Real-time decoding of covert attention in higher-order visual areas.
Neuroimage
; 169: 462-472, 2018 04 01.
Article
en En
| MEDLINE
| ID: mdl-29247807
ABSTRACT
Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online 'winner-takes-all approach' with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, 'cognitive BCIs' access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Reconocimiento Visual de Modelos
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Atención
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Percepción Espacial
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Procesamiento de Imagen Asistido por Computador
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Corteza Cerebral
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Neuroimagen Funcional
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Interfaces Cerebro-Computador
Límite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Neuroimage
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2018
Tipo del documento:
Article