Tasks activating the default mode network map multiple functional systems

Abstract

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

Keywords: Activation likelihood estimation; DMN; Insula; Semantics; Task-induced deactivations.

Fig. 1

Surface mapping of the nine activation likelihood estimation maps

Fig. 2

Pie charts with the proportions of each ALE voxels for each one of the resting-state networks proposed by Shirer et al., Yeo et al., and Doucet et al. As reference, each parcellation is presented in form of volume renderings. ECN executive control network, sal salience network, precun precuneus, BG basal ganglia, visuospat visuospatial network, sensmot sensorimotor network. The ECN by Shirer et al. roughly corresponds to the frontoparietal network by Yeo et al. and Doucet et al. The ventral attention network by Yeo et al. includes the salience network. The language network by Shirer et al. includes large parts of the DMN as depicted by others

Fig. 3

Multidimensional scaling (MDS) of the nine activation likelihood estimation (ALE) maps. A: 1 − r distance matrix of the nine ALE maps. B First two axis of the MDS 3-dimensional solution. ALEs volume mappings are shown next to their respective MDS coordinates. C First and third axis of the MDS 3-dimensional solution. D MDS 3-dimensional solution, seen from different perspectives. From left to right, the views are progressively rotated for a better understanding of tridimensionality

Fig. 4

Results of the four-component solution of the Independent Component Analysis. Left: surface mapping of the voxel-wise scores. Right: weights of the unmixing matrix of each component (loadings) on each paradigm map

Fig. 5

Surface mapping of the overlaps between the volumes of positive voxels of the four ICs and PG1 and 3 by Margulies et al. (2016). For each comparison, the ratio of positive IC voxels overlapping with the positive PG is reported