2023.9010029 · Cited by 1
The use of happy faces as visual stimuli improves the performance of the hybrid SSVEP+P300 brain computer interface
Kapgate, D. D. (2024) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110170 · Cited by 1
Improving subject transfer in EEG classification with divergence estimation
Smedemark-Margulies, N., Wang, Y., Koike–Akino, T., Liu, J., Parsons, K., Bicer, Y., & Deniz Erdogmus, B. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad9777 · Cited by 2
A multi-source classification framework with invariant representation reconstruction for dual-target RSVP-BCI tasks in cross-subject scenario
Chen, H., Wang, D., Xu, M., Chen, J., Zhang, Y., & Chen, Y. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.129239 · Cited by 1
An explainable hybrid bio-inspired feature selection framework using RSVP-evoked P300 EEG signals for identity authentication
Abinayaa, S., & Sridhar, S. S. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129674 · Cited by 1
SDDA: Spatial Distillation Based Distribution Alignment for Cross-Headset EEG Classification
Liu, D., Li, S., Wang, Z., Li, W., & Wu, D. (2025) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2025.3631604 · Cited by 1
A Few-Layer Multilayer Perceptron is Worth Attention for EEG Classification in Rapid Serial Visual Presentation Task
Zhang, Z., Zheng, Y., Guo, K., Liang, J., & Dong, M. (2026) · International Journal of Neural Systems · doi:10.1142/s0129065726500309 · Cited by 1
The ASME-speller: 30-class auditory brain-computer interface speller using stream segregation and the QWERTY layout
Kojima, S., & Kanoh, S. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1807535 · Cited by 1
CLET: Computation of Latencies in Event-related potential Triggers using photodiode on virtual reality apparatuses
Swami, P., Gramann, K., Vonstad, E. K., Vereijken, B., Holt, A., Holt, T., Sandstrak, G., Nilsen, J. H., & Su, X. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1223774 · Cited by 1
Event-Related Potential in Rapid Serial Visual Presentation-based Partial Face Cognition Depends on Visible Face Components
Chanpornpakdi, I., & Tanaka, T. (2023) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc58517.2023.10317267 · Cited by 1

Authors: Lees, S., Dayan, N., Cecotti, H., McCullagh, P., Maguire, L., Lotte, F., & Coyle, D.
Affiliations: University of Ulster (GB)
California State University, Fresno (US)
Centre National de la Recherche Scientifique (FR)
Corresponding author: Coyle, Damien
ORCID: Lees, Stephanie
Dayan, Natalie
Cecotti, Hubert
McCullagh, Paul
Maguire, Liam
Lotte, Fabien
Coyle, Damien
Venue: Journal of Neural Engineering
Publisher: IOP Publishing
Published: 2018-01-24
Volume: 15
Issue: 2
Pages: 021001
ISSN: 1741-2552 (ISSN-L)
1741-2560
DOI: 10.1088/1741-2552/aa9817
OpenAlex: W2767056600
Cited by: 149
References: 120
Citations by year: 2026: 7 · 2025: 24 · 2024: 35 · 2023: 21 · 2022: 14 · 2021: 18 · 2020: 16 · 2019: 8 · 2018: 6
FWCI: 0.92
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
iopscience.iop.org/info/page/text-and-data-mining (tdm)
creativecommons.org/licenses/by/3.0/ (vor)
Locations: Journal of Neural Engineering (publishedVersion, cc-by)
PubMed (publishedVersion)
Ulster University Research Portal (Ulster University) (publishedVersion, other-oa)
HAL (submittedVersion, other-oa)
Funders: Engineering and Physical Sciences Research Council (EP/H012958/1)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords: rapid serial visual presentation, brain-computer interface, event-related potentials, preattentive processing, EEG, human-machine symbiosis, display modes, experimental standardization
MeSH terms: Brain, Electroencephalography, Evoked Potentials, Visual, Humans, Photic Stimulation, Time Factors, Brain-Computer Interfaces

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A review of rapid serial visual presentation-based brain–computer interfaces

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