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Brain-Inspired Communication Technologies: Information Networks with Continuing Internal Dynamics and Fluctuation
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Summary :
Computation in the brain is realized in complicated, heterogeneous, and extremely large-scale network of neurons. About a hundred billion neurons communicate with each other by action potentials called “spike firings” that are delivered to thousands of other neurons from each. Repeated integration and networking of these spike trains in the network finally form the substance of our cognition, perception, planning, and motor control. Beyond conventional views of neural network mechanisms, recent rapid advances in both experimental and theoretical neuroscience unveil that the brain is a dynamical system to actively treat environmental information rather passively process it. The brain utilizes internal dynamics to realize our resilient and efficient perception and behavior. In this paper, by considering similarities and differences of the brain and information networks, we discuss a possibility of information networks with brain-like continuing internal dynamics. We expect that the proposed networks efficiently realize context-dependent in-network processing. By introducing recent findings of neuroscience about dynamics of the brain, we argue validity and clues for implementation of the proposal.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E98-B No.1 pp.153-159
- Publication Date
- 2015/01/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E98.B.153
- Type of Manuscript
- Special Section PAPER (Special Section on Position Papers Exploring Innovative Intelligence and Technologies in Communications)
- Category
Authors
Jun-nosuke TERAMAE
Osaka University
Naoki WAKAMIYA
Osaka University
Keyword
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Jun-nosuke TERAMAE, Naoki WAKAMIYA, "Brain-Inspired Communication Technologies: Information Networks with Continuing Internal Dynamics and Fluctuation" in IEICE TRANSACTIONS on Communications,
vol. E98-B, no. 1, pp. 153-159, January 2015, doi: 10.1587/transcom.E98.B.153.
Abstract: Computation in the brain is realized in complicated, heterogeneous, and extremely large-scale network of neurons. About a hundred billion neurons communicate with each other by action potentials called “spike firings” that are delivered to thousands of other neurons from each. Repeated integration and networking of these spike trains in the network finally form the substance of our cognition, perception, planning, and motor control. Beyond conventional views of neural network mechanisms, recent rapid advances in both experimental and theoretical neuroscience unveil that the brain is a dynamical system to actively treat environmental information rather passively process it. The brain utilizes internal dynamics to realize our resilient and efficient perception and behavior. In this paper, by considering similarities and differences of the brain and information networks, we discuss a possibility of information networks with brain-like continuing internal dynamics. We expect that the proposed networks efficiently realize context-dependent in-network processing. By introducing recent findings of neuroscience about dynamics of the brain, we argue validity and clues for implementation of the proposal.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.153/_p
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@ARTICLE{e98-b_1_153,
author={Jun-nosuke TERAMAE, Naoki WAKAMIYA, },
journal={IEICE TRANSACTIONS on Communications},
title={Brain-Inspired Communication Technologies: Information Networks with Continuing Internal Dynamics and Fluctuation},
year={2015},
volume={E98-B},
number={1},
pages={153-159},
abstract={Computation in the brain is realized in complicated, heterogeneous, and extremely large-scale network of neurons. About a hundred billion neurons communicate with each other by action potentials called “spike firings” that are delivered to thousands of other neurons from each. Repeated integration and networking of these spike trains in the network finally form the substance of our cognition, perception, planning, and motor control. Beyond conventional views of neural network mechanisms, recent rapid advances in both experimental and theoretical neuroscience unveil that the brain is a dynamical system to actively treat environmental information rather passively process it. The brain utilizes internal dynamics to realize our resilient and efficient perception and behavior. In this paper, by considering similarities and differences of the brain and information networks, we discuss a possibility of information networks with brain-like continuing internal dynamics. We expect that the proposed networks efficiently realize context-dependent in-network processing. By introducing recent findings of neuroscience about dynamics of the brain, we argue validity and clues for implementation of the proposal.},
keywords={},
doi={10.1587/transcom.E98.B.153},
ISSN={1745-1345},
month={January},}
Copy
TY - JOUR
TI - Brain-Inspired Communication Technologies: Information Networks with Continuing Internal Dynamics and Fluctuation
T2 - IEICE TRANSACTIONS on Communications
SP - 153
EP - 159
AU - Jun-nosuke TERAMAE
AU - Naoki WAKAMIYA
PY - 2015
DO - 10.1587/transcom.E98.B.153
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2015
AB - Computation in the brain is realized in complicated, heterogeneous, and extremely large-scale network of neurons. About a hundred billion neurons communicate with each other by action potentials called “spike firings” that are delivered to thousands of other neurons from each. Repeated integration and networking of these spike trains in the network finally form the substance of our cognition, perception, planning, and motor control. Beyond conventional views of neural network mechanisms, recent rapid advances in both experimental and theoretical neuroscience unveil that the brain is a dynamical system to actively treat environmental information rather passively process it. The brain utilizes internal dynamics to realize our resilient and efficient perception and behavior. In this paper, by considering similarities and differences of the brain and information networks, we discuss a possibility of information networks with brain-like continuing internal dynamics. We expect that the proposed networks efficiently realize context-dependent in-network processing. By introducing recent findings of neuroscience about dynamics of the brain, we argue validity and clues for implementation of the proposal.
ER -
English
