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Embedding Responses in Spontaneous Neural Activity Shaped through Sequential Learning

Overview of attention for article published in PLoS Computational Biology, March 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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10 X users
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1 Facebook page

Citations

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20 Dimensions

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76 Mendeley
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3 CiteULike
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Title
Embedding Responses in Spontaneous Neural Activity Shaped through Sequential Learning
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002943
Pubmed ID
Authors

Tomoki Kurikawa, Kunihiko Kaneko

Abstract

Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in our previous study.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 4%
Switzerland 2 3%
United States 2 3%
Japan 2 3%
China 1 1%
Spain 1 1%
Unknown 65 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Researcher 15 20%
Student > Master 12 16%
Professor 7 9%
Professor > Associate Professor 6 8%
Other 13 17%
Unknown 7 9%
Readers by discipline Count As %
Neuroscience 14 18%
Agricultural and Biological Sciences 13 17%
Physics and Astronomy 9 12%
Engineering 8 11%
Computer Science 8 11%
Other 14 18%
Unknown 10 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 27 September 2023.
All research outputs
#7,064,386
of 25,759,158 outputs
Outputs from PLoS Computational Biology
#4,714
of 9,032 outputs
Outputs of similar age
#55,498
of 208,592 outputs
Outputs of similar age from PLoS Computational Biology
#48
of 151 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 9,032 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.2. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 208,592 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 151 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.