Functional Structure of Spontaneous Sleep Slow Oscillation Activity in Humans

Abstract

BackgroundDuring non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.Methodology/Principal FindingsWe detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.Conclusions/SignificanceThis work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.

Slow Oscillations during Sleep Coordinate Interregional Communication in Cortical Networks

“…Concerning commonalities, our data show that, whenever reliable SO modulation of brain processing was observed, it was consistently localized around the site of SO detection. These local modulations of information processing fit with previous evidence showing that individual SOs can emerge locally on the scalp and travel across the cortical surface in idio- syncratic trajectories Menicucci et al, 2009). Thus, our findings suggest that, as an SO sweeps across the cortex, it organizes neural processing locally along its pathway.…”

“…Intriguingly, SO modulations have been related to prior daytime learning Mölle et al, 2004Mölle et al, , 2009Mölle et al, , 2011, and SOs are causally involved in the offline reprocessing and stabilization of memories (Marshall et al, 2006;Antonenko et al, 2013;Ngo et al, 2013). Such sleep-related memory stabilization is widely held to involve the reactivation of memory traces in hippocampo-neocortical networks, leading to the formation of hippocampus-independent links between cortically distributed memory representations (Marr, 1971;Frankland and Bontempi, 2005).…”

Cordycepin Increases Nonrapid Eye Movement Sleep via Adenosine Receptors in Rats

“…On the contrary, theta waves in NREM sleep were significantly increased, delta waves in NREM sleep slightly decreased, and no change in alpha waves was observed. Theta waves between alpha and delta waves in wavelength specially were increased in NREM sleep [26]. …”

29 (CR). Axillary-Femoral Bypass May Provide Inadequate Distal Perfusion Compared To In-Line Large Diameter Aortic Reconstruction

“…Other a posteriori estimates of proneness to bistability have the advantage of being computable event by event: These are the two morphological features of the SSO shown in Fig. These SSO parameters were measured on the signal filtered in the delta (0.5-4.0 Hz) band (for the filter implementation details see Menicucci et al, 2009or Piarulli et al, 2010. SSO amplitude is defined as the peak-to-peak voltage range and reflects how many pyramidal neurons synchronously undergo bistability (cellular down and up state); slope 1 is defined as the steepness of the wave between the first zero crossing and the negative peak and corresponds to the neuronal pool synchronization in falling into the down state Vyazovskiy et al, 2007;Chauvette et al, 2010).…”