Decoding the cognitive states of attention and distraction in a real-life setting using EEG.

Lapses in attention can have serious consequences in situations such as driving a car, hence there is considerable interest in tracking it using neural measures. However, as most of these studies have been done in highly controlled and artificial laboratory settings, we want to explore whether it is also possible to determine attention and distraction using electroencephalogram (EEG) data collected in a natural setting using machine/deep learning. 24 participants volunteered for the study.

Tibetan Buddhist monastic debate: Psychological and neuroscientific analysis of a reasoning-based analytical meditation practice.

Analytical meditation and monastic debate are contemplative practices engaged in by Tibetan Buddhist monastics that have up to now been largely unexplored in Western contemplative science. The highly physical form of contemplative debating plays an important role in the monastic curriculum. Based on discussions and recorded interviews Tibetan monastic teachers and senior students at Sera Jey Monastic University and preliminary experiments, we outline an initial theory that elucidates the psychological mechanisms underlying this practice.

Computational modelling approaches to meditation research: why should we care?

Computational modeling and meditation are not frequently mentioned in the same breath. However, in this article we argue that computational modeling can provide insights into the mechanisms by which meditation produces its effects on cognition. Moreover, computational modeling allows the researcher to make predictions about how effects of meditation will generalize to other contexts such as other tasks, which can be tested in subsequent experiments.