Electrophysiological Correlates of Lucid Dreaming: Sensor and Source Level Signatures.
Çağatay Demirel, Jarrod Gott, Kristoffer Appel, Katharina Lüth, Christian Fischer, Cecilia Raffaelli, Britta Westner, Xinlin Wang, Zsófia Zavecz, Axel Steiger, Daniel Erlacher, Stephen LaBerge, Sérgio Mota-Rolim, Sidarta Ribeiro, Marcel Zeising, Nico Adelhöfer, Martin Dresler
The Journal of neuroscience : the official journal of the Society for Neuroscience May 14, 2025 DOI: 10.1523/JNEUROSCI.2237-24.2025 via PubMed
Summary
AI-generated from the abstractLucid dreaming, where a person becomes aware they are dreaming, is linked to REM sleep. To overcome previous research limitations, a new preprocessing pipeline was applied to pooled EEG data from multiple labs. Sensor-level differences between lucid and nonlucid REM sleep were minimal, but source-level analysis revealed reduced beta power (12-30 Hz) in right central and parietal areas, including the temporoparietal junction, during lucid dreaming. Alpha-band (8-12 Hz) connectivity increased compared to nonlucid REM sleep. During eye signaling of lucidity, gamma1 power (30-36 Hz) increased in right temporo-occipital regions, including the precuneus, and interhemispheric gamma1 connectivity rose. These patterns suggest shifts in network communication underlying changes in perception, self-awareness, and cognitive control.
Study at a glance
| Characteristics | Observational study with pooled EEG data across laboratories Peer reviewed |
|---|---|
| Population | Human participants (male and female) |
| Topics | Lucid dreaming |
| Keywords | Metacognition Self-awareness Lucid-dreaming lucid dreams Consciousness awareness Sleep-science rem sleep |
| Citations | 8 |
| Key finding | Lucid dreaming is characterized by reduced beta power in right central and parietal regions, increased alpha-band connectivity, and increased gamma1 power and connectivity during eye signaling, indicating distinct neural dynamics. |
Abstract
Lucid dreaming (LD) is a state of conscious awareness of the ongoing oneiric state, predominantly linked to REM sleep. Progress in understanding its neurobiological basis has been hindered by small sample sizes, diverse EEG setups, and artifacts like saccadic eye movements. To address these challenges in characterizing the electrophysiological correlates of LD, we introduced an adaptive multistage preprocessing pipeline, applied to human data (male and female) pooled across laboratories, allowing us to explore sensor- and source-level markers of LD. We observed that, while sensor-level differences between LD and nonlucid REM sleep were minimal, mixed-frequency analysis revealed broad low alpha to gamma power reductions during LD compared with wakefulness. Source-level analyses showed significant beta power (12-30 Hz) reductions in right central and parietal areas, including the temporoparietal junction, during LD. Moreover, functional connectivity in the alpha band (8-12 Hz) increased during LD compared with nonlucid REM sleep. During initial LD eye signaling compared with the baseline, source-level gamma1 power (30-36 Hz) increased in right temporo-occipital regions, including the right precuneus. Finally, functional connectivity analysis revealed increased interhemispheric and inter-regional gamma1 connectivity during LD, reflecting widespread network engagement. These results suggest that distinct source-level power and connectivity patterns characterize the dynamic neural processes underlying LD, including shifts in network communication and regional activation that may underlie the specific changes in perception, memory processing, self-awareness, and cognitive control. Taken together, these findings illuminate the electrophysiological correlates of LD, laying the groundwork for decoding the mechanisms of this intriguing state of consciousness.