The present study demonstrates that tSOS applied during non-REM sleep in an afternoon nap, in comparison with sham stimulation, enhanced subsequent declarative learning of pictures, word pairs, and word lists, whereas training of a procedural finger sequence tapping skill remained unaffected. As expected, tSOS increased the depth of non-REM sleep by increasing SWS and, as a hallmark of SWS, SWA. Acutely, tSOS phase-locked spindle activity to the up-state of the induced slow oscillation. In combination, these findings corroborate and extend previous observations (Van Der Werf et al., 2009) pointing to a causative role of SWA in providing capacities for encoding of new information in the hippocampus-dependent memory system for the upcoming period of wakefulness.
Increase in SWA and depth of non-REM sleep
The application of tSOS oscillating at 0.75 Hz proved to be effective in enhancing SWA and SWS. The effects of tSOS are known to be state-dependent (Steriade et al., 1993; Kanai et al., 2008). Thus, we only applied tSOS when subjects were in non-REM sleep and cortical circuits preferentially resonate in the slow oscillation frequency, which ensured that the effect of tSOS expressed itself mainly as an enhanced SWA. Whereas, during the acute periods of stimulation, endogenous SWA generated in cortical tissue cannot be readily separated from activity in the same frequency band that is related to the stimulation signal, analysis of 1-min periods following the 4-min periods of tSOS confirmed a distinct increase in SWA, especially during the first periods of stimulation. This observation agrees with previous studies (Marshall et al., 2006) in which a similar stimulation protocol conducted during nocturnal sleep enhanced both SWA and SWS during the stimulation-free intervals immediately after the periods of stimulation, with the effects being also most pronounced during the first three post-stimulation periods.
Considering that, in those previous studies, owing to the strong contamination originating from the stimulation signal, EEG data during actual electrical stimulation could not be analysed, the present study including such analyses of EEG activity during ongoing stimulation represents a clear advance over this previous work. Our time–frequency analyses revealed pronounced phase-coupling of EEG activity in a broad frequency range of 8–20 Hz to the tSOS-induced slow oscillation signal, such that, among activity in other frequency bands, activity in the spindle band culminated during the anodal up-phases of the oscillation. The detection of discrete spindles and the event correlation histograms calculated across all spindle events (peaks and troughs) of all detected spindles clearly showed that those spindles detected during the stimulation were grouped by the up-phases of the oscillating stimulation signal. This observation not only corroborates the acute effectiveness of tSOS, but also strongly supports the conclusion that tSOS-induced SWA does indeed mimic physiologically normal conditions, because, also under natural conditions, endogenous slow oscillations drive spindle generation such that spindles occur preferentially during the slow oscillation up-phase (Mölle et al., 2002, 2011; Steriade, 2003; Steriade & Timofeev, 2003). On the other hand, this finding tempts us to speculate that phase-coupling of spindle activity might secondarily contribute to the enhancing effects of tSOS-induced slow oscillations on encoding. However spindle activity as such is unlikely to be an effective mediator of the enhanced encoding capabilities after tSOS, as spindle activity as such did not differ between the stimulation and sham conditions, and was also not positively correlated in any way with measures of encoding. The fact that induction of slow oscillations by tSOS prevents any direct measurement of endogenous slow oscillations is an obvious limitation of our approach. However, it is of importance in this context that, for tSOS, we chose the maximum current amplitude, such that it induced, in the underlying neocortex, potential fields of a similar amplitude as those naturally observed during SWA, thus closely mimicking endogenous slow oscillations (Steriade et al., 1996). Together, these observations justify the conclusion that the potential fields associated with the occurrence of slow oscillations and SWA do indeed play a causal role in the beneficial effect that these brain oscillations during sleep have on the encoding of information during succeeding wakefulness.
Enhanced learning of declarative but not procedural tasks
The main finding of our study is that tSOS-induced slow oscillation activity during a nap consistently improved subsequent learning on different declarative tasks, whereas training of a procedural skill (finger sequence tapping) was completely unaffected. As training of finger sequence tapping skills is less dependent on hippocampal function than is learning of the declarative tasks, this pattern of findings suggests that SWA particularly benefits encoding in the hippocampus-dependent declarative memory system (Squire et al., 1993; Squire & Zola, 1996; Gais & Born, 2004; Debas et al., 2010). In fact, our pattern of findings is well in line with recent findings by Van Der Werf et al. (2009), who tested changes in the learning of declarative and procedural tasks following suppression of SWA during nocturnal sleep by acoustic stimulation. In that study, suppression of SWS, as compared with undisturbed sleep, significantly impaired the encoding of pictures, and this was associated with a significant decrease in hippocampal activation during encoding, whereas training of a finger sequence tapping skill, as in our study, was not influenced by manipulation of SWA. Thus, the results from these two studies are strikingly complementary, although the studies also differed to some extent in their approach and design. Here, we not only enhanced SWA through tSOS, rather than suppressing SWA through acoustic stimulation, but also modified SWA during a single sleep cycle of a nap, rather than during a full night of sleep. Unlike in the study of Van der Werf et al., the encoding period in our study took place immediately after sleep, and retrieval was tested after only a short delay, rather than after another night of sleep. Thus, our procedure enabled a more direct assessment of encoding quality (in the absence of any confounding effects of intervening sleep). Importantly, we show enhancing effects of tSOS-induced SWA not only for the learning and subsequent recognition of pictures, but