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CC BY-NC-ND 4.0 · Sleep Sci 2023; 16(04): e408-e416
DOI: 10.1055/s-0043-1776749
Original Article

Detecting Lucid Dreams by Electroencephalography and Eyebrow Movements

Michael Raduga 
REMspace, Phase Research Center, Novorossiysk, Krasnodar Krai, Russia
,
Andrey Shashkov
REMspace, Phase Research Center, Novorossiysk, Krasnodar Krai, Russia
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Abstract

Objective When metacognition arises during rapid eye movement (REM) sleep, people experience lucid dreaming (LD). Studies on this phenomenon face different obstacles. For example, its standard verification protocol requires at least three types of sensors. We hypothesized that preagreed frontalis movements (PAFMs), as a sign of lucidity, could be seen on electroencephalography (EEG) during REM sleep. In this case, only one EEG sensor would be needed to verify LD.

Method Under laboratory observation, five volunteers were instructed to induce LD, during which they needed to use the standard verification protocol with pre-agreed eye movements (PAEMs) and then immediately raise their eyebrows three times as a PAFM.

Results All participants were able to send signals from a total of eight LDs using one or both methods. Preagreed frontalis movements and PAEMs were equally distinctive on most EEGs, but PAFM quality was strongly dependent on the accuracy of the method. Preagreed frontalis movements exhibited two types of EEG patterns and led to immediate awakening when LD was not stable.

Discussion Though the outcomes show that PAFMs can be used to verify LD, this method was less consistent and apparent than PAEMs. Furthermore, accurate instructions are needed before using PAFMs. When polysomnography is unavailable, PAFMs can be applied, as it requires only one EEG sensor to detect REM sleep and consciousness simultaneously.

Keywords

lucid dreaming - REM sleep - electroencephalography - consciousness


Publication History

Received: 28 June 2022

Accepted: 26 January 2023

Article published online:
22 November 2023

© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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