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Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces

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 horizo...

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Detalles Bibliográficos
Autores principales: Matran-Fernandez, Ana, Poli, Riccardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451058/
https://www.ncbi.nlm.nih.gov/pubmed/28562664
http://dx.doi.org/10.1371/journal.pone.0178498
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author Matran-Fernandez, Ana
Poli, Riccardo
author_facet Matran-Fernandez, Ana
Poli, Riccardo
author_sort Matran-Fernandez, Ana
collection PubMed
description 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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spelling pubmed-54510582017-06-12 Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces Matran-Fernandez, Ana Poli, Riccardo PLoS One Research Article 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. Public Library of Science 2017-05-31 /pmc/articles/PMC5451058/ /pubmed/28562664 http://dx.doi.org/10.1371/journal.pone.0178498 Text en © 2017 Matran-Fernandez, Poli http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Matran-Fernandez, Ana
Poli, Riccardo
Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title_full Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title_fullStr Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title_full_unstemmed Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title_short Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
title_sort towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451058/
https://www.ncbi.nlm.nih.gov/pubmed/28562664
http://dx.doi.org/10.1371/journal.pone.0178498
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