The Default Mode Network and Behavior: a Model to Analyse Psycho-Physiological Interactions in Resting State fMRI.

The Default Mode Network (DMN) was discovered through data-driven analysis of resting-state fMRI, making it difficult to link the network to specific cognitive functions or personality traits, because no observable task is performed during scanning. Over two decades of research have not produced a consensus methodology for studying these relationships. The authors propose an alternative method that reduces the dimensionality of extensive psychological evaluations and the spatial features of intrinsic connectivity components. Their results show that connectivity networks are only low to moderately related to behavioral and personality traits, and that this relationship is not direct. The approach may help reveal how intrinsic brain network organization relates to individual differences in cognition and personality.

Study at a glance

Abstract

The Default Mode Network was a key finding for cognitive neuroscience, but being the result of a data-driven analysis of resting-state fMRI data, its psychological and clinical implications have been difficult to elucidate. This is because in the resting-state paradigm we cannot directly correlate an observable specific task with specific brain connectivity patterns, and therefore inferences about the relationship between particular cognitive domains and the resting-state networks are limited. A similar problem arises when trying to link the network with personality traits: the DMN, as other intrinsic networks, is not a simple metric to compare with the results of a psychological test, but a complex composite of spatio-temporal features. Although over the last two decades several research works have provided insights about these relationships, we still lack a consensus on the methodology that best captures these interactions. In this context, we propose an alternative method to model the psycho-physiological relationships of the resting state components with behavioral data, based on the dimensionality reduction of an extensive psychological evaluation and the spatial dimension of the intrinsic connectivity components. Our results show that the connectivity networks are low to moderately related with behavioral and personality traits, or at least this relation is not in a direct way. This integration of neuroimaging and psychological assessment data creates valuable pathways for cognitive neuroscience, potentially revealing with precision how intrinsic brain network organization relates to individual variations in cognitive functioning and personality dimensions.