Joint Gray and White Matter Networks Predict Mindfulness and Mind Wandering Traits: A Data Fusion Machine Learning Approach

Abstract

AbstractMind wandering is a ubiquitous part of our normal cognition and daily lives, with people reporting that their mind wanders during 25-50% of their waking hours. Studies suggest that mind wandering shares an inverse relationship with mindfulness skills. Our aim was to expand this evidence directly by investigating the mediating effect among mindfulness, mind wandering, and brain features. The main goal of our study in particular was to find out which morphometric brain features are associated with mindfulness and mind wandering, and to investigate how mindfulness mediates deliberate and spontaneous mind wandering in terms of these associated brain components. GM and WM MRI scans of 76 individuals and self-reported questionnaires were included in the analysis. We predicted that specific gray matter (GM) and white matter (WM) networks would also influence deliberate and spontaneous mind wandering tendencies with mindfulness as a mediator. We found that GM and WM networks including structures that have been consistently linked to mindfulness, such as the cingulate, the insula, the basal ganglia and fronto-parietal attentive regions, exert direct effects on mindfulness, and deliberate and spontaneous mind wandering. We also found an indirect mediating effect of the FFMQ facetacting with awarenesson spontaneous mind wandering in terms of increased and decreased GM volume concentrations. This study elicited the link between mind wandering and mindfulness and expands our knowledge on the neural bases of these two psychological constructs.