Structural differences between REM and non-REM dream reports assessed by graph analysis
Open accessPreprint — published as 10.1371/journal.pone.0228903
Abstract
Dream reports collected after rapid eye movement sleep (REM) awakenings are, on average, longer, more vivid, bizarre, emotional and story-like compared to those collected after non-REM. However, a comparison of the word-to-word structural organization of dream reports is lacking, and traditional measures that distinguish REM and non-REM dreaming may be confounded by report length. This problem is amenable to the analysis of dream reports as non-semantic directed word graphs, which provide a structural assessment of oral reports, while controlling for individual differences in verbosity. Against this background, the present study had two main aims: Firstly, to investigate differences in graph structure between REM and non-REM dream reports, and secondly, to evaluate how non-semantic directed word graph analysis compares to the widely used measure of report length in dream analysis. To do this, we analyzed a set of 125 dream reports obtained from 19 participants in controlled laboratory awakenings from REM and N2 sleep. We found that: (1) graphs from REM sleep possess a larger connectedness compared to those from N2; (2) measures of graph structure can predict ratings of dream complexity, where increases in connectedness and decreases in randomness are observed in relation to increasing dream report complexity; and (3) measures of the Largest Connected Component of a graph can improve a model containing report length in predicting sleep stage and dream complexity. These results indicate that dream reports sampled after REM awakening have on average a larger connectedness compared to those sampled after N2 (i.e. words recur with a longer range), a difference which appears to be related to underlying differences in dream complexity. Altogether, graph analysis represents a promising method for dream research, due to its automated nature and potential to complement report length in dream analysis.
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REM dreams are more complex and have a larger connectedness (though graph-theoretically less random-like) than NREM dreams.
“the analysis of dream protocols by non-semantic word graphs has shown that REM dreams are more complex and have a larger connectedness (although they are graph-theoretically less random-like) than NREM dreams [78].”
From How Adversarial REM Dreams May Facilitate Creativity, and Why We Become Aware of Them (2024) · cites this paper as [78]
The Discussion and Conclusions report larger graph connectedness in REM than N2 dream reports and associate more complex dreams with larger connectedness. But the section “REM Reports Are Longer and Have Larger Connectedness Compared to N2” explicitly says the study found no difference between REM and non-REM reports in random-likeness, contrary to the citing sentence’s comparative claim. (LLM, conf=0.92)
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Erregungs- und Regulationssysteme im System der Research Domain Criteria
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“Neurophysiologists have perceived NREM sleep stages as periods of reduced arousal threshold, relative quiescence, and slower brain activity compared to wakefulness (Martin et al. 2020).”
The clinical use of dream content in modern psychiatry
Plevin, D. M., & Munro, V. (2025) · Australasian Psychiatry · doi:10.1177/10398562241311926 · Cited by 1 · see citing works
“8 It is now known that there are two brain areas crucial to dream development.”
Jigalin, R., & Schredl, M. (2025) · Sleep Science · doi:10.1055/s-0045-1809924
“22,23 Retrospective methods primarily capture acted-out dreams, which are better remembered in hindsight, while prospective methods, by including non-acted-out dreams, capture a broader range of dreams.”
Creating Authentic Assessment Tools for Independent Learning in Islamic Boarding Schools
Zuniati, M., Wawan, W., Anggraini, D., et al. (2024) · Jurnal Inovasi dan Pengembangan Hasil Pengabdian Masyarakat · doi:10.61650/jip-dimas.v2i1.555
A Review of Sleep Process and Influencing Factors
Jin, Z. (2022) · Highlights in Science Engineering and Technology · doi:10.54097/hset.v14i.1611
“Basically, sleep structure is divided into REM sleep and NREM sleep, and NREM includes light and deep sleep.”
BackgroundInfluentialLeveraging Large Language Models for Dream Analysis
Srivastava, A. K., Haque, M. A., & Ahmad, T. (2026) · Procedia Computer Science · doi:10.1016/j.procs.2026.05.142
ANNs Dream of Augmented Sheep: An Artificial Dreaming Algorithm
Assunção, G., Castelo-Branco, M., & Menezes, P. (2022) · International Conference on Image Processing and Vision Engineering · doi:10.5220/0011055700003209
“Opposing wave activity makes for an easy distinction between the two stages (Martin et al., 2020).”
- Authors
- Martin, J. M., Wainstein, D., Mota, N. B., Mota-Rolim, S. A., Araújo, J. F., Solms, M., & Ribeiro, S.
- Affiliations
- Universidade Federal do Rio Grande do Norte (BR)
- University of Cape Town (ZA)
- Corresponding author
- Ribeiro, Sidarta
- Venue
- PLoS ONE
- Publisher
- openRxiv
- Published
- 2020-01-28
- Volume
- 15
- Issue
- 7
- Pages
- e0228903-e0228903
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7377375
- OpenAlex
- W3044697089
- Cited by
- 45
- References
- 45
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 13 · 2023: 6 · 2022: 8 · 2021: 3
- FWCI
- 2.28
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PLoS ONE (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- Funders
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2013-07699-0, 13/07699-0)
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (2013/07699-0, 308775/2015-5, 408145/2016-1)
- Governo Brasil
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (2013/07699–0, 308775/20155, 408145/2016-1)
- Financiadora de Estudos e Projetos (2013/07699-0)
- Fundação de Apoio à Pesquisa do Rio Grande do Norte
- University of Cape Town (457091)
- Ministério da Ciência e Tecnologia
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- REM sleep, NREM sleep, dream narrative, graph structure, graph connectivity, largest connected component, report length, sleep stage classification, dream vividness, N2 sleep
- MeSH terms
- Adolescent, Adult, Dreams, Female, Humans, Male, Mental Recall, Sleep Stages, Sleep, REM, Time Factors, Linear Models, Young Adult
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