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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
853 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 583 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 853 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 29 3%
United Kingdom 12 1%
Japan 11 1%
Germany 9 1%
France 6 <1%
Canada 5 <1%
Chile 4 <1%
Netherlands 4 <1%
Italy 3 <1%
Other 27 3%
Unknown 743 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 200 23%
Researcher 187 22%
Student > Master 129 15%
Student > Bachelor 105 12%
Student > Doctoral Student 53 6%
Other 179 21%
Readers by discipline Count As %
Psychology 224 26%
Agricultural and Biological Sciences 179 21%
Neuroscience 128 15%
Medicine and Dentistry 77 9%
Computer Science 67 8%
Other 178 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 944. 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 05 April 2018.
All research outputs
#2,769
of 9,725,395 outputs
Outputs from Science
#158
of 45,194 outputs
Outputs of similar age
#31
of 126,463 outputs
Outputs of similar age from Science
#2
of 743 outputs
Altmetric has tracked 9,725,395 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 45,194 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.8. 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 126,463 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 743 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.