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Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

Overview of attention for article published in Frontiers in Systems Neuroscience, November 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 1,410)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

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19 news outlets
blogs
7 blogs
twitter
394 X users
facebook
9 Facebook pages
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22 Google+ users
reddit
6 Redditors

Citations

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28 Dimensions

Readers on

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254 Mendeley
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Title
Brain Computation Is Organized via Power-of-Two-Based Permutation Logic
Published in
Frontiers in Systems Neuroscience, November 2016
DOI 10.3389/fnsys.2016.00095
Pubmed ID
Authors

Kun Xie, Grace E. Fox, Jun Liu, Cheng Lyu, Jason C. Lee, Hui Kuang, Stephanie Jacobs, Meng Li, Tianming Liu, Sen Song, Joe Z. Tsien

Abstract

There is considerable scientific interest in understanding how cell assemblies-the long-presumed computational motif-are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2 (i) -1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors-the synaptic switch for learning and memory-were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques-which preferentially encode specific and low-combinatorial features and project inter-cortically-is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6-which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems-is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain's basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

X Demographics

X Demographics

The data shown below were collected from the profiles of 394 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 254 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 4 2%
Spain 2 <1%
Germany 2 <1%
Bulgaria 1 <1%
India 1 <1%
Canada 1 <1%
Hong Kong 1 <1%
Mexico 1 <1%
Other 3 1%
Unknown 234 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 25%
Researcher 48 19%
Student > Master 31 12%
Student > Bachelor 27 11%
Other 20 8%
Other 37 15%
Unknown 27 11%
Readers by discipline Count As %
Computer Science 65 26%
Neuroscience 44 17%
Agricultural and Biological Sciences 25 10%
Engineering 19 7%
Psychology 18 7%
Other 53 21%
Unknown 30 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 482. 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 20 January 2022.
All research outputs
#56,373
of 25,804,096 outputs
Outputs from Frontiers in Systems Neuroscience
#3
of 1,410 outputs
Outputs of similar age
#1,127
of 313,101 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#1
of 26 outputs
Altmetric has tracked 25,804,096 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 1,410 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. 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 313,101 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 26 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 96% of its contemporaries.