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无形的大脑:研究著作中的知识与神经元活动

Invisible Brain: Knowledge in Research Works and Neuron Activity.

作者信息

Segev Aviv, Curtis Dorothy, Jung Sukhwan, Chae Suhyun

机构信息

Graduate School of Knowledge Service Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, South Korea.

School of Computing, KAIST, 291 Daehak-ro, Yuseong-gu, 305-701, South Korea.

出版信息

PLoS One. 2016 Jul 20;11(7):e0158590. doi: 10.1371/journal.pone.0158590. eCollection 2016.

DOI:10.1371/journal.pone.0158590
PMID:27439199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4954711/
Abstract

If the market has an invisible hand, does knowledge creation and representation have an "invisible brain"? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an "invisible brain" or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism.

摘要

如果市场有一只“看不见的手”,那么知识创造与呈现是否有一个“看不见的大脑”呢?虽然知识被视为大脑中神经元活动的产物,但我们能否识别出存在于大脑之外却反映大脑中神经元活动的知识呢?这项研究表明,大脑中神经元活动的模式能够在与知识相关的活动呈现中被观察到。在此我们表明,基于已发表的文章,神经元活动机制似乎呈现了过去几十年中学到的大部分知识,这可以被看作是一个“看不见的大脑”或集体隐藏神经网络。在分析专利中的知识活动时也出现了类似的结果。我们的研究还试图将知识增长描述为神经网络活动的增长。结果表明,与知识相关的活动能够在神经元活动机制之外被观察到。因此,知识可能作为一种独立的机制存在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/4315a655ed9e/pone.0158590.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/52f9b1c68267/pone.0158590.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/c7b2166ddcf3/pone.0158590.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/6601a41a4971/pone.0158590.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/50b2b7336fde/pone.0158590.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/936e4c274203/pone.0158590.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/4315a655ed9e/pone.0158590.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/52f9b1c68267/pone.0158590.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/c7b2166ddcf3/pone.0158590.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/6601a41a4971/pone.0158590.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/50b2b7336fde/pone.0158590.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/936e4c274203/pone.0158590.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23c8/4954711/4315a655ed9e/pone.0158590.g006.jpg

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Transfer entropy reconstruction and labeling of neuronal connections from simulated calcium imaging.从模拟钙成像中重建和标记神经元连接的转移熵。
PLoS One. 2014 Jun 6;9(6):e98842. doi: 10.1371/journal.pone.0098842. eCollection 2014.
2
Testing for effects of different stimuli on neuronal firing relative to background activity.检测不同刺激对神经元放电相对于背景活动的影响。
J Neural Eng. 2013 Oct;10(5):056019. doi: 10.1088/1741-2560/10/5/056019. Epub 2013 Sep 18.
3
From the connectome to brain function.从连接组学到脑功能。
Nat Methods. 2013 Jun;10(6):483-90. doi: 10.1038/nmeth.2451.
4
Whole-brain functional imaging at cellular resolution using light-sheet microscopy.使用光片显微镜进行细胞分辨率的全脑功能成像。
Nat Methods. 2013 May;10(5):413-20. doi: 10.1038/nmeth.2434. Epub 2013 Mar 18.
5
Mapping a complete neural population in the retina.在视网膜中绘制完整的神经群体图谱。
J Neurosci. 2012 Oct 24;32(43):14859-73. doi: 10.1523/JNEUROSCI.0723-12.2012.
6
Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals.无模型重建钙成像信号中的兴奋性神经元连接
PLoS Comput Biol. 2012;8(8):e1002653. doi: 10.1371/journal.pcbi.1002653. Epub 2012 Aug 23.
7
Neural population dynamics during reaching.在到达过程中的神经群体动力学。
Nature. 2012 Jul 5;487(7405):51-6. doi: 10.1038/nature11129.
8
Brain-wide neuronal dynamics during motor adaptation in zebrafish.斑马鱼运动适应过程中的全脑神经元动力学。
Nature. 2012 May 9;485(7399):471-7. doi: 10.1038/nature11057.
9
Dynamic effective connectivity of inter-areal brain circuits.区域间脑回路的动态有效连通性。
PLoS Comput Biol. 2012;8(3):e1002438. doi: 10.1371/journal.pcbi.1002438. Epub 2012 Mar 22.
10
Two-photon calcium imaging in the intact brain.双光子钙成像技术在完整大脑中的应用。
Adv Exp Med Biol. 2012;740:83-102. doi: 10.1007/978-94-007-2888-2_4.