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Dream to Predict? REM Dreaming as Prospective Coding

Overview of attention for article published in Frontiers in Psychology, January 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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Title
Dream to Predict? REM Dreaming as Prospective Coding
Published in
Frontiers in Psychology, January 2016
DOI 10.3389/fpsyg.2015.01961
Pubmed ID
Authors

Sue Llewellyn

Abstract

The dream as prediction seems inherently improbable. The bizarre occurrences in dreams never characterize everyday life. Dreams do not come true! But assuming that bizarreness negates expectations may rest on a misunderstanding of how the predictive brain works. In evolutionary terms, the ability to rapidly predict what sensory input implies-through expectations derived from discerning patterns in associated past experiences-would have enhanced fitness and survival. For example, food and water are essential for survival, associating past experiences (to identify location patterns) predicts where they can be found. Similarly, prediction may enable predator identification from what would have been only a fleeting and ambiguous stimulus-without prior expectations. To confront the many challenges associated with natural settings, visual perception is vital for humans (and most mammals) and often responses must be rapid. Predictive coding during wake may, therefore, be based on unconscious imagery so that visual perception is maintained and appropriate motor actions triggered quickly. Speed may also dictate the form of the imagery. Bizarreness, during REM dreaming, may result from a prospective code fusing phenomena with the same meaning-within a particular context. For example, if the context is possible predation, from the perspective of the prey two different predators can both mean the same (i.e., immediate danger) and require the same response (e.g., flight). Prospective coding may also prune redundancy from memories, to focus the image on the contextually-relevant elements only, thus, rendering the non-relevant phenomena indeterminate-another aspect of bizarreness. In sum, this paper offers an evolutionary take on REM dreaming as a form of prospective coding which identifies a probabilistic pattern in past events. This pattern is portrayed in an unconscious, associative, sensorimotor image which may support cognition in wake through being mobilized as a predictive code. A particular dream illustrates.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 1%
Portugal 1 1%
Germany 1 1%
France 1 1%
United States 1 1%
Unknown 79 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 19%
Student > Master 12 14%
Student > Bachelor 12 14%
Researcher 10 12%
Other 4 5%
Other 11 13%
Unknown 19 23%
Readers by discipline Count As %
Psychology 28 33%
Neuroscience 15 18%
Agricultural and Biological Sciences 5 6%
Biochemistry, Genetics and Molecular Biology 3 4%
Engineering 3 4%
Other 7 8%
Unknown 23 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2023.
All research outputs
#2,297,564
of 25,888,937 outputs
Outputs from Frontiers in Psychology
#4,616
of 34,854 outputs
Outputs of similar age
#37,520
of 402,165 outputs
Outputs of similar age from Frontiers in Psychology
#91
of 447 outputs
Altmetric has tracked 25,888,937 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 34,854 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,165 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 447 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.