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.
Highlights
Brain-computer interfaces (BCIs) attempt to link measures of brain-related physiological activity with control of a device for communication or movement
We examined 3 brain regions; parietal lobe, lateral occipital cortex (LOC), and fusiform face area (FFA), all of which have been suggested to contain salience maps (Gottlieb, 2007; Zenon et al, 2010), and have roles in integrating position and category-specific information (Carlson et al, 2011)
This study demonstrates accurate decoding of attention-based information, using realtime fMRI
Summary
Brain-computer interfaces (BCIs) attempt to link measures of brain-related physiological activity with control of a device for communication or movement. A standard approach is to target brain activations produced in primary sensory or motor cortex (Jackson and Zimmermann, 2012), mapping the function of the target brain region with BCI output in a one-to-one fashion e.g. using motor cortical activations to control a hand prosthesis, or using retinotopic representations in primary visual cortex to direct a cursor on a screen (Andersson et al, 2013a; Birbaumer et al., 2008; Golub et al, 2016; Lebedev and Nicolelis, 2006; Miranda et al, 2015; Murphy et al, 2015). Cognitive BCIs seek to advance this premise by engaging higher-order brain regions, which control or combine basic afferent sensory information to produce behaviourally meaningful actions, or target regions which are involved in overarching processes such as attention We used realtime fMRI (rt-fMRI) to test whether brain activations in higher-order visual cortex could be accurately classified in real-time
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