Hierarchical dynamics as a macroscopic organizing principle of the human brain

Abstract

Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined "temporal receptive windows" are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.

Keywords: fMRI; frequency; functional connectivity; intrinsic; subcortex.

Fig. 1.

Hierarchy of intrinsic timescales revealed from fMRI autocorrelation. (A) Intrinsic timescale was estimated for each cortical vertex as the temporal autocorrelation decay during the resting state, quantified as half of the full width at half maximum of the ACF (Methods). (B) Vertex-wise map of mean intrinsic timescale (n = 1,139 subjects).

Fig. 2.

Hierarchical timescales in nonneocortical structures. Three-dimensional renderings rotated to highlight the major axes of variation in mean intrinsic timescale (n = 1,139 subjects) in the left and right (A) striatum, (B) thalamus, (C) hippocampus, and (D) cerebellum. Timescales are given in seconds. Direction labels indicate dorsal (D), posterior (P), and (anatomical) rightward (R). Three-dimensional maps generated from MNI152 voxel coordinates.

Fig. 3.

Cortical and subcortical timescale gradients relate to functional organization. (A) Group-averaged intrinsic timescales computed for cortical (as in Fig. 1) and nonneocortical (as in Fig. 2) structures, including striatum and thalamus (Middle) and cerebellum [Right, shown as flatmap (119)] (separate scale used for each structure). (B) Canonical large-scale functional networks as defined by refs. , , and (Methods). (C) Mean intrinsic timescale (ACF decay) computed within each network for each brain structure analyzed. Mean and SE (error bars) computed across subjects (n = 1,139).

Fig. 4.

Individual variability in FC is linked to individual variability in intrinsic timescales. (A) Maps of cortical ACF decay (Left) and mean FC magnitude (i.e., FC strength; Methods) (Right) for two example individuals, MSC05 (Upper) and MSC06 (Lower). Compressed ACF decay range is due to high-pass filtering specific to this analysis (Methods). (B) For each individual, spatial correlation between the individual’s mean FC magnitude and all 10 individuals’ maps of intrinsic timescale (i.e., ACF decay) topography. The subject’s own map of intrinsic timescale is represented by solid colors.