The Intrinsic Properties of Brain Based on the Network Structure Article Swipe
Xiang Zou
,
Lie Yao
,
Donghua Zhao
,
Liang Chen
,
Ying Mao
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1911.00640
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1911.00640
Objective: Brain is a fantastic organ that helps creature adapting to the environment. Network is the most essential structure of brain, but the capability of a simple network is still not very clear. In this study, we try to expound some brain functions only by the network property. Methods: Every network can be equivalent to a simplified network, which is expressed by an equation set. The dynamic of the equation set can be described by some basic equations, which is based on the mathematical derivation. Results (1) In a closed network, the stability is based on the excitatory/inhibitory synapse proportion. Spike probabilities in the assembly can meet the solution of a nonlinear equation set. (2) Network activity can spontaneously evolve into a certain distribution under different stimulation, which is closely related to decision making. (3) Short memory can be formed by coupling of network assemblies. Conclusion: The essential property of a network may contribute to some important brain functions.
Related Topics
Concepts
Property (philosophy)
Computer science
Set (abstract data type)
Spike (software development)
Nonlinear system
Stability (learning theory)
Simple (philosophy)
Network structure
Biological neural network
Artificial neural network
Synapse
Artificial intelligence
Theoretical computer science
Neuroscience
Physics
Machine learning
Psychology
Philosophy
Programming language
Software engineering
Quantum mechanics
Epistemology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1911.00640
- https://arxiv.org/pdf/1911.00640
- OA Status
- green
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2989274750
All OpenAlex metadata
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https://openalex.org/W2989274750Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1911.00640Digital Object Identifier
- Title
-
The Intrinsic Properties of Brain Based on the Network StructureWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-11-02Full publication date if available
- Authors
-
Xiang Zou, Lie Yao, Donghua Zhao, Liang Chen, Ying MaoList of authors in order
- Landing page
-
https://arxiv.org/abs/1911.00640Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1911.00640Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1911.00640Direct OA link when available
- Concepts
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Property (philosophy), Computer science, Set (abstract data type), Spike (software development), Nonlinear system, Stability (learning theory), Simple (philosophy), Network structure, Biological neural network, Artificial neural network, Synapse, Artificial intelligence, Theoretical computer science, Neuroscience, Physics, Machine learning, Psychology, Philosophy, Programming language, Software engineering, Quantum mechanics, EpistemologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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5Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 11, 15, 22, 45, 68, 82, 91, 96, 103, 107 |
| abstract_inverted_index.try | 37 |
| abstract_inverted_index.into | 120 |
| abstract_inverted_index.meet | 106 |
| abstract_inverted_index.most | 16 |
| abstract_inverted_index.only | 43 |
| abstract_inverted_index.set. | 64, 113 |
| abstract_inverted_index.some | 40, 75, 155 |
| abstract_inverted_index.that | 6 |
| abstract_inverted_index.this | 34 |
| abstract_inverted_index.very | 31 |
| abstract_inverted_index.Brain | 1 |
| abstract_inverted_index.Every | 49 |
| abstract_inverted_index.Short | 135 |
| abstract_inverted_index.Spike | 100 |
| abstract_inverted_index.based | 80, 94 |
| abstract_inverted_index.basic | 76 |
| abstract_inverted_index.brain | 41, 157 |
| abstract_inverted_index.helps | 7 |
| abstract_inverted_index.organ | 5 |
| abstract_inverted_index.still | 29 |
| abstract_inverted_index.under | 124 |
| abstract_inverted_index.which | 58, 78, 127 |
| abstract_inverted_index.brain, | 20 |
| abstract_inverted_index.clear. | 32 |
| abstract_inverted_index.closed | 89 |
| abstract_inverted_index.evolve | 119 |
| abstract_inverted_index.formed | 139 |
| abstract_inverted_index.memory | 136 |
| abstract_inverted_index.simple | 26 |
| abstract_inverted_index.study, | 35 |
| abstract_inverted_index.Network | 13, 115 |
| abstract_inverted_index.Results | 85 |
| abstract_inverted_index.certain | 122 |
| abstract_inverted_index.closely | 129 |
| abstract_inverted_index.dynamic | 66 |
| abstract_inverted_index.expound | 39 |
| abstract_inverted_index.making. | 133 |
| abstract_inverted_index.network | 27, 46, 50, 143, 151 |
| abstract_inverted_index.related | 130 |
| abstract_inverted_index.synapse | 98 |
| abstract_inverted_index.Methods: | 48 |
| abstract_inverted_index.activity | 116 |
| abstract_inverted_index.adapting | 9 |
| abstract_inverted_index.assembly | 104 |
| abstract_inverted_index.coupling | 141 |
| abstract_inverted_index.creature | 8 |
| abstract_inverted_index.decision | 132 |
| abstract_inverted_index.equation | 63, 69, 112 |
| abstract_inverted_index.network, | 57, 90 |
| abstract_inverted_index.property | 148 |
| abstract_inverted_index.solution | 108 |
| abstract_inverted_index.described | 73 |
| abstract_inverted_index.different | 125 |
| abstract_inverted_index.essential | 17, 147 |
| abstract_inverted_index.expressed | 60 |
| abstract_inverted_index.fantastic | 4 |
| abstract_inverted_index.functions | 42 |
| abstract_inverted_index.important | 156 |
| abstract_inverted_index.nonlinear | 111 |
| abstract_inverted_index.property. | 47 |
| abstract_inverted_index.stability | 92 |
| abstract_inverted_index.structure | 18 |
| abstract_inverted_index.Objective: | 0 |
| abstract_inverted_index.capability | 23 |
| abstract_inverted_index.contribute | 153 |
| abstract_inverted_index.equations, | 77 |
| abstract_inverted_index.equivalent | 53 |
| abstract_inverted_index.functions. | 158 |
| abstract_inverted_index.simplified | 56 |
| abstract_inverted_index.Conclusion: | 145 |
| abstract_inverted_index.assemblies. | 144 |
| abstract_inverted_index.derivation. | 84 |
| abstract_inverted_index.proportion. | 99 |
| abstract_inverted_index.distribution | 123 |
| abstract_inverted_index.environment. | 12 |
| abstract_inverted_index.mathematical | 83 |
| abstract_inverted_index.stimulation, | 126 |
| abstract_inverted_index.probabilities | 101 |
| abstract_inverted_index.spontaneously | 118 |
| abstract_inverted_index.excitatory/inhibitory | 97 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.8299999833106995 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |