We can talk about not only the topics in front of us, but also the topics of the past and the future. We are discussing while confirming each other's imagination and understanding. Even in the era when humans did not have letters, they negotiated the exchange of goods, gained new knowledge, and expanded their living area. Of course, using letters further developed civilization to the present day. The group of humans is called society, and the ability to dialogue is essential to be a member of that group. What are the functions required for dialogue ability? This is the starting point of this paper. Trained livestock can understand how to act with the owner's commands or gestures. However, it is not possible to return messages to the owner, such as having leftover work or interruption of work due to inconvenient work etc. This message is the language itself that shows the ability to dialogue. This paper shows that to enable two-way dialogue, both brains need two areas related to language. One area consists of the time series of symbols, and the other area consists of images activated by responses from the symbol area. This structure and behavior are consistent with the knowledge of Cerebrum in neuroscience. The basic logical circuits of neural networks follow Hebb's law in neuroscience, and by connecting them hierarchically, arbitrary logical circuits can be realized with limited scale.
| Published in | American Journal of Neural Networks and Applications (Volume 12, Issue 1) |
| DOI | 10.11648/j.ajnna.20261201.14 |
| Page(s) | 34-39 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2026. Published by Science Publishing Group |
Context Corresponding Neuron Layers, Getting Knowledge by Dialogue, Dynamically Recognize the Object, Dialog Between Fellows, Image World in Cerebrum, Real World in Cerebrum, Linking Symbols and Images
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APA Style
Yanagawa, S. (2026). Neural Networks with Cerebrum Functions Can Exchange Knowledge by Dialog. American Journal of Neural Networks and Applications, 12(1), 34-39. https://doi.org/10.11648/j.ajnna.20261201.14
ACS Style
Yanagawa, S. Neural Networks with Cerebrum Functions Can Exchange Knowledge by Dialog. Am. J. Neural Netw. Appl. 2026, 12(1), 34-39. doi: 10.11648/j.ajnna.20261201.14
AMA Style
Yanagawa S. Neural Networks with Cerebrum Functions Can Exchange Knowledge by Dialog. Am J Neural Netw Appl. 2026;12(1):34-39. doi: 10.11648/j.ajnna.20261201.14
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Download@article{10.11648/j.ajnna.20261201.14,
author = {Seisuke Yanagawa},
title = {Neural Networks with Cerebrum Functions Can Exchange Knowledge by Dialog},
journal = {American Journal of Neural Networks and Applications},
volume = {12},
number = {1},
pages = {34-39},
doi = {10.11648/j.ajnna.20261201.14},
url = {https://doi.org/10.11648/j.ajnna.20261201.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20261201.14},
abstract = {We can talk about not only the topics in front of us, but also the topics of the past and the future. We are discussing while confirming each other's imagination and understanding. Even in the era when humans did not have letters, they negotiated the exchange of goods, gained new knowledge, and expanded their living area. Of course, using letters further developed civilization to the present day. The group of humans is called society, and the ability to dialogue is essential to be a member of that group. What are the functions required for dialogue ability? This is the starting point of this paper. Trained livestock can understand how to act with the owner's commands or gestures. However, it is not possible to return messages to the owner, such as having leftover work or interruption of work due to inconvenient work etc. This message is the language itself that shows the ability to dialogue. This paper shows that to enable two-way dialogue, both brains need two areas related to language. One area consists of the time series of symbols, and the other area consists of images activated by responses from the symbol area. This structure and behavior are consistent with the knowledge of Cerebrum in neuroscience. The basic logical circuits of neural networks follow Hebb's law in neuroscience, and by connecting them hierarchically, arbitrary logical circuits can be realized with limited scale.},
year = {2026}
}
TY - JOUR T1 - Neural Networks with Cerebrum Functions Can Exchange Knowledge by Dialog AU - Seisuke Yanagawa Y1 - 2026/04/20 PY - 2026 N1 - https://doi.org/10.11648/j.ajnna.20261201.14 DO - 10.11648/j.ajnna.20261201.14 T2 - American Journal of Neural Networks and Applications JF - American Journal of Neural Networks and Applications JO - American Journal of Neural Networks and Applications SP - 34 EP - 39 PB - Science Publishing Group SN - 2469-7419 UR - https://doi.org/10.11648/j.ajnna.20261201.14 AB - We can talk about not only the topics in front of us, but also the topics of the past and the future. We are discussing while confirming each other's imagination and understanding. Even in the era when humans did not have letters, they negotiated the exchange of goods, gained new knowledge, and expanded their living area. Of course, using letters further developed civilization to the present day. The group of humans is called society, and the ability to dialogue is essential to be a member of that group. What are the functions required for dialogue ability? This is the starting point of this paper. Trained livestock can understand how to act with the owner's commands or gestures. However, it is not possible to return messages to the owner, such as having leftover work or interruption of work due to inconvenient work etc. This message is the language itself that shows the ability to dialogue. This paper shows that to enable two-way dialogue, both brains need two areas related to language. One area consists of the time series of symbols, and the other area consists of images activated by responses from the symbol area. This structure and behavior are consistent with the knowledge of Cerebrum in neuroscience. The basic logical circuits of neural networks follow Hebb's law in neuroscience, and by connecting them hierarchically, arbitrary logical circuits can be realized with limited scale. VL - 12 IS - 1 ER -
Japanese Neural Network Society, Tokyo, Japan
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