A Computational Model of Focused Attention Meditation and Its Transfer to a Sustained Attention Task

Abstract

Meditation has been shown to aid with the management of affective disorders through improving emotion regulation. Here we begin to develop a theory of meditation by creating a computational cognitive model of focused attention meditation. Our model was created within Prims, a derivative of the ACT-R cognitive architecture. We implemented a model based on an extensive literature review of how the meditation experience unfolds over time. We then tested the Prims model in a sustained attention task, intending to capture a faculty that may be trained with meditation practice. The model was significantly better able to maintain focus after the meditation practice than before. These results agree qualitatively with empirical findings of a longitudinal study on the effects of meditation conducted in 2010. The central mechanism for increasing task relevant focus in the model seems to be a feedback loop. The meditation and mind-wandering processes reinforce themselves and weaken the other. However, this reinforcement is more dispersed in the more elaborate mind-wandering process, which causes it to decrease over time. We speculate that observed improvements in emotion regulation observed after meditation arise from the ability to maintain focus, because it allows the practitioner to avoid emotions spiraling out of control.