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

Ekanayake, Jinendra; Hutton, Chloe; Ridgway, Gerard; Scharnowski, Frank; Weiskopf, Nikolaus; Rees, Geraint

doi:10.1016/j.neuroimage.2017.12.019

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

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Weiskopf, Nikolaus
Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom;
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Ekanayake, J., Hutton, C., Ridgway, G., Scharnowski, F., Weiskopf, N., & Rees, G. (2018). Real-time decoding of covert attention in higher-order visual areas. NeuroImage, 169, 462-472. doi:10.1016/j.neuroimage.2017.12.019.

Cite as: https://hdl.handle.net/21.11116/0000-0000-20C9-9

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.