also for the free and cued recall of learnt verbal materials. Cued and free recall paradigms probe the hippocampal contribution to a memory representation, which basically relies on the forming of new associative connections, to a greater extent than recognition (Tulving & Madigan, 1970; Squire et al., 2007). Thus, the mechanisms and brain regions mediating cued or free recall and recognition differ. Whereas cued and free recall critically rely on a fine-tuned interaction between the prefrontal and hippocampal circuitry, hippocampal contributions to recognition performance are less essential (Mayes et al., 2002; Barbeau et al., 2005; Holdstock et al., 2005; Squire et al., 2007). Hence, our finding that tSOS-enhanced SWA improved the subjects' ability to learn word pairs and word lists as assessed by cued and free recall is another strong hint that the benefit of SWA for encoding of information pertains in particular to the hippocampus-dependent declarative memory system. Along this line of reasoning, there is also evidence from studies in humans and rats that the effects of tSOS on word list learning observed here, indicating an increased susceptibility to proactive interference, likewise reflect basically improved encoding within the prefrontal–hippocampal circuitry (Han et al., 1998; Caplan et al., 2007; Malleret et al., 2010). Thus, rats with neurotoxic lesions to the hippocampus performed better than control rats on a configural learning task specifically when short intertrial intervals were used, because, in this condition, unlike in the controls, performance was not disturbed by proactively interfering response tendencies from the preceding trial (Han et al., 1998). These and related findings suggest that enhanced encoding of events, as observed here after tSOS, may express itself as a transient impairment in encoding similar events, representing enhanced sensitivity to proactive interference. On the other hand, performance on control tests such as the digit span test, which did not indicate any difference between the tSOS and sham stimulation conditions, excluded the possibility that the improved encoding of hippocampus-dependent information after tSOS was secondary to a general improvement in prefrontal working memory function.
The synaptic down-scaling hypothesis is an attractive concept with which to explain our results (Tononi & Cirelli, 2003, 2006; Huber et al., 2007; Massimini et al., 2009). The concept assumes that synaptic connections become globally potentiated, in some cases close to saturation, while information is encoded during wakefulness, and that subsequent SWA during SWS serves to broadly depotentiate and decrease the strength of synaptic connections, thereby renewing the capacity and preparing the synaptic network for the encoding of new information during the following period of wakefulness. As the concept currently concentrates on the homeostatic regulation of synaptic strength within neocortical networks, it does not account for our findings pointing towards a beneficial effect of induced SWA and slow oscillations preferentially on the hippocampal encoding of information. Indeed, we did not observe any improvement in the learning of procedural finger sequence tapping, which is a task relying more on corticostriatal than hippocampal circuitry (Squire et al., 1993; Squire & Zola, 1996; Debas et al., 2010). Although the hippocampus itself does not generate slow oscillations, it is reached by neocortically generated slow oscillations synchronizing hippocampal with neocortical activity (Sirota & Buzsaki, 2005; Isomura et al., 2006; Clemens et al., 2007; Mölle et al., 2009; Nir et al., 2011). Changes in membrane potentials of hippocampal interneurons are phase-locked to the neocortical slow oscillation, with the synchronizing influence of the neocortical slow oscillation probably being mediated via the temporo-ammonic pathway (Hahn et al., 2006; Wolansky et al., 2006). On this background, our findings tempt us to conclude that SWA and slow oscillations spreading from their neocortical origin down-scale synapses predominantly in the hippocampal circuitry, perhaps because of the generally greater synaptic plasticity of hippocampal than of neocortical networks, although, on the basis of the available data, this conclusion remains tentative. Alternatively, the fact that tSOS specifically improves declarative but not procedural encoding might be attributed to synaptic down-scaling within neocortical networks, whereby tSOS, owing to the positioning of the stimulation electrodes, might have predominantly affected anterior rather than posterior cortical regions. However, this interpretation is unlikely, because procedural learning tasks such as finger sequence tapping also essentially involve frontal cortical areas (e.g. Heun et al., 2004; Fischer et al., 2005). Thus, if tSOS had induced synaptic down-scaling mainly in anterior neocortical networks, this should have also improved learning on the finger sequence tapping task. Slow oscillations support the long-term consolidation of hippocampal memories, presumably by driving the neuronal replay and redistribution of newly encoded hippocampal representations towards neocortical sites of long-term storage (Marshall et al., 2006; Ji & Wilson, 2007; Diekelmann & Born, 2010). The present data suggest that the down-scaling and memory-consolidating actions of slow oscillations in the hippocampus are linked, such that the slow oscillation-induced reactivation and redistribution of recently encoded memories results in a freeing of hippocampal capacities for the encoding of new information.
It is known that sleep and, particularly, SWS facilitate consolidation of hippocampus-dependent declarative memories. In addition, findings after sleep deprivation have pointed to a ‘forward’ role of sleep in promoting the learning of new materials during subsequent wakefulness (McDermott et al., 2003; Yoo et al., 2007). The involvement of SWA was indicated by a recent study revealing impaired encoding of declarative memories after suppression of SWA (Van Der Werf et al., 2009). In contrast, our study demonstrates a direct enhancing effect of tSOS-induced SWA on the encoding of declarative memory. In combination, these findings corroborate a causal link between sleep SWA and the renewal of hippocampal encoding capacities. Because procedural learning did not benefit from enhanced SWA, SWA-dependent renewal of encoding capacities and the putative underlying processes of synaptic down-scaling appear to predominantly impact on hippocampal networks.