Hong-Viet V. Ngo

Auditory Closed-Loop Stimulation of the Sleep Slow Oscillation Enhances Memory

Brain rhythms regulate information processing in different states to enable learning and memory formation. The <1 Hz sleep slow oscillation hallmarks slow-wave sleep and is critical to memory consolidation. Here we show in sleeping humans that auditory stimulation in phase with the ongoing rhythmic occurrence of slow oscillation up states profoundly enhances the slow oscillation rhythm, phase-coupled spindle activity, and, consequently, the consolidation of declarative memory. Stimulation out of phase with the ongoing slow oscillation rhythm remained ineffective. Closed-loop in-phase stimulation provides a straight-forward tool to enhance sleep rhythms and their functional efficacy.

Induction of slow oscillations by rhythmic acoustic stimulation

Slow oscillations are electrical potential oscillations with a spectral peak frequency of ∼0.8 Hz, and hallmark the electroencephalogram during slow‐wave sleep. Recent studies have indicated a causal contribution of slow oscillations to the consolidation of memories during slow‐wave sleep, raising the question to what extent such oscillations can be induced by external stimulation. Here, we examined whether slow oscillations can be effectively induced by rhythmic acoustic stimulation. Human subjects were examined in three conditions: (i) with tones presented at a rate of 0.8 Hz (‘0.8‐Hz stimulation’); (ii) with tones presented at a random sequence (‘random stimulation’); and (iii) with no tones presented in a control condition (‘sham’). Stimulation started during wakefulness before sleep and continued for the first ∼90 min of sleep. Compared with the other two conditions, 0.8‐Hz stimulation significantly delayed sleep onset. However, once sleep was established, 0.8‐Hz stimulation significantly increased and entrained endogenous slow oscillation activity. Sleep after the 90‐min period of stimulation did not differ between the conditions. Our data show that rhythmic acoustic stimulation can be used to effectively enhance slow oscillation activity. However, the effect depends on the brain state, requiring the presence of stable non‐rapid eye movement sleep.

Driving Sleep Slow Oscillations by Auditory Closed-Loop Stimulation—A Self-Limiting Process

The <1 Hz EEG slow oscillation (SO) is a hallmark of slow-wave sleep (SWS) and is critically involved in sleep-associated memory formation. Previous studies showed that SOs and associated memory function can be effectively enhanced by closed-loop auditory stimulation, when clicks are presented in synchrony with upcoming SO up states. However, increasing SOs and synchronized excitability also bear the risk of emerging seizure activity, suggesting the presence of mechanisms in the healthy brain that counter developing hypersynchronicity during SOs. Here, we aimed to test the limits of driving SOs through closed-loop auditory stimulation in healthy humans. Study I tested a “Driving stimulation” protocol (vs “Sham”) in which trains of clicks were presented in synchrony with SO up states basically as long as an ongoing SO train was identified on-line. Study II compared Driving stimulation with a “2-Click” protocol where the maximum of stimuli delivered in a train was limited to two clicks. Stimulation was applied during SWS in the first 210 min of nocturnal sleep. Before and after sleep declarative word-pair memories were tested. Compared with the Sham control, Driving stimulation prolonged SO trains and enhanced SO amplitudes, phase-locked spindle activity, and overnight retention of word pairs (all ps < 0.05). Importantly, effects of Driving stimulation did not exceed those of 2-Click stimulation (p > 0.180), indicating the presence of a mechanism preventing the development of hypersynchronicity during SO activity. Assessment of temporal dynamics revealed a rapidly fading phase-locked spindle activity during repetitive click stimulation, suggesting that spindle refractoriness contributes to this protective mechanism.

A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation.

Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12–15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols.

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.

Triggering up states in all-to-all coupled neurons

Slow-wave sleep in mammalians is characterized by a change of large-scale cortical activity currently paraphrased as cortical Up/Down states. A recent experiment demonstrated a bistable collective behaviour in ferret slices, with the remarkable property that the Up states can be switched on and off with pulses, or excitations, of same polarity; whereby the effect of the second pulse significantly depends on the time interval between the pulses. Here we present a simple time discrete model of a neural network that exhibits this type of behaviour, as well as quantitatively reproduces the time-dependence found in the experiments.

Insights on auditory closed-loop stimulation targeting sleep spindles in slow oscillation up-states

BACKGROUND The consolidation of sleep-dependent memories is mediated by an interplay of cortical slow oscillations (SOs) and thalamo-cortical sleep spindles. Whereas an enhancement of SOs with auditory closed-loop stimulation has been proven highly successful, the feasibility to induce and boost sleep spindles with auditory stimulation remains unknown thus far. NEW METHOD Here we tested the possibility to enhance spindle activity during endogenous SOs and thereby to promote memory consolidation. Performing a sleep study in healthy humans, we applied an auditory Spindle stimulation and compared it with an Arrhythmic stimulation and a control condition comprising no stimulation (Sham). RESULTS With Spindle stimulation we were not able to directly entrain endogenous spindle activity during SO up-states. Instead, both Spindle and Arrhythmic stimulation evoked a resonant SO response accompanied by an increase in spindle power phase-locked to the SO up-state. Assessment of overnight retention of declarative word-pairs revealed no difference between all conditions. COMPARISON WITH EXISTING METHODS Our Spindle stimulation produced oscillatory evoked responses (i.e., increases in SOs and spindle activity during SO up-states) quite similar to those observed after the auditory closed-loop stimulation of SOs in previous studies, lacking however the beneficial effects on memory retention. CONCLUSION Our findings put the endeavour for a selective enhancement of spindle activity via auditory pathways into perspective and reveal central questions with regard to the stimulation efficacy on both an electrophysiological and a neurobehavioral level.

Dynamics of the thalamo-cortical system driven by pulsed sensory stimulation

There exists a large body of evidence pointing to an essential role of sleep in memory consolidation [1-3]. In particular non-REM sleep seems to be important for consolidating declarative memories [4]. Boosting the so-called slow oscillations (<1 Hz) during non-REM sleep via transcranial electric stimulation leads to a potentiation of memory [5]. It has also been demonstrated that slow oscillations can be induced by optogenetic, magnetic and acoustic stimulation [6-8]. Here we present data from human sleep studies and modeling results on the thalamo-cortical system under sensory stimulation, that give new clues for effective stimulation protocols. We use a population model that exhibits important features of brain activity during non-REM sleep, e.g. spindles, cortical slow oscillations with gamma activity and clock-like delta oscillations. The model aims at reproducing evoked responses of auditory and visual stimuli at several frequencies. We extend previous results on the phase-dependent response of isolated cortex [9] to stimuli which are time-locked to spindle and slow oscillation events and test the hypothesis that the main factor determining thalamic gating properties in non-REM sleep is the phase of the cortical slow oscillation.

Differential influence of sinusoidal and noisy inputs on synaptic connections in a network with STDP

We hypothesize that the type of cortical network activation influences synaptic connectivity in the network, eventually expressed in an altered responsiveness to external stimuli. Our predictions are based on a time discrete canonical model of spike-time–dependent plasticity. The results show that, at a given synaptic connection strength in the network, sinusoidal input to the network can decrease synaptic potentiation whereas uncorrelated noise increases synaptic potentiation, implying that these opposing effects manifest themselves in respective decreases and increases of the network response to an external stimulus. These predictions are in qualitative agreement with visually evoked responses obtained in humans after 9 hour periods of visual deprivation (used to increase sinusoidal EEG alpha-activity in cortical networks) or normal daytime vision (as an approximate of noise input).