Closed-loop auditory stimulation method to modulate sleep slow waves and motor learning performance in rats

Abstract

Slow waves and cognitive output have been modulated in humans by phase-targeted auditory stimulation. However, to advance its technical development and further our understanding, implementation of the method in animal models is indispensable. Here, we report the successful employment of slow waves’ phase-targeted closed-loop auditory stimulation (CLAS) in rats. To validate this new tool both conceptually and functionally, we tested the effects of up- and down-phase CLAS on proportions and spectral characteristics of sleep, and on learning performance in the single pellet-reaching task, respectively. Without affecting 24-h sleep-wake behavior, CLAS specifically altered delta (slow waves) and sigma (sleep spindles) power persistently over chronic periods of stimulation. Down-phase CLAS exerted a detrimental effect on overall engagement and success rate in the behavioral test, and overall CLAS-dependent spectral changes were positively correlated with learning performance. Altogether, our results provide proof-of-principle evidence that phase-targeted CLAS of slow waves in rodents is efficient, safe and stable over chronic experimental periods, enabling the use of this high-specificity tool for basic and preclinical translational sleep research.

Down‐phase auditory stimulation is not able to counteract pharmacologically or physiologically increased sleep depth in traumatic brain injury rats

“…In order to verify the effect of auditory stimulation on SWA, we conducted bilateral tethered EEG/EMG recordings (differential mode) during 24 hr, to serve as BL, and throughout the subsequent 5 treatment‐days (Figure 1c), and run our stimulation paradigm as previously described (Moreira et al, 2021). Briefly, following confirmation of impedances below 5 kΩ, we recorded EEG/EMG signals using SYNAPSE software (TDT, USA): the data were sampled at 610.35 Hz, amplified (bandwidth 0.1–285 Hz; PZ5 NeuroDigitizer preamplifier, TDT, USA) following an anti‐aliasing low‐pass filter (285 Hz, corresponding to 45% of sampling frequency), synchronously digitised (RZ2 BIOAMP processor, TDT, USA), and stored locally (WS‐8 workstation, TDT, USA).…”

“…Auditory stimulation of slow oscillations during NREM sleep was successfully implemented by presenting sound triggers real‐time locked with the phase of slow waves (Ngo et al, 2015). Targeting the ascending phase of slow waves enhances their amplitude and entrainment, with consequent impact on memory performance and restorative functions in both health and disease (Leminen et al, 2017; Ngo et al, 2013; Ong et al, 2016; Papalambros et al, 2017), whereas targeting the down‐phase of slow waves results in a decrease of SWA, which was associated with impaired behavioural performance (Fattinger et al, 2017; Moreira et al, 2021). However, to test the preclinical applicability and the degree of therapeutic potential of CLAS in a model of TBI, there are a few critical aspects we must explore further.…”

Manipulations of sleep‐like slow‐wave activity by noninvasive brain stimulation

“…Similarly, CLAS does not have any apparent effect on sleep structure or subjective sleep quality (Leminen et al, 2017). CLAS can also disrupt SWA during sleep (i.e., if delivered during down‐states), resulting in reduced cortical capacity to undergo plasticity changes and the ensuing learning performance (Fattinger et al, 2017; Moreira et al, 2021).…”

Neuronal‐spiking‐based closed‐loop stimulation during corticalON‐ andOFF‐states in freely moving mice

“…Sleep slow waves are homeostatically regulated (Achermann et al, 1993; Borbély, 1982; Huber et al, 2000; Krone et al, 2021; Thomas et al, 2020), and have been implicated in synaptic plasticity, metabolic restoration, glymphatic clearance and other functions (Frank & Heller, 2019; Krueger et al, 2016; Vyazovskiy & Harris, 2013). Traditionally, online detection of slow waves relies solely on their cortical surface‐ or scalp‐recorded electroencephalogram (EEG) waveforms (Moreira et al, 2021; Ngo et al, 2013; Santostasi et al, 2016), where the specific phase is assumed to correspond to periods of high or low neuronal activity (ON‐ and OFF‐states) or transitions between population activity and silence (McKillop et al, 2018; Nir et al, 2011). However, in such studies no attempts have been made to directly target the underlying neuronal network activity itself.…”