Modulation of the brain's functional network architecture in the transition from wake to sleep

Abstract

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes.

Fig. 1

αHDR to BOLD correlations. (a) Data are illustrated over 5 min duration runs (3/subject, 24 subjects). (b) Data are illustrated over 20 min duration runs (1/subject, 21 subjects). In color figures, hot colors represent positive correlations, while cool colors indicate anticorrelated activity. Statistical maps are shown for a fixed effects analysis corrected for multiple comparisons (p<0.05).

Fig. 2

A hallmark of the descent to sleep is the reduction in functional anticorrelations between core regions of the default mode network and those of dorsal attention and executive control networks. **p<0.001 and *p<0.05.

Fig. 3

Map of regions used in global network analysis of the transitional states from wake to sleep are illustrated as spheres centered on the coordinates for 151 regions of interest derived from a meta-analysis of task fMRI studies. Spheres are illustrated larger than 10 mm for ease of visualization. The legend indicates the meta-analysis task region nearest the combined region illustrated.

Fig. 4

Community structure in the wake state global network architecture. CARET maps show the communities to which each of 151 regions of interest were assigned. Notably, regions segregate into communities whose anatomical locations are consistent with a set of neural networks (legend) defined both on task and resting state fMRI. The central map illustrates community structure using the SoNIA visualization tool based on modularity analysis of global network structure. Subnetwork connectedness and the degree to which each community segregates from others in the network can be seen using this tool.

Fig. 5

Summary of changes in network community structure in the state change from wake to N2 sleep. The upper panel plots all 151 nodal regions of interest as a function of their modularity assignment for three neural states: wake, N1, and N2 sleep. Subnetworks are assigned a subnet-specific pattern with network label noted above the panel. Shifts in regional network community assignments are illustrated on CARET maps (left hemisphere only) to indicate their spatial location.