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Updated: Feb 16, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
Published on: January 23, 2017
Real-time decoding of covert attention in higher-order visual areas
Jinendra Ekanayake1, Chloe Hutton2, Gerard Ridgway3
1Wellcome Trust Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom; Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Institute of Cognitive Neuroscience, University College London, London, United Kingdom.
This study demonstrates cognitive brain-computer interfaces (BCI) using higher-order brain regions for attention decoding. This advances BCI technology for potential communication in patients with severe brain injuries.
Area of Science:
- Neuroscience
- Cognitive Science
- Biomedical Engineering
Background:
- Brain-computer interfaces (BCI) traditionally rely on motor and sensory brain regions.
- Existing BCI methods often require invasive surgical implants or complex neuroimaging setups.
Purpose of the Study:
- To establish proof-of-principle for using higher-order brain regions in BCI.
- To explore the use of cognitive processes, specifically attention, for BCI control.
- To develop a non-invasive BCI system for communication in patients with severe brain injuries.
Main Methods:
- Utilized real-time functional magnetic resonance imaging (fMRI).
- Implemented an online 'winner-takes-all' classification approach with quadrant-specific parameter estimates.
- Linked brain activation classifications to the covert allocation of attention to images presented in four locations.
Main Results:
- Achieved single-block classification of brain activations related to attention.
- Demonstrated significantly above-chance decoding accuracies in three target higher-order brain regions.
- Reached individual decoding accuracies up to 70%.
Conclusions:
- Higher-order brain regions can be effectively utilized for BCI applications.
- 'Cognitive BCIs' leverage versatile information from complex mental processes.
- This approach offers a potential communication platform for individuals with severe motor impairments.
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