Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants

Abstract

The human default mode network (DMN) is implicated in several unique mental capacities. In this study, we tested whether brain-wide interregional communication in the DMN can be derived from population variability in intrinsic activity fluctuations, gray-matter morphology, and fiber tract anatomy. In a sample of 10,000 UK Biobank participants, pattern-learning algorithms revealed functional coupling states in the DMN that are linked to connectivity profiles between other macroscopical brain networks. In addition, DMN gray matter volume was covaried with white matter microstructure of the fornix. Collectively, functional and structural patterns unmasked a possible division of labor within major DMN nodes: Subregions most critical for cortical network interplay were adjacent to subregions most predictive of fornix fibers from the hippocampus that processes memories and places.

Keywords: high-level cognition; machine learning; systems neuroscience.

Fig. 1.

Target atlas definition for the DMN. (A) DMN with its major nodes as commonly studied in neuroimaging. (B) A DMN division into 32 subregions provided the basis for all present investigations, including four subregions in the dmPFC, six in the vmPFC, four in the PMC, six in the bilateral MTG, four in the bilateral TPJ, and eight in the bilateral HC from a recent quantitative atlas (, –20, 47, 48). The 32 DMN compartments allowed analyzing the brain-wide structural and functional correspondence at a fine-grained scale of inquiry (see SI Appendix, Fig. S1). All subregion definitions are open for inspection and reuse (https://neurovault.org/collections/3434/). L/R, left/right.

Fig. 2.

DMN subregion structure is predictive of fornix fibers from the hippocampus. DMN gray matter volumes exposed generalizable patterns that explain white matter tract variability. Among 48 anatomical fiber bundles, three highly predictable tracts carried fornix-related fibers, a major hippocampus output pathway from the limbic system, with 24%, 9%, and 8% explained population variance. (A) Prediction accuracy (R² scores) for the eight most robustly inferred fiber tracts for various diffusion MRI measures, starting from highest estimated performance in yet-to-be-observed individuals. (B) Anatomical tracts with strongest DMN association (color indicates out-of-sample R²). (C) Prominent predictive association with fornix microstructure (mean FA) was located in the bilateral TPJs, medial parts of left vmPFC, posterior parts of left MTG, and right HC, as well as dorsal posterior cingulate (PMC-3) and retrosplenial (PMC-4) cortex. Subregions in green−yellow (blue) increased (decreased) volume together with fornix FA across individuals (SI Appendix, Fig. S2).

Fig. 3.

Functional coupling among DMN subregions is associated with between-network interplay. Summarizing the 19 population modes for display reveals how functional connectivity changes in the DMN explain brain-wide connectivity changes between major networks (SI Appendix, Figs. S3–S6). (A) Biggest positive vs. negative cumulative modulation of connectivity between subregions is apparent in the anterior vs. posterior TPJs, lateral vs. medial portions of the vmPFC, anterior vs. posterior MTG, and precuneus vs. posterior cingulate midline. DMN subregions in hot (cool) colors are related to increases (decreases) of baseline connectivity strength that accompany specific network connectivity shifts. (B) Importance of the 19 modes measured by Pearson’s correlation between canonical variates (blue), all statistically significant at P value < 0.001. (C) Biggest positive and negative cumulative network modulations were spatially overlapping. Of note is that the DMN subregions with high modulation weights across modes are mostly located outside of the brain networks with the most recruitment changes.

Fig. 4.

Functional coupling shifts of the statistically strongest DMN−networks mode, depicting the single most important mode among 19 linked dimensions of within-DMN connectivity (Top) and between-network connectivity (Bottom). Increased coupling of anterior TPJs with other DMN subregions was estimated to be dominantly involved in connectivity shifts of large-scale networks. Such partial-correlation analyses have become a standard to focus on immediate coupling relationships between brain regions (49). It is, however, important to keep in mind that this type of connectivity analysis is susceptible to noise and does not permit statements about directional or causal functional influences (50).