Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep
- Washington University in St. Louis, United States
- Christian-Albrechts-Universität zu Kiel, Germany
- Goethe-Universität Frankfurt am Main, Germany
Figures
Figure 1
Calculation of lag structure using lagged cross-covariance functions and parabolic interpolation.
Lags are defined by analysis of timeseries derived from two loci. (A) Two exemplar loci (both in the default mode network). The time series were extracted from the illustrated loci over ~200 s. (B) …
Figure 2
Lag projection maps in wake and slow wave sleep.
Lag projection maps depict the mean lag between each voxel and the rest of the brain (Mitra et al., 2014; Nikolić, 2007). Panels A-B display lag projection maps, in units of seconds, derived from …
Figure 3 with 2 supplements
Seed-based lag maps in wake and SWS corresponding to the subcortical regions identified in Figure 2C: thalamus (A), putamen (B), and brainstem (C).
Also shown are lag difference maps (SWS minus wake) thresholded for cluster-wise statistical significance ( Z > 4.5, p<0.05 corrected; as in Figure 2C). During wake, the cerebral cortex is generally …
Figure 3—figure supplement 1
Expanded view of seed-based lag maps derived using thalamus, putamen, and brainstem regions of interest defined in Figure 2C.
Axial and Sagittal slices as in Figure 1. Coronal slice: Y = +12.
Figure 3—figure supplement 2
Seed-based lag difference maps thresholded for cluster-wise statistical significance of p<0.05 (as in Figure 2).
All significant lag differences are negative (blue), and predominantly found in cortex, indicating that many areas of cortex become significantly earlier than subcortical structures during SWS as …
Figure 4 with 2 supplements
Seed-based lag maps in wake and SWS corresponding to the cortical regions identified in Figure 2C: visual cortex (A), medial prefrontal cortex (B), and paracentral lobule (C).
Also shown are lag difference maps (SWS minus wake), thresholded for statistical significance, as in Figure 2. Panel A shows that, whereas the visual seed is neither wholly late nor early in wake, …
Figure 4—figure supplement 1
Expanded view of seed-based lag maps derived using visual, medial prefrontal cortex, and paracentral lobule regions of interest defined in Figure 2C.
Slice coordinates identical to Figure 3—figure supplement 1.
Figure 4—figure supplement 2
Seed-based lag difference maps thresholded for cluster-wise statistical significance (as in Figure 2).
For the visual cortex seed, nearly the entire cortex becomes late (red) with respect to visual cortex in SWS compared to wake. These effects are especially prominent in paracentral lobule and …
Figure 5 with 2 supplements
Time delay (TD) matrices.
Panels A-B display TD matrices (in units of seconds) in wake and SWS, respectively. Each pixel represents the lag between two voxels. TD matrices are, by definition, anti-symmetric. Hence, all …
Figure 5—figure supplement 1
Time delay (TD) matrices as a function of sleep stage, alternate voxel orderings.
(A) Wake. (B-C) N2 sleep. (D-E) N3 sleep (SWS). Panels A and D duplicate panels A and B in Figure 5. Panels C and E provide an alternative view of cross-RSN lag structure disorganization during …
Figure 5—figure supplement 2
Resting state network (RSN) assignments for gray matter voxels used to compute the TD matrix and functional connectivity matrix results shown in main Figures 5, 6.
This figure illustrates the 1065 (6 mm)3 gray matter voxels satisfying a criterion of ≥90% probability of belonging to one of the 7 cortical resting state networks defined in (Hacker et al., 2013). …
Figure 6
Zero-lag correlation (conventional functional connectivity; FC) matrices.
(A): wake. (B): slow wave sleep. Voxels shown in the correlation matrices correspond to Figure 5A, B (see also Figure 5—figure supplement 2), and matrix values are Fisher-z transformed Pearson …
Figure 7 with 2 supplements
Lag structure dimensionality in wake and SWS.
We have previously shown that multiple temporal sequences can be extracted from a TD matrix by applying spatial principal components analysis (PCA) to the TD matrix after zero-centering each column …
Figure 7—figure supplement 1
Lag thread topographies in wake corresponding to the eigenvalues shown in Figure 7.
Four lag threads are shown in accordance with the maximum likelihood dimensionality estimate. The illustrated topographies are comparable to the first 4 lag threads shown in Figure 2 of Mitra et …
Figure 7—figure supplement 2
Lag threads topographies in SWS.
Note pronounced differences in comparison to lag threads obtained in wake (Figure 7—figure supplement 1). SWS lag threads 1 and 3 show visual earliness and paracentral lobule lateness, as in Figure 2…
