Decoding the Mental States of Focus and Distraction in a Real Life Setting of Tibetan Monastic Debates Using EEG and Machine Learning

Cognitive science has started to make more and more use of techniques from machine learning to disentangle the neural correlates of cognitive processes. It can be particularly useful for complex situations in which many things are happening at the same time. Here we apply machine learning to investigate the cognitive processes in a rather novel situation: Tibetan monastic debate. Monastic debate is a core practice used in Tibetan monasteries to train preciseness of reasoning and memorization. In the work presented here we distinguish between the occurrence of attentional states, focus and distraction. This gives insight into the cognitive effect of debate training.