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Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI
Brain-Computer interface technologies mean to create new communication channels between our mind and our environment, independent of the motor system, by detecting and classifying self regulation of local brain activity. BCIs can provide patients with severe paralysis a means to communicate and to l...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215723/ https://www.ncbi.nlm.nih.gov/pubmed/22110702 http://dx.doi.org/10.1371/journal.pone.0027638 |
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author | Andersson, Patrik Pluim, Josien P. W. Siero, Jeroen C. W. Klein, Stefan Viergever, Max A. Ramsey, Nick F. |
author_facet | Andersson, Patrik Pluim, Josien P. W. Siero, Jeroen C. W. Klein, Stefan Viergever, Max A. Ramsey, Nick F. |
author_sort | Andersson, Patrik |
collection | PubMed |
description | Brain-Computer interface technologies mean to create new communication channels between our mind and our environment, independent of the motor system, by detecting and classifying self regulation of local brain activity. BCIs can provide patients with severe paralysis a means to communicate and to live more independent lives. There has been a growing interest in using invasive recordings for BCI to improve the signal quality. This also potentially gives access to new control strategies previously inaccessible by non-invasive methods. However, before surgery, the best implantation site needs to be determined. The blood-oxygen-level dependent signal changes measured with fMRI have been shown to agree well spatially with those found with invasive electrodes, and are the best option for pre-surgical localization. We show, using real-time fMRI at 7T, that eye movement-independent visuospatial attention can be used as a reliable control strategy for BCIs. At this field strength even subtle signal changes can be detected in single trials thanks to the high contrast-to-noise ratio. A group of healthy subjects were instructed to move their attention between three (two peripheral and one central) spatial target regions while keeping their gaze fixated at the center. The activated regions were first located and thereafter the subjects were given real-time feedback based on the activity in these regions. All subjects managed to regulate local brain areas without training, which suggests that visuospatial attention is a promising new target for intracranial BCI. ECoG data recorded from one epilepsy patient showed that local changes in gamma-power can be used to separate the three classes. |
format | Online Article Text |
id | pubmed-3215723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32157232011-11-21 Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI Andersson, Patrik Pluim, Josien P. W. Siero, Jeroen C. W. Klein, Stefan Viergever, Max A. Ramsey, Nick F. PLoS One Research Article Brain-Computer interface technologies mean to create new communication channels between our mind and our environment, independent of the motor system, by detecting and classifying self regulation of local brain activity. BCIs can provide patients with severe paralysis a means to communicate and to live more independent lives. There has been a growing interest in using invasive recordings for BCI to improve the signal quality. This also potentially gives access to new control strategies previously inaccessible by non-invasive methods. However, before surgery, the best implantation site needs to be determined. The blood-oxygen-level dependent signal changes measured with fMRI have been shown to agree well spatially with those found with invasive electrodes, and are the best option for pre-surgical localization. We show, using real-time fMRI at 7T, that eye movement-independent visuospatial attention can be used as a reliable control strategy for BCIs. At this field strength even subtle signal changes can be detected in single trials thanks to the high contrast-to-noise ratio. A group of healthy subjects were instructed to move their attention between three (two peripheral and one central) spatial target regions while keeping their gaze fixated at the center. The activated regions were first located and thereafter the subjects were given real-time feedback based on the activity in these regions. All subjects managed to regulate local brain areas without training, which suggests that visuospatial attention is a promising new target for intracranial BCI. ECoG data recorded from one epilepsy patient showed that local changes in gamma-power can be used to separate the three classes. Public Library of Science 2011-11-14 /pmc/articles/PMC3215723/ /pubmed/22110702 http://dx.doi.org/10.1371/journal.pone.0027638 Text en Andersson et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Andersson, Patrik Pluim, Josien P. W. Siero, Jeroen C. W. Klein, Stefan Viergever, Max A. Ramsey, Nick F. Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title | Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title_full | Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title_fullStr | Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title_full_unstemmed | Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title_short | Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI |
title_sort | real-time decoding of brain responses to visuospatial attention using 7t fmri |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3215723/ https://www.ncbi.nlm.nih.gov/pubmed/22110702 http://dx.doi.org/10.1371/journal.pone.0027638 |
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