Predicting behavioural errors in advance using MEG data - preprint out now!
Exciting new research by Hamid, Alex and Anina is now out as a preprint. This study investigates human vigilance decrements using neural decoding in MEG. During tasks where one has to sustain attention for long periods of time and rarely act, such as in air traffic control or train monitoring, lapses of attention can have significant consequences. Using the methods developed here, Hamid and colleagues were able to successfully predict forthcoming human errors in a novel multiple-object-monitoring paradigm. This research provides a first step into developing methods to predict and pre-empt behavioural errors due to lapses in attention.
Link to preprint: https://www.biorxiv.org/content/10.1101/2020.06.29.178970v1