The quality & complexity of dreams appear to vary with our stages of sleep, consistent with a new analysis.
Before the 21 century, we usually think dreams only occurred during rapid eye movement (REM) sleep, but newer research shows people sometimes recall dreams even once they are woken from non-REM stages of sleep.
Whether these two sorts of dreaming are inherently different are some things neuroscientists are still trying to work out.
When patients are woken during paradoxical sleep, research reveals they will usually recall elaborate, vivid, & emotional story-like dreams. In contrast, those woken during non-REM stages remember their dreams less & dreams themselves tend to be more thought like.
These are important findings, but they’re supported subjective reports. REM dreams are often described in additional words but when the length of outline is controlled for, differences in elaboration disappear or are highly diminished.
Researchers in Brazil have now developed a high-speed analysing tool which will take these qualitative-reports & display them during a more objective graph form, taking under consideration biases for both length & language.
“We know REM dreams are longer & more like movies” says neuroscientist Sidarta Ribeiro from University of Sao Paulo in Brazil.
“Automating the method of study , as we did within the study, made possible the first-ever quantitative measurement of this structural difference.”
Compared to traditional methods, which believe parsing out the meaning of words, this non-semantic graph analysis was ready to instead specialise in the general tone of what was said.
Focusing on 133 previously collected dream-reports from 20 participants, who were woken at different stages of dreaming, researchers graphed out words, replacing them with the nodes on a graph.
Analysing their structural organisation, the new tool found REM dream reports were more complex & filled with connected information compared to dreams during non-REM sleep.
And this fact was true no matter the report’s length. “This is the first study to use graph theory to point out that REM dream reports have more structural connectedness than non-REM dream reports,” says neuroscientist Joshua Martin from the Humboldt University in Berlin.
“Not to depreciate the relevance of traditional methods, but these results are important because they show that computational methods are often applied to studies of dreaming.”
While non-REM sleep suspected of getting some restorative-function, we’re still not sure why paradoxical sleep exists. If dreaming during this stage is actually of a special quality, as this new research suggests, then REM & non-REM dreaming could be driven by distinct underlying mechanisms that would play differing roles in our biology.
Compared to REM dreams, dreams from N2 stage – a deep, non-REM, slow-wave sleep – were shorter, less frequently recalled, less intense & more thought-like.
Of course, sleep studies accompany many limitations beyond mere subjectivity. Being woken up continuously throughout the night could itself be impacting the standard of sleep among volunteers.
Recall of dreams may be warped by sleep inertia – that weird stage between waking & sleeping – although dreams narrative complexity appears to remain an equivalent even once participants have woken up properly.
While complex dream narratives may still occur in non-REM sleep, the authors suspect the very physiology of paradoxical sleep, which shows great cortical activity & muscle atonia, may be a better time for interactive-narratives to unfold uninterrupted.
“In this sense, dream experiences that are coherent, immersive, & story-like could also be more easily organized into a report with larger connectedness, while dream experiences that are fragmented & isolated are relatively harder to arrange mentally and thus are structurally less connected,” the authors explain.
Not only do the results of the study complement existing literature on dream reports & REM sleep , but they also support recent and more objective measurements of dream bank databases.
A study published in 2020, as an example , used an algorithm to sift through 24,000 dreams & located various “statistical markers” that support the hypothesis that our dreams are a continuation of everyday life.
One algorithm isn’t enough to put this mystery to bed, but mathematical tools like this one might be useful when it comes-to assessing our sleep and our dreams with as little bias and with as many considered factors as possible.
The current study was conducted at a much smaller-scale, but it offers a number of the first really objective measurements on dreams that we have got .
