Return of cybernetics

In non-invasive approaches such as electroencephalography (EEG), brain activity is measured with electrodes placed on the scalp, which has the advantage that no surgery is required. Decoding the recorded signals into useful real-time information is challenging, but advances in materials engineering and machine learning in the past decade are showing promise. In an Article in this issue, Yeo et al. demonstrate a compact and lightweight, scalp-wearable device that reads out visually evoked electrical signals with high resolution. A deep learning algorithm is trained to classify the signals and can be used offline. In one experiment (with able-bodied subjects) it is shown that a wheelchair can be controlled in real time, demonstrating the practical promise of this approach.