Fig. 6: Global and local effects of the occurrence of slow waves on sub-components of decision-making.
From: Predicting lapses of attention with sleep-like slow waves
Reaction times in the Go/NoGo tasks were modelled according to a Hierarchical Drift-Diffusion Model (see “Methods”). a–f Topographical maps of the effect of slow waves (i.e. whether or not a slow wave was detected for each trial and for a specific electrode) on the parameters of decision-making: drift Go [vGo] (a), drift NoGo [vNoGo] (b), drift bias [vBias] (c), threshold [a] (d), non-decision time or NDT [t] (e), decision bias [z] (f). The effect of slow-wave occurrence was estimated with LMEs (see “Methods”) and topographies show the scalp distribution of the associated t values (N = 26 participants). Black dots denote significant clusters of electrodes (pcluster<0.05, Bonferroni-corrected, see “Methods”).
