Real-time decoding of covert attention in higher-order visual areas

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2018-04, Vol.169, p.462-472
• Main Authors: Ekanayake, Jinendra, Hutton, Chloe, Ridgway, Gerard, Scharnowski, Frank, Weiskopf, Nikolaus, Rees, Geraint
• Format: Article
• Language: English
• Subjects: Adult; Attention; Attention - physiology; Brain; Brain injury; Brain mapping; Brain-Computer Interfaces; Cerebral Cortex - diagnostic imaging; Cerebral Cortex - physiology; Cognition & reasoning; Cognitive ability; Eye Movement Measurements; Female; Functional magnetic resonance imaging; Functional Neuroimaging - methods; Humans; Image Processing, Computer-Assisted - methods; Information sources; Interfaces; Magnetic Resonance Imaging; Male; Motor task performance; Neuroimaging; NMR; Nuclear magnetic resonance; Pattern Recognition, Visual - physiology; Proof of Concept Study; Space Perception - physiology; Visual perception; Visual task performance; Young Adult
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2017.12.019

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. •Proof-of-principle of a ‘cognitive brain-computer-interface’ using realtime fMRI.•Higher order visual brain regions used to decode the allocation of attention.•Online single-block classification of 4-quadrant spatial attention to realworld images.•Brain signal detection made more efficient by using ‘m-sequences’.•Higher order mental processes produce more information for communication interfaces.