Figure 7.

Increased responsiveness to perturbations in simulated wake-like compared to sleep-like states. Excitatory firing rate of a simulated brain region in time during wake-like (A) and sleep-like dynamics, in response to a stimulus. Black lines show the mean across 40 realizations, reminiscent of event-related potentials (ERPs), and gray shaded areas show the standard deviation from the mean across realizations. (B, C) Spatio-temporal propagation of responses to stimuli in wake-like (B) and sleep-like (C) states. Color plotted on the brain surface indicates earliest time at which each region becomes significantly different from its pre-stimulus baseline (see Methods), with earlier times in lighter colors. Regions in white do not present significant differences in firing rate in response to the stimulus. In wake-like states, stimulus responses recruit more brain regions and produce more spatially widespread and temporally sustained activity patterns, reminiscent of empirical observations. (D–F) Box plots of perturbational complexity index (PCI) measurements from 40 realizations of wake-like and sleep-like simulations with increasing stimulus amplitudes (panels left to right). Significant changes in the PCI are observed when the spike frequency adaptation (b_e) is varied (one-way Kruskal-Wallis test; p < 0.05 for each group of adaptation values, b_e = 0, 20, 40, 60, for each stimulus value (0.01, 0.1, and 1 Hz). Results of post-hoc Conover test for multiple comparisons between values of b_e are shown in the figure, where *p < 0.05, **p < 0.01, and ***p < 0.001). In high-adaptation, sleep-like regimes, a sharp drop in PCI is observed, denoting more spatio-temporally complex responses in the Lempel-Ziv sense in wake-like compared to sleep-like states, consistent with experiments (Massimini et al., 2005; Casali et al., 2013).