Novel murine closed-loop auditory stimulation paradigm elicits macrostructural sleep benefits in neurodegeneration

Author:

Dias InêsORCID,Kollarik SedefORCID,Siegel Michelle,Baumann Christian R.,Moreira Carlos G.ORCID,Noain DanielaORCID

Abstract

AbstractBoosting slow-wave activity (SWA) by modulating slow-waves through closed-loop auditory stimulation (CLAS) might provide a powerful nonpharmacological tool to investigate the link between sleep and neurodegeneration. Nevertheless, CLAS in this context was not yet explored. Here, we established mouse CLAS (mCLAS)-mediated SWA enhancement and explored its effects onto sleep deficits in neurodegeneration, by targeting the up-phase of slow-waves in mouse models of Alzheimer’s (AD, Tg2576) and Parkinson’s disease (PD, M83). We found that tracking a 2Hz component of slow-waves leads to highest precision of NREM sleep detection in mice, and that its combination with a 30° up-phase-target produces a significant SWA 15-30% increase from baseline in WTADand TGADmice versus a MOCK group. Conversely, combining 2Hz with a 40° phase target yields a significant increase ranging 30-35% in WTPDand TGPDmice. Interestingly, these phase-target-triggered SWA increases are not genotype dependent but strain specific. Sleep alterations that may contribute to disease progression and burden were described in AD and PD lines. Notably, pathological sleep traits where rescued by mCLAS, which elicited a 14% decrease of pathologically heightened NREM sleep fragmentation in TGADmice, accompanied by a steep decrease in microarousal events during both light and dark periods. Overall, our results indicate that model-tailored phase-targeting is key to modulate SWA through mCLAS, prompting the acute alleviation of key neurodegeneration-associated sleep phenotypes and potentiating sleep regulation and consolidation. Further experiments assessing the long-term effect of mCLAS in neurodegeneration may majorly impact the establishment of sleep-based therapies.

Publisher

Cold Spring Harbor Laboratory

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