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Title: Structural differences between REM and non-REM dream reports assessed by graph analysis
Authors: Martin, Joshua Michael
Andriano, Danyal Wainstein
Mota, Natália Bezerra
Rolim, Sérgio Arthuro Mota
Araujo, John Fontenele
Ribeiro, Sidarta Tollendal Gomes
Keywords: Dreams;Sleep, REM;Sleep stages
Issue Date: 23-Jul-2020
Citation: MARTIN, Joshua M.; ANDRIANO, Danyal Wainstein; MOTA, Natalia B.; MOTA-ROLIM, Sergio A.; ARAÚJO, John Fontenele; SOLMS, Mark; RIBEIRO, Sidarta. Structural differences between REM and non-REM dream reports assessed by graph analysis. Plos One, [S.l.], v. 15, n. 7, p. e0228903, jul. 2020. Disponível em: Acesso em: 27 jul. 2020.
Portuguese 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 133 dream reports obtained from 20 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 report 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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