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Principles of Intelligence: On Evolutionary Logic of the Brain

Overview of attention for article published in Frontiers in Systems Neuroscience, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 blog
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14 X users
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2 Facebook pages
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1 Wikipedia page

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89 Mendeley
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Title
Principles of Intelligence: On Evolutionary Logic of the Brain
Published in
Frontiers in Systems Neuroscience, February 2016
DOI 10.3389/fnsys.2015.00186
Pubmed ID
Authors

Joe Z. Tsien

Abstract

Humans and animals may encounter numerous events, objects, scenes, foods and countless social interactions in a lifetime. This means that the brain is constructed by evolution to deal with uncertainties and various possibilities. What is the architectural abstraction of intelligence that enables the brain to discover various possible patterns and knowledge about complex, evolving worlds? Here, I discuss the Theory of Connectivity-a "power-of-two" based, operational principle that can serve as a unified wiring and computational logic for organizing and constructing cell assemblies into the microcircuit-level building block, termed as functional connectivity motif (FCM). Defined by the power-of-two based equation, N = 2 (i) -1, each FCM consists of the principal projection neuron cliques (N), ranging from those specific cliques receiving specific information inputs (i) to those general and sub-general cliques receiving various combinatorial convergent inputs. As the evolutionarily conserved logic, its validation requires experimental demonstrations of the following three major properties: (1) Anatomical prevalence-FCMs are prevalent across neural circuits, regardless of gross anatomical shapes; (2) Species conservancy-FCMs are conserved across different animal species; and (3) Cognitive universality-FCMs serve as a universal computational logic at the cell assembly level for processing a variety of cognitive experiences and flexible behaviors. More importantly, this Theory of Connectivity further predicts that the specific-to-general combinatorial connectivity pattern within FCMs should be preconfigured by evolution, and emerge innately from development as the brain's computational primitives. This proposed design-principle can also explain the general purpose of the layered cortex and serves as its core computational algorithm.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Spain 1 1%
France 1 1%
Unknown 85 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 24%
Student > Master 14 16%
Student > Ph. D. Student 11 12%
Student > Bachelor 7 8%
Student > Postgraduate 5 6%
Other 16 18%
Unknown 15 17%
Readers by discipline Count As %
Neuroscience 16 18%
Computer Science 13 15%
Psychology 9 10%
Agricultural and Biological Sciences 8 9%
Medicine and Dentistry 5 6%
Other 19 21%
Unknown 19 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 September 2021.
All research outputs
#1,599,247
of 22,836,570 outputs
Outputs from Frontiers in Systems Neuroscience
#132
of 1,344 outputs
Outputs of similar age
#30,736
of 397,099 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#3
of 43 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done particularly well, scoring higher than 90% 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 397,099 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 92% of its contemporaries.
We're also able to compare this research output to 43 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 93% of its contemporaries.