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Neural Decoding of Visual Imagery During Sleep

Overview of attention for article published in Science, April 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Readers on

mendeley
797 Mendeley
citeulike
8 CiteULike
Title
Neural Decoding of Visual Imagery During Sleep
Published in
Science, April 2013
DOI 10.1126/science.1234330
Pubmed ID
Authors

T. Horikawa, M. Tamaki, Y. Miyawaki, Y. Kamitani, Horikawa T, Tamaki M, Miyawaki Y, Kamitani Y

Abstract

Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.

Twitter Demographics

The data shown below were collected from the profiles of 581 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 797 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 29 4%
United Kingdom 13 2%
Japan 10 1%
Germany 8 1%
Canada 5 <1%
France 5 <1%
Netherlands 5 <1%
Chile 4 <1%
Italy 3 <1%
Other 21 3%
Unknown 694 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 180 23%
Researcher 156 20%
Student > Master 109 14%
Student > Bachelor 92 12%
Student > Doctoral Student 47 6%
Other 148 19%
Unknown 65 8%
Readers by discipline Count As %
Psychology 209 26%
Agricultural and Biological Sciences 177 22%
Neuroscience 85 11%
Medicine and Dentistry 77 10%
Computer Science 63 8%
Other 121 15%
Unknown 65 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 904. 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 25 June 2017.
All research outputs
#2,040
of 7,945,514 outputs
Outputs from Science
#118
of 40,500 outputs
Outputs of similar age
#28
of 117,967 outputs
Outputs of similar age from Science
#2
of 744 outputs
Altmetric has tracked 7,945,514 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 40,500 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 32.0. This one has done particularly well, scoring higher than 99% 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 117,967 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 99% of its contemporaries.
We're also able to compare this research output to 744 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.