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
722 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 591 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 722 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 30 4%
United Kingdom 15 2%
Germany 10 1%
Japan 10 1%
Canada 5 <1%
France 5 <1%
Netherlands 5 <1%
Chile 4 <1%
Italy 3 <1%
Other 23 3%
Unknown 612 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 188 26%
Researcher 153 21%
Student > Master 103 14%
Student > Bachelor 87 12%
Student > Doctoral Student 45 6%
Other 146 20%
Readers by discipline Count As %
Psychology 199 28%
Agricultural and Biological Sciences 181 25%
Medicine and Dentistry 77 11%
Neuroscience 73 10%
Computer Science 64 9%
Other 128 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 901. 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 21 February 2017.
All research outputs
#1,739
of 7,430,338 outputs
Outputs from Science
#95
of 39,148 outputs
Outputs of similar age
#26
of 115,685 outputs
Outputs of similar age from Science
#2
of 744 outputs
Altmetric has tracked 7,430,338 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 39,148 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.7. 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 115,685 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